The platform promises reduced “candidate churn” using conversation AI and automated interview settings. In addition, the company’s financial model only requires users to pay when a candidate is hired.

“Hiring teams spend the most time creating jobs, screening resumes, scheduling interviews… At Fyndo, we realized that most of these tasks [could] be automated using the technology,” said Fyndo Chief Product Officer Kaushik Vinay.

AI-Driven

Fyndo describes its solution as an AI-driven recruitment platform that automates the hiring process for the hiring teams at SMBs. The platform sources, screens and schedules interviews with the best-matching candidates, the company said, relying only on minor human intervention. In addition, the automated process completes hiring more quickly and eliminates unintentional human bias during the screening process, Fyndo said.

Fyndo CEO Amit Chauhan estimates recruiters can get back one hour each day during the recruitment process by using his platform. “Hiring teams spend too much time doing tasks that could be automated and improved by today’s technology,” he said.

Fyndo distributes job postings to “major” job sites with one click, allowing employers to quickly reach both active and passive candidates. Its proprietary AI technology screens job description data points and matches them against a candidate’s information, Fyndo said. It then showcases the best candidates and notably reduces the time spent reviewing applications. The AI also detects fraud and spam applications and removes them from the application pool.

Fyndo said it uses AI to automate job creation, distribution, candidate screening and communication. The use of AI, Fyndo said, allows employers to speed up their hiring process, reach more candidates and keep interested candidates engaged.

The post Hiring Automation Platform Fyndo Launches for SMBs appeared first on RecruitingDaily.

With the advent of artificial intelligence, the recruitment process has become simpler and more efficient. Now, applicants can send their resumes online; the software scans all details, and interviews are set automatically.

The increasing use of AI in various industries, including recruiting, is constantly expanding in the current commercial ecosystem.

While AI technology cannot fully replace the natural human cognitive ability, new solutions that have similar functions to some extent are available. These software types include machine learning technology, allowing them to learn, make decisions, and process information without manual input.

Companies in various business sectors enjoy the flexibility of AI integration in devices, tools, and programs. As a result, they are adopting these solutions to automate and enhance their normal processes.

For example, ChatGPT is trained for large-scale human-generated text analysis and generates similarly styled responses. In recruitment processes, this is useful for automating the initial interview process.

The Benefits of AI in Recruiting

Businesses adopting AI-based solutions for the recruitment process have seen many advantages. In this regard, you can also expect some benefits of AI in recruitment in your industry.

Time-saving and Efficiency

AI-based recruitment solutions are increasingly used by businesses, primarily to shorten the duration of the hiring process overall.

According to reports, talent acquisition experts typically spend around 13 hours (or one-third of their estimated workweek schedule) sourcing applicants for just one open position. This is only the first stage of the process—the overall hiring process involves many more steps.

Therefore, recruiters have started to prefer AI-powered software as it can streamline their talent acquisition process. The algorithms scan the applicants based on specific criteria, assign interview dates, and even provide assessment results—all in a shorter period of time.

Reducing Bias in the Recruitment Process

With an AI-based intelligent scanning system, you can screen all applicants faster per your set regulations, like specialization type, employment experience, and educational background.

To note, the AI-based software only relies on the recruitment-related criteria points regarding attributes, skills, and knowledge to hire team members. This helps in reducing bias during the recruitment process.

Enhancing the Quality of Hires

On average, companies in European countries take around 30 days to hire staff, while American companies take approximately 23.8 days. However, the more prominent companies acquire top-level candidates with the best-of-the-best credentials within the first few days. Thus, you need to conduct a fast and smooth recruitment process.

With AI-powered software for recruitment, it is faster to shift through the applications and target the most suitable candidates for the work. Additionally, these solutions can automate the overall workflow, leaving the recruiters free to focus on a complete analysis of the top candidates or the open position.

So, avoid spending time shifting through applications and conducting the interview processes early.

Case Studies: Examples of AI Use in Recruiting

For a better understanding of the impact of artificial intelligence in recruiting, here are some real-world AI recruitment examples for reference.

1.   IBM’s Watson Recruitment Tool

This application for Talent Suite works with the cognitive mechanisms within the ATS (Application Tracking System) of clients. It helps deliver a high-quality recruitment experience.

With this tool, recruiters can match the candidates’ skills with the company’s requirements, prioritize requisitions, recognize that applicants have the highest growth potential via predictive hiring, etc.

2.   Unilever’s AI-based Video Interviewing Tool

Incorporating video interviewing functionality for recruitment is highly useful to avoid issues like candidate ghosting. This initiative’s primary focus is to save time with the interview process by allowing recruiters to interact with applicants directly via video conference.

3.   Hilton’s Use of AI for Talent Acquisition

Hilton integrated AI mechanisms in their hiring model for optimized talent acquisition. The software evaluated the candidates and their information, increasing hiring rates by forty percent and reducing vacant position fill-up time by 90%.

Future of AI in Recruiting

The role of artificial intelligence in recruitment is expected to improve in the coming years, as evidenced by its current expansion in varying industries. The main issues that need to be addressed in this regard are as follows.  

Advancements in AI technology

These solutions are operational in diverse fields, like manufacturing, telecommunications, financial services, retail, and professional services. Not to mention, all sectors have noticed growth with AI-powered automation tools and solutions.

There can be several benefits of AI in recruitment, including:

• Personalized application and recruitment experience for candidates
• Automatic hiring processes
• Predictive hiring support based on critical parameters, like knowledge base, experience, etc.
• More inclusion and diversity in the team

Ethical Concerns and the Need for Regulation

AI-based software for recruitment purposes includes various novel assessment and talent acquisition tools. For example, they assess different application information based on voice inflections, personal data, and other details to decide who is the right candidate for a job.

However, it is difficult to deduce what precisely the software judges to draw insights, so guaranteeing an entirely ethical recruitment process is impossible. These tools’ machine learning ability analyzes data and adapts to what they learn. These systems are susceptible to learned biases too.

Developers of these solutions prioritize properly balancing all data used for AI model training to cover details for all demographic groups to avoid biased hiring.

The Role of HR professionals in the Changing Landscape of Recruitment

The HR department in most companies today is shifting towards technological solutions to streamline its workflow. More of these professionals are adopting collaborative tools for workforce management, including automated hiring models for the company.

They depend on these tools more since they allow them to focus on other, more stringent processes requiring focused manual attention. So, using automated recruitment systems will decrease human intervention here and digitize the process more.

Wrapping Up

There are many AI recruitment examples for judging job applicants and choosing the right talent for the company. Now, job opening emails can be sent with attractive subject lines to attract applicants due to the emerging role of artificial intelligence in recruitment. More companies will adopt these solutions over time to save money and time while streamlining the recruitment process.

However, while the benefits are high, HR professionals need to note the potential ethical implications of AI in their recruiting practices.

The post The Impact of Artificial Intelligence on Recruiting appeared first on RecruitingDaily.

And, recruiting is no exception – from creating interview questions and job ad templates to following up with candidates, ChatGPT has many potential applications in the field. However, it would be a mistake to treat the technology as a silver bullet. Seriously!

ChatGPT is undeniably impressive as a dynamic language model, but it also has a habit of getting basic questions wrong, providing nonsensical interpretations, and presenting these mistakes in a convincing way to users who aren’t familiar with the subject matter at all. Don’t believe me? Just go down a reddit hole.

Now, don’t get me wrong. These problems certainly don’t make ChatGPT useless for recruiters, but they provide ample cause for caution. ChatGPT can complement the recruiting process in many ways, but hiring professionals need to figure out how to integrate it without relying on it. As AI rapidly becomes more powerful, recruiters will have to continually reassess which AI-powered tools they’re using and how to fully leverage those tools without taking unnecessary risks.

The Shift Toward AI in Recruiting

Recruiters were focused on the role of AI in their field long before the arrival of ChatGPT. AI has the potential to help recruiters source talent, reduce hiring mistakes, improve diversity, and accomplish many other goals. For example, at a time when the labor market remains hot and companies are finding it difficult to fill open roles, AI-powered talent rediscovery can give them a competitive edge by quickly searching through and surfacing previous applicants who meet a specific set of hiring criteria.

An Oracle survey found that significant majorities of HR professionals would like to use AI for many elements of talent acquisition: identifying candidates with the right competencies (66 percent), spending less time sifting through resumes (64 percent), filling open positions more quickly (58 percent), and improving the candidate experience (55 percent). The same survey found that HR professionals expected to use AI much more heavily in the coming years, though just 12 percent strongly agreed that they’re knowledgeable about using AI for talent acquisition.

As recruiters cast increasingly wide nets in search of talent and remote platforms make it easier to hire and onboard employees from anywhere in the world, AI will play a larger role in all aspects of talent acquisition. Still, there are good reasons why this role will likely continue to be supplemental rather than central to the most effective recruitment strategies.

The Liabilities of ChatGPT

Consider one of the most commonly-cited problems with ChatGPT as it currently exists: its answers are often incorrect. There are proliferating accounts of how ChatGPT misstates historical facts, makes programming mistakes, and even gets basic arithmetic wrong. This problem isn’t limited to ChatGPT – Alphabet shares recently plummeted when Google’s new Bard chatbot presented inaccurate information in a high-profile ad. Meanwhile, Microsoft’s new Bing chatbot (powered by OpenAI software) has proven to be bizarrely moody, frequently and stubbornly incorrect, and even emotionally manipulative.

Although ChatGPT is a powerful platform that offers a glimpse into the future of AI-enabled work, its tendency to make mistakes should be a big red flag for recruiters. For example, recruiters may attempt to answer candidate questions more efficiently with ChatGPT and end up providing erroneous information. This is particularly problematic when it comes to issues around diversity and inclusion, disabilities and accessibility, and compliance with relevant laws and regulations. There are many reports of bias in ChatGPT’s answers, which isn’t surprising as the model is built on real-world associations where biases are pervasive.

ChatGPT will continue to improve, and there are plenty of ways for recruiters to use the technology productively. But this should always be done with the full awareness of the platform’s shortcomings and the risks of over-reliance on AI in the hiring process.

Taking full advantage of ChatGPT and other AI platforms

ChatGPT is among the most powerful language models and information aggregators available, and its reach is growing all the time. As the platform continues to gather data from millions of users (and now that Microsoft is incorporating ChatGPT into Bing), we should expect to see the amount and quality of information increase along with the number of users. Meanwhile, other major companies, startups, and labs will pursue their own generative language models.

How can recruiters benefit from these developments? ChatGPT is capable of providing job descriptions, candidate pitches, and interview questions. It can create boolean strings to help recruiters widen or narrow their search parameters. It can immediately generate overviews of market research. However, beyond the fact that recruiters should be wary of many of ChatGPT’s “answers” for the reasons outlined above (bias, unreliability, etc.), they should also use the platform as more of a jumping-off point than as an end in itself.

Recruiters are still the ones who know what type of culture they’re trying to build, what unique advantages and constraints their companies face, and what they’re looking for in a candidate. These are all reasons they should remember that, while ChatGPT offers an answer for certain recruiting challenges, it isn’t the answer.

The post ChatGPT Won’t Revolutionize Recruiting Anytime Soon appeared first on RecruitingDaily.

Virtual people are a hybrid of animation, AI, sound tech, and machine learning, resulting in digitized “staff” who can interact with the public based on their unique programming. Virtual people projects and their role in businesses are on the rise. This fascinating addition and development in the Metaverse have piqued the interest of recruiters and employers.

The Latest Buzz on Virtual People

China’s pioneers in AI technology have made some impactful additions to the recruitment world. Here’s the latest on virtual people and their increasing presence in the workplace:

• Beijing plans to grow the municipal virtual people industry to more than 50 billion yuan by 2025.
• Over 280 000 enterprises in China use services related to digital humans and have a growth rate of nearly 60%.
• The revenue accrued by digital humans in entertainment is anticipated to reach 175 billion yuan in China by 2023, while the service-orientated virtual staff is expected to exceed 95 billion yuan, according to an industry report released by QbitAI, an industry services platform focusing on AI and cutting-edge technology.

Why is Digital Staffing an Attractive Choice?

For the most part, digital “staff” have a low-drama appeal for employees and advertising agencies. A virtual personality will not encounter negative criticism for their personal actions and scandals. This is beneficial for Chinese brands looking to use virtual people as spokespeople and hosts for their brand events and customer-interactive positions.

Anonymity is another appeal to using virtual staff. A U.S.-based study that used virtual humans to assess mental health patients found that people find it easier to disclose their information when there is anonymity, an attribute that is more easily found when talking to a digital personality.

The costs of virtual personalities are also expected to drop as technology improves. In the past year, Baidu’s virtual people and robotics business has seen costs drop by 80%. Expenses are around $14,300 per year for a three-dimensional virtual person and $3,000 (¥20,000) for a two-dimensional one.

Where are Virtual People Most Used?

China’s cyberspace is becoming densely populated with digital humans, and we will soon see similar merges in other developed countries. Popular spaces that have hired digital employees include:

• Financial services companies
• Local tourism boards
• Broadcasting spaces
• Healthcare
• Education
• Manufacturing and retail
• Marketing — social media influencers, mascots, corporate speakers, etc.
• Entertainment media

From animated to realistic-looking, AI personnel can be used for most interactive simulations. The use of virtual staff will only spread as technology advances.

The Pros of Virtual Hiring

For companies looking to hire virtual people, here are the perks of using a tech company’s virtual creation for you:

• Reduces burnout and burden on staff
• 24/7 response time
• Consistent communication that’s always on-script
• Product and brand experts
• Multi-lingual capabilities

Recruiting virtual staff requires an in-depth look at tech companies that offer digital human creation. The brain of a virtual person is then tailored for the job based on product database and knowledge. Virtual humans can also provide face-to-face interaction and communicate based on non-verbal facial cues and voice tones. You get to design your candidate as you please.

Digital humans can provide a helpful layer to the workforce and streamline many positions. Their success is measurable. But at this point, many customers still prefer human interaction over artificial virtual interactions.

The Future of Recruiting – Mind Versus Machine

The shift of working side-by-side with virtual humans may seem intimidating, but recruiters and companies hold the role of deciding when and where these digital humans can serve them. The quality and initial input for well-executed virtual staff members cost companies time, effort, and trial periods. This investment is worth the effort for some roles in a company.

Ultimately, we can imagine and expect a future where we see digital people paralleled with humans. Staffing a business requires keeping your finger on the pulse of tech advancements and finding creative ways to source candidates. Look at what your competitors are doing, assess your goals, and determine whether a virtual person may have a future in your company or the business you’re staffing.

The post Staffing your Workforce with Virtual, Digital People – A Closer Look appeared first on RecruitingDaily.

In other words, hiring managers face a series of structural challenges that will make recruitment and retention difficult for the foreseeable future. This is why HR teams are increasingly using innovative strategies to reduce hiring costs and identify more promising candidates. Talent rediscovery is among the most effective of these strategies, as it allows hiring managers to narrow their candidate search to potential employees who have applied previously, which means they’re choosing from talent pools that are more likely to be aligned with their needs. 

Companies are now using AI to dramatically improve cumbersome applicant tracking systems (ATS) – a process which filters candidates much more efficiently, improves time-to-hire, and helps companies find the right people for open positions. Let’s take a closer look at how AI-powered talent rediscovery is changing hiring, as well as several strategies for using this approach to build a stronger workforce as cost-effectively as possible. 

New Technologies Can Facilitate Talent Rediscovery

One of the most difficult aspects of talent rediscovery is gathering and processing the full range of data that exists on all former applicants. Even if that information is technically available, hiring managers aren’t capable of manually analyzing it quickly and thoroughly. Considering the fact that just 55% of HR leaders say they “effectively surface past applicants to fill open roles,” it’s clear that the methods of talent rediscovery could use an update. 

Hiring managers can use tools based on artificial intelligence (AI) technologies to rapidly review all relevant applicant information: resumes, cover letters, references, previous interactions with the company and so on. AI-powered talent rediscovery can also enable personalized engagement with candidates on the basis of their unique backgrounds and professional aspirations. Over three-quarters of senior candidates say the recruitment process affects their perception of a company, while 62% of these candidates report that they’ve abandoned this process because it was taking too long. 

AI-powered talent rediscovery attempts to address all these issues concurrently by making the hiring process more data-driven and predictive, creating a candidate-focused hiring experience and improving efficiency for companies and future employees. 

How Companies Can Fully Leverage Technology to Rediscover Talent

Companies can use AI-powered talent rediscovery software in conjunction with their existing ATS, which will provide the raw data necessary to assess candidates and communicate with them productively. These tools make it possible to evaluate whether candidates have the skills, experience and even personal characteristics for a specific role.

If a company used a pre-employment assessment when the candidate applied, this will provide even more data to analyze such as cognitive aptitude, emotional intelligence and other relevant traits. 

One of the main reasons many companies are failing to rediscover talent with their existing ATS is the fact that these systems are incapable of providing qualitative data about candidates. They warehouse basic information, but can’t use that information to generate actionable insights.

When HR teams use AI to rediscover talent, they won’t just search a much wider array of candidates than they could with manual ATS solutions, they’ll also determine which candidates are suited for which roles, overall cultural fit and the likelihood of successful outreach. 

AI-Powered Talent Rediscovery Offers a Critical Competitive Edge

A crucial aspect of any hiring process is its ability to predict which candidates will perform well on the job. Traditional hiring methods such as resumes and unstructured interviews have a poor record of predicting job performance when compared to objective measures such as general cognitive ability. These methods are also prone to bias, which leads some candidates to conceal certain aspects of their identities (such as race) when they apply.  

By reevaluating former candidates and applicants with more advanced, less bias-prone tools, it’s possible to surface overlooked talent. While AI is limited to existing data about candidates, it can make connections and predictions that other forms of analysis cannot.

AI-powered talent rediscovery can mitigate bias by impartially evaluating candidates on the basis of their suitability for each job, a process that will simultaneously make more predictive decisions by focusing on the abilities and traits that actually matter. Even if the candidate in question applied for a position that’s no longer available, the same approach will work in novel situations. 

At a time when the competition for talent is intense and candidate experience matters more than ever, AI-powered talent rediscovery can help companies reduce hiring and onboarding costs, take full advantage of their existing talent networks and hire exceptional employees. 

The post How AI-Powered Talent Rediscovery is Transforming Hiring appeared first on RecruitingDaily.

Nearly half of employees worldwide — including one-third of C-level leaders in the U.S. — would not recommend their company or their profession to their children or a young person they care about. Worse, said the Workforce Institute at UKG, a startling 38% of employees globally “wouldn’t wish my job on my worst enemy,” which rises to 45% in the U.S.  

While the impact of a potential recession and rising inflation dampens the hiring outlook, U.S. employers continue to report upbeat hiring plans, says ManpowerGroup. IT remains the strongest sector (+52%), despite headlines about tech hiring and layoffs. The weakest outlooks were predicted by employers in communication services (18%), goods & services (15%), transport, and logistics & automotive (5%).

Most enterprises are cautiously optimistic about conditions in 2023 and anticipate tapping outsourcing resources to control costs and meet the demand for talent, according to Everest Group’s annual Key Issues survey. More than 80% of respondents expect their investments in outsourcing for IT services and business process services to remain the same or increase in 2023 compared to 2022. Enterprises cited price and cost pressures as their number one concern this year, moving into the top position from second place during 2022. Talent/skills shortage dropped from first position to third, while adapting to evolving customer needs and business models occupied the second position.

Some 88% of companies worldwide are already using AI in some form to streamline their hiring, onboarding and upskilling processes. However, the talent platform Clapself said the level of automation in HR continues to lag other business functions such as sales and marketing. “Overall candidate experience, hiring costs and time it takes to fill a position continue to be major worries for hiring managers,” said CEO Anuj Kanish. 

Workday appointed Carl Eschenbach as co-CEO, where he will serve alongside Aneel Bhusri. He will remain on the Workday board of directors, of which he’s been a member since 2018.

Hourly work marketplace Snagajob said that Keith Forshew has been appointed chief executive officer.  

The post HCM Talent Technology Roundup January 6, 2023 appeared first on RecruitingDaily.

FORVIS, a professional services firm, launched TALENT SHIFT, LLC, a gig-work marketplace that matches accounting, tax and advisory professionals with project opportunities on a fixed-term basis. The offering aims to connect gig workers with projects that fit their skill sets and interests, as well as their desire for hybrid and flexible work schedules.

Nearly three-quarters of chief finance officers (74%) expect talent or labor costs to jump substantially in the coming year, according to research by Deloitte. This comes as 41% of them feel pessimistic about their companies’ financial prospects during 2022’s fourth quarter, up from 37% in the third. 

ShiftPixy introduced its “Fast Fill” recruiting technology. The product is designed to directly reach available workers through mobile technology, encouraging them to immediately sign up for available shifts. According to the company, to find the workforce, businesses need to move to mobile technology – meeting people where they live and socialize.

Clapself announced the launch of its AI-powered platform that connects professionals who want flexibility with the U.S.-based enterprises that are seeking talent through contract hiring.

The post HCM Talent Technology Roundup December 23, 2022 appeared first on RecruitingDaily.

Can You Define Talent Acquisition for Me

Sure! Talent acquisition is the process of finding and acquiring skilled workers for an organization. This can include activities such as recruiting, screening, and hiring employees. The goal of talent acquisition is to build a strong and capable workforce that can help the organization achieve its business objectives.

What Are 3 Applications for AI in Talent Acquisition?

There are many potential applications for AI in talent acquisition, but here are three examples:

1. 1. Recruitment: AI can be used to automate many of the tasks involved in recruiting, such as sourcing and screening candidates, scheduling interviews, and managing job postings. This can help organizations save time and resources, and enable them to find the best candidates more efficiently.
   2. Employee assessment: AI can be used to evaluate job candidates and provide insights about their suitability for a role. This can be done through the use of algorithms that analyze candidates’ resumes and other data, such as job performance reviews, to identify key skills and experiences.
   3. Retention: AI can be used to help organizations retain their top performers by providing personalized feedback and coaching. For example, AI can be used to monitor employee performance and provide recommendations for career development, helping to keep workers engaged and motivated.

Can You Give Me 3 Good Interview Questions to Ask a Python Developer During an Interview?

Sure, here are three good interview questions to ask a Python developer:

1. 1. Can you explain the difference between a tuple and a list in Python?
   2. How do you handle exceptions in Python? Can you provide an example?
   3. Can you explain the purpose of the “self” keyword in Python, and how it is used in method definitions?

These questions can help you evaluate a candidate’s knowledge of basic Python concepts, as well as their ability to think critically and problem-solve. It’s also a good idea to ask the candidate to write some code on a whiteboard or laptop to assess their practical skills.

Can You Give Me a Good Technical Interview Question for a Python Developer?

Here is a good technical interview question for a Python developer:

“Can you explain how Python’s garbage collector works, and how it affects the performance of a Python program? Can you provide an example of how you might use the garbage collector in your own code?”

This question tests the candidate’s knowledge of Python’s garbage collection system, which is an important aspect of the language’s performance and memory management. A good answer would explain how the garbage collector works, how it affects program performance, and provide an example of how to use it in code. This can help you evaluate the candidate’s technical expertise and problem-solving skills.

Can You Give Me a Good Technical Interview Question for a Python Developer?

Sure, here is another good technical interview question for a Python developer:

“How do you manage dependencies in a Python project, and why is this important? Can you provide an example of how you have implemented dependency management in a previous project?”

This question tests the candidate’s knowledge of dependency management in Python, which is an important aspect of developing and maintaining complex applications. A good answer would explain the importance of dependency management, describe a specific approach or tool that the candidate has used in the past, and provide an example of how it was implemented in a previous project. This can help you evaluate the candidate’s technical expertise and experience in Python development.

Can You Give Me 3 Examples of Things I Should Not Ask During an Interview?

It’s important to avoid asking certain types of questions during an interview, as they may be unlawful, discriminatory or simply inappropriate. Here are three examples of things that you should not ask during an interview:

1. 1. Questions about an applicant’s age, race, ethnicity, gender, sexual orientation or other protected characteristics. These types of questions are unlawful under federal and state anti-discrimination laws, and can create a hostile or uncomfortable environment for the applicant.
   2. Questions about an applicant’s religious beliefs or practices. These types of questions are also unlawful under federal and state anti-discrimination laws, and can create a hostile or uncomfortable environment for the applicant.
   3. Questions about an applicant’s medical or health history. These types of questions are generally not relevant to the job, and can be seen as intrusive or inappropriate. Additionally, asking about medical or health information may violate federal and state laws that protect an individual’s privacy.

In general, it’s best to focus on questions that are directly related to the job requirements and the candidate’s ability to perform the tasks required. This will help you evaluate the candidate’s qualifications and experience in a fair and legal manner.

In Your Opinion, What Impact Will AI Have On Talent Acquisition?

It’s difficult to predict exactly what impact AI will have on talent acquisition, as it will likely depend on how it is used and the specific context in which it is applied. However, some possible impacts of AI on talent acquisition include:

• • Improved efficiency and speed: AI can automate many of the tasks involved in talent acquisition, such as sourcing and screening candidates, scheduling interviews and managing job postings. This can help organizations save time and resources, and enable them to find the best candidates more efficiently.
  • Enhanced decision making: AI can be used to analyze large amounts of data related to job candidates, such as resumes, job performance reviews and skills assessments. This can provide organizations with valuable insights and help them make more informed hiring decisions.
  • Improved candidate experience: AI can be used to provide a more personalized and engaging candidate experience. For example, AI-powered chatbots can be used to answer common questions and provide real-time feedback to candidates throughout the recruitment process.

Overall, the impact of AI on talent acquisition is likely to be significant, as it has the potential to improve many aspects of the process and help organizations build a stronger and more capable workforce.

How Would an AI Be Used Fairly to Screen a Candidate During a Job Interview?

AI can be used fairly to screen candidates during a job interview by following a few key principles:

1. 1. Ensure that the AI system is designed to be unbiased and fair. This means avoiding the use of data or algorithms that could potentially discriminate against certain groups of people.
   2. Use a diverse and representative data set to train the AI system. This will help ensure that the system can accurately evaluate candidates from a variety of backgrounds and experiences.
   3. Regularly evaluate and test the AI system to ensure that it is working as intended and is not producing biased or unfair results.
   4. Provide transparency and accountability around the use of AI in the hiring process. This means clearly communicating to candidates how the AI system is being used, and providing them with an opportunity to challenge or appeal any decisions made by the system.

By following these principles, organizations can use AI to screen candidates in a fair and unbiased manner, and ensure that all job applicants are treated equitably throughout the hiring process.

Do You Think AI Could Make  Hiring Decisions in the Future Without Human Input?

It’s difficult to predict exactly how AI will be used in the future, but it is possible that it could be used to make hiring decisions without human input. However, there are several factors that could impact the extent to which this happens, including the availability of reliable and unbiased data, the development of advanced AI algorithms, and legal and ethical considerations.

It’s important to remember that AI is a tool, and it is ultimately up to humans to decide how it is used. Therefore, if AI is used to make hiring decisions in the future, it will be important to ensure that it is done in a responsible and transparent manner, and that it is subject to regular evaluation and oversight. This will help ensure that the use of AI in hiring is fair, unbiased, and aligned with the organization’s values and goals.

What Are Some of the Ethical and Legal Considerations of Using AI for a Job Interview?

There are several ethical and legal considerations that organizations should be aware of when using AI for a job interview. These include:

1. 1. Bias and fairness: AI systems can be trained on data that is biased or unrepresentative, which can result in unfair or discriminatory decisions. Organizations should be careful to avoid using biased data when training AI systems, and should regularly evaluate and test the systems to ensure that they are not producing biased results.
   2. Transparency and accountability: Organizations should be transparent about how AI is being used in the hiring process, and should provide candidates with an opportunity to challenge or appeal any decisions made by the AI system. This will help ensure that the use of AI is fair and accountable.
   3. Legal compliance: Organizations should ensure that their use of AI in the hiring process complies with all relevant laws and regulations, including anti-discrimination laws and privacy laws. This will help protect the rights of job applicants and prevent legal liabilities for the organization.

Overall, it’s important for organizations to carefully consider the ethical and legal implications of using AI in the hiring process, and to take steps to ensure that it is done in a responsible and transparent manner. This will help ensure that the use of AI is fair and beneficial to both the organization and job applicants.

The Current Time to Fill of a Job Is 42 Days on Average According to SHRM, How Much Time Could Using an AI Save in This Process?

It’s difficult to say exactly how much time using an AI could save in the job recruitment process, as it will depend on a variety of factors such as the complexity of the job, the size of the organization, and the quality of the AI system being used.

However, in general, AI has the potential to save time in many of the tasks involved in recruiting, such as sourcing and screening candidates, scheduling interviews, and managing job postings. By automating these tasks, AI can help organizations find the best candidates more efficiently and reduce the time it takes to fill a job.

For example, if an organization currently spends an average of 42 days to fill a job, using an AI could potentially reduce that time by automating some of the tasks involved in the process. However, the exact amount of time saved will depend on the specific circumstances of the organization and the AI system being used.

What Are Three Use Cases for AI in Talent Acquisition?

Here are three potential use cases for AI in talent acquisition:

1. 1. Automated resume screening: AI can be used to analyze resumes and other job application materials to identify candidates who are most likely to be a good fit for a particular role. This can help organizations save time and resources by quickly identifying and prioritizing the best candidates.
   2. Predictive hiring: AI can be used to analyze data about job candidates, such as their skills, experience, and performance reviews, to predict their likelihood of success in a particular role. This can help organizations make more informed hiring decisions and improve the overall quality of their workforce.
   3. Candidate engagement: AI can be used to provide personalized and engaging experiences for job candidates throughout the recruitment process. For example, AI-powered chatbots can be used to answer common questions and provide real-time feedback to candidates, helping to keep them engaged and motivated.

Overall, AI has the potential to improve many aspects of the talent acquisition process, from identifying and assessing candidates to engaging and retaining top performers.

How Could an AI Be Used to Source Passive Candidates for a Job?

An AI could be used to source passive candidates for a job by using algorithms to analyze data about potential candidates, such as their skills, experience, and professional networks. This can help identify individuals who may be a good fit for a particular role, even if they are not actively looking for a job.

For example, an AI system could be trained on data about job requirements, industry trends, and the skills and experiences of successful candidates. The system could then use this data to search for potential candidates who match the desired profile, and identify individuals who may be interested in the job but are not actively looking for new opportunities.

The AI system could then contact these potential candidates and provide them with information about the job and the organization, and encourage them to apply or learn more about the opportunity. This can help organizations find and engage with passive candidates who may not be easily identifiable through traditional recruitment methods.

Write a Short Example of Outreach to a Potential Candidate About a Software Engineering Job

Here is a short example of outreach to a potential candidate about a software engineering job:

Dear [Candidate],

We came across your profile and noticed that you have experience in software engineering and a strong background in [relevant technologies]. We are currently looking for a software engineer to join our team at [Company], and we think you may be a good fit for the role.

At [Company], we are working on exciting projects that use [relevant technologies] to [achieve business objectives]. Our team is made up of talented and passionate engineers who are dedicated to [achieving company mission].

We would love to learn more about your experience and see if there may be an opportunity for you at [Company]. If you are interested, please don’t hesitate to reach out to us.

Best regards, [Your name] [Your contact information]

What Are the 3 Technologies That Will Make the Most Change in Talent Acquisition?

It’s difficult to predict exactly which technologies will have the most impact on talent acquisition, as the field is constantly evolving and new technologies are being developed all the time. However, here are three technologies that could potentially make significant changes in the field:

1. 1. Artificial intelligence (AI): AI has the potential to automate many of the tasks involved in talent acquisition, such as sourcing and screening candidates, scheduling interviews, and managing job postings. This can help organizations save time and resources, and enable them to find the best candidates more efficiently.
   2. Virtual and augmented reality (VR/AR): VR and AR technologies can be used to provide immersive and engaging experiences for job candidates, such as virtual job interviews or simulations of the work environment. This can help organizations provide a more personalized and engaging candidate experience, and give candidates a better idea of what it would be like to work at the organization.
   3. Blockchain: Blockchain technology can be used to create decentralized and secure systems for storing and sharing data about job candidates, such as their resumes, skills, and experiences. This can help organizations maintain a comprehensive and up-to-date database of potential candidates, and make it easier to share and access candidate information across different departments and teams.

Overall, these technologies have the potential to significantly change the way that talent acquisition is done, and can help organizations build a stronger and more capable workforce.

Should AI Be Allowed to Conduct Job Interviews either Now or in the Future?

Whether AI should be allowed to conduct job interviews is a complex and contentious issue, and there are many different perspectives on the matter. Some argue that AI can provide a more objective and unbiased approach to interviewing, and can help organizations identify the best candidates more efficiently. Others argue that AI lacks the empathy and human interaction that is essential to the hiring process, and that it could lead to unfair or discriminatory decisions.

In general, it’s important to consider the potential advantages and disadvantages of using AI in job interviews, and to weigh these against the organization’s goals and values. If an organization decides to use AI for interviewing, it should be done in a responsible and transparent manner, and should be subject to regular evaluation and oversight to ensure that it is fair and unbiased.

Overall, whether or not AI should be allowed to conduct job interviews is a decision that should be made on a case-by-case basis, taking into account the specific context and circumstances of the organization and the job candidates.

What Should a Company Consider Before Implementing an AI in Their Recruitment Process?

Before implementing an AI in their recruitment process, a company should consider several key factors, including:

1. 1. The goals and objectives of the organization: It’s important to carefully consider why the organization is considering using AI in the recruitment process, and how it aligns with the organization’s overall goals and objectives. This will help ensure that the use of AI is aligned with the organization’s strategic direction and priorities.
   2. The potential impact on candidates and employees: The use of AI in the recruitment process can have significant impacts on job candidates and existing employees, both positive and negative. It’s important to carefully consider these impacts, and to take steps to mitigate any potential negative effects.
   3. The availability of reliable and unbiased data: AI systems rely on data to make decisions and predictions, so it’s important to ensure that the data being used is reliable and unbiased. This will help ensure that the AI system is able to make fair and accurate decisions.
   4. Legal and ethical considerations: The use of AI in the recruitment process is subject to a variety of legal and ethical considerations, such as anti-discrimination laws and privacy laws. It’s important for organizations to carefully consider these considerations and ensure that their use of AI complies with all relevant laws and regulations.

Overall, it’s important for organizations to carefully consider these and other factors before implementing AI in their recruitment process, in order to ensure that it is done in a responsible and effective manner.

Can You Write Me a Job Advertisement for an RN With a Focus in Oncology?

Sure, here is a sample job advertisement for an RN with a focus in oncology:

Job Title: Oncology RN

Location: [City], [State]

We are seeking an experienced and compassionate Oncology RN to join our team at [Hospital]. In this role, you will provide care and support to patients with cancer, and work closely with a team of oncologists and other healthcare professionals to deliver high-quality care.

Responsibilities:

• • • Provide direct nursing care to patients with cancer, including administering medications, monitoring vital signs, and coordinating with other members of the healthcare team
    • Educate patients and their families about their condition, treatment options, and self-care
    • Collaborate with oncologists and other healthcare professionals to develop and implement individualized care plans for patients
    • Monitor patients for changes in condition and respond to any potential complications or emergencies
    • Participate in ongoing training and professional development to maintain and improve clinical skills and knowledge

Qualifications:

• • • Current RN license in [State]
    • Bachelor’s degree in Nursing or related field
    • At least 2 years of experience as an RN, with a focus on oncology
    • Knowledge of oncology nursing principles and practices
    • Excellent communication and interpersonal skills

If you are a dedicated and caring RN with a passion for oncology, we encourage you to apply for this exciting opportunity. Please submit your resume and

Thank You, This Has Been a Very Informative Discussion

You’re welcome! I’m glad I could help you. If you have any other questions, don’t hesitate to ask. I’m here to help!

The post My Interview With GPT-3 About the Future of AI in Talent Acquisition appeared first on RecruitingDaily.

Oracle announced Oracle Recruiting Booster, a talent acquisition solution designed to help organizations build better relationships with candidates and more efficiently hire them. A part of Oracle Fusion Cloud HCM, the product extends the capabilities of the company’s existing recruiting suite, and includes tools to help employers run high-volume events for high-volume efforts.

Career-development platform the Muse purchased Fairygodboss, an online career community for women. Fairygodboss was founded in 2015 by Georgene Huang and Romy Newman as an authentic career space for all women to feel supported and empowered. The acquisition reinforces The Muse said the transaction illustrates its dedication to making career matches where people, culture and values align.

Workers are looking for new jobs, asking for extra shifts or taking on side hustles to make ends meet as everyday expenses eat up a bigger chunk of their paychecks. A study by Qualtrics found that 64% of workers say it’s harder to pay for their living expenses now than it was a year ago. In addition, the rate of employees quitting is still high as job seekers accelerate their search, trying to find a new role with better compensation while openings are still available.

Gloat unveiled Skills Landscape, a platform enhancement that allows organizations to quickly upskill at scale by giving every employee skill-based guidance on how to reach their career goals. The program captures and analyzes workforce decisions and translates them into actionable recommendations for each worker.

Nearly one in three employees (30%) is considering leaving their job due to their employer’s response to the U.S. Supreme Court decision to overturn Roe v. Wade, according to a report from Catalyst, a nonprofit that works to accelerate progress for women. Almost half of those surveyed (44%) said their organizations and leaders are not doing enough to ensure abortion access, and one-third (33%) want their CEO to advocate for abortion rights. Workers were nearly twice as likely (83% vs 45%) to say that their organization genuinely cares about addressing employee needs if their company took action in response to Roe v. Wade being overturned.

The post HCM Talent Technology Roundup October 28, 2022 appeared first on RecruitingDaily.

This unconscious bias can lead to hiring decisions based not on merit or qualifications but on factors such as race, gender or ethnicity. The result? A less diverse workforce and failure to reflect the company’s customer base.

Intelligent automation (IA) can help create a more equitable hiring process by reducing the reliance on human decision-making. By using algorithms to screen candidates, rate their qualifications, and select the most qualified candidates for interviews, IA allows companies to avoid the pitfalls of unconscious bias and create a more diverse and representative workforce.

What Are Intelligent Automation and Unconscious Bias?

IA combines advanced technologies such as artificial intelligence, prescriptive analytics, robotic process automation, intelligent document processing and process and task mining to create digital workers, or bots, to support decision-making. Examples include data-driven processes using unstructured data, such as analyzing and classifying candidates’ resumes and CVs and making decisions or recommendations about who to interview.

Unconscious bias is how personal beliefs and prejudices influence hiring managers’ decision-making. These biases are often based on gender, race, ethnicity or age and can lead to an unfair hiring process. These unconscious biases make it harder for talented candidates to get a fair shot in the hiring process.

How Can IA Reduce Unconscious Bias In the Hiring Process?

There are several ways in which IA can reduce unconscious bias when hiring people:

1. 1. Find a broader pool of candidates: Intelligent Automation can automate candidate sourcing by scraping databases to find ideal candidates for vacant positions. It can also handle the flood of applicants for any given job. The Harvard Business Review says every online job posting receives an average of 250 applicants. Recruiters can’t manually handle this many resumes themselves, so they tend to whittle it down to the 10-20%they can handle, usually focusing on Ivy League degrees, employees of competitors and employee referrals. Through IA, digital workers can help avoid the issue of recruiters being unable to read every application.
   2. Create a more standardized process: Inconsistency in hiring can amplify unconscious bias. IA can help create a more standardized process by ensuring all candidates are treated the same and each step in the process is followed correctly since digital workers are always perfectly compliant with company policy. Examples include automated job postings, tracking applications through the hiring pipeline and running automatic background checks.
   3. Use data to drive decisions: IA can provide access to otherwise unavailable data. For instance, data sets too large for human workers to review. This data can be used to analyze previous hires, discern patterns and suggest corrections to the process. It can also help drive hiring decisions and ensure candidates are selected based on their qualifications, not a personal bias.

Benefits of Reducing Unconscious Bias

Reducing the unconscious bias in the hiring process can benefit an organization in many ways, including:

1. 1. Create a more diverse workforce: A more diverse workplace is not just good sense; it’s good business. Greater diversity enhances creativity, drives innovation and helps companies grow. For example, the Boston Consulting Group reported more diverse management teams led to 19%higher revenues than companies with less diverse leadership.
   2. Reduce turnover: Employees who feel they were hired relatively and without bias are more likely to be satisfied with their job and less likely to leave the company. By reducing unconscious bias in the hiring process, companies can reduce employee turnover and save on costs associated with recruiting and training new employees.
   3. Improve the bottom line: Workplace disputes often rooted in unconscious bias cost the U.S. economy approximately $359 billion annually. In addition, outright discrimination adds another $64 billion to the tab every year. Taken together, allowing unconscious bias into your hiring process proves costly.

More needs to be done to promote equity in your average hiring process. However, IA can be a powerful tool in reducing unconscious bias by allowing hiring managers to focus on the essential criteria for the role rather than allowing personal biases to influence their decision-making.

The post Eliminating Unconscious Bias in Your Hiring Process appeared first on RecruitingDaily.

What is Recruiting Automation?

Recruitment automation is any technology that eliminates manual and repetitive tasks that make the recruitment process slow and inefficient. Talent acquisition teams can then shift their focus to building meaningful interactions with top talent. 

A simple use case might mean, managing how candidate data is shared across a hiring team via an applicant tracking system.

While a more advanced example could mean, leveraging machine learning and artificial intelligence to get deeper into the talent pool faster — identifying qualified candidates more quickly than a recruiting team crawling LinkedIn could.

Why are more Recruiters Implementing Recruiting Automation Software?

There’s a well-known speech by roboticist Daniela Rus where Rus demonstrated how humans can outperform AI on skilled tasks. Rus’s argument wasn’t that we should kick machine learning-driven automation to the curb; rather, that we can achieve the best results by using AI-powered automation tools to augment skilled human performance.

On the one hand, recruiters and hiring managers have the very human, very complicated task of developing meaningful candidate relationships and creating a great candidate experience.

On the other, recruiting presents tons of simple but high-volume and time-consuming tasks, ex: candidate sourcing, resume screening and the back-and-forth of updates.

Recruiters and hiring managers who utilize recruiting automation software can reduce time to hire and permit talent acquisition departments to focus on the best candidates.

5 Recruiting Automation Software Solutions

Let’s look at the automated solutions that will help recruiters save lots of time while boosting their productivity. We’ve broken down the hiring process into five steps, and it all starts with your job description.

Ongig

A Harvard University study found that job ads for male-dominated careers like engineering tended to code masculine. As a result, women were left with negative impressions of gender diversity, job appeal and anticipated belongingness.

The good news is that solutions like Ongig can help you rapidly identify words in your postings that are turning off job seekers from underrepresented groups — and let you know what you need to fix to appeal to diverse candidates.

Ongig also helps you turn “boring and biased job descriptions” into effective and consistent ones with custom job description templates and a “missing sections” scanner that shows you if you’ve left out key sections candidates care about (e.g., salary, benefits, diversity or mission statements).  

Key Features: 

• • Gender, race, disability, age, neurodiversity, LGBTQ+ and other bias elimination
  • Neutral and inclusive languaging suggestions
  • Job description readability score
  • Job posting template builder
  • ATS integration for job posting workflow

Celential

Many recruiters spend around half their time sourcing qualified candidates, so automating that process could have the single greatest impact on ROI.

Celential is an AI-powered, human-in-the-loop recruiting solution that handles the search, matching, and outreach for software engineering, data science/ML and product talent. Once companies sign up, they only need to submit their open job roles and they will start receiving a list of candidates ready to interview.

How is this possible? Celential possesses a tech talent graph of over 10,000,000 tech candidate profiles from the US, Canada and Latin America. They then utilize their matching engine powered by thousands of data sources and Machine Learning models custom-built for tech recruiting to find the most accurate matches to your role, team and product domain.   

Once their AI discovers a mutual fit, it then creates a unique personalized pitch message and contacts candidates on your behalf. All that’s left to do is check your email or ATS and select the candidates you want to move to interviews.

Key Features: 

• • Quality candidates delivered to your inbox within 3 days
  • 70-80+% of candidates presented for interviews are accepted by hiring teams
  • Dedicated human customer support
  • ATS and workflow integration
  • Flexible plans to scale sourcing up and down depending on hiring needs
  • Diversity-focused sourcing

HackerEarth

With unfilled technical jobs projected to surpass 80 million by 2030, software engineers can afford to be picky. That’s why slow and complicated interview processes are a death blow to hiring for tech organizations in 2022.

It can help to offload the screening itself to a platform like HackerEarth. HackerEarth Assessments is a tech hiring platform that helps recruiters and engineering managers to create accurate, skill-based coding tests.

It offers a rich library of 16,000+ questions across 80+ skills that enables you to create highly accurate coding assessments with very minimal technical knowledge. This platform lets you create your own assessment for any role or skill in under 5 minutes, and you can even add your custom questions.

Since HackerEarth can sync all your candidate data with your ATS, you can directly invite candidates to take the assessment you created on this platform, see at what stage each candidate is in throughout the hiring process, avail performance reports and deliver real-time feedback to candidates – without switching between multiple applications.

Key Features: 

• • Customized coding tests and assessments
  • Leverage cutting-edge plagiarism and proctoring controls to ensure fair assessments
  • Automated scheduling for interviews and assessments
  • Generate a leaderboard after each test and shortlist candidates with a single click
  • Get in-depth candidate performance reports with a code playback feature

Workable  

If there’s one thing we keep hearing over and over again, it’s that Talent Acquisition teams need to become more data-driven to survive 2022’s economic uncertainty.

Workable’s intuitive ATS can help with reporting and analytics. Geared towards startups and SMBs, Workable allows you to manage — and track — all stages of the recruiting process, from job posting to interview to hire. 

That clear data is a huge asset when it comes to improving your hiring process. An ATS can help you identify recruiting bottlenecks at a high level and eliminate them for a better candidate experience.

As a standard on every plan, Workable offers features such as an advanced careers page builder, interview self-scheduling, a referrals portal and Developer API. You only get two languages on the more basic plan (English + one more) and then the Premier plan gets 6 different languages.

Key Features: 

• • Easy-to-use centralized hiring workspace
  • Candidate finding features and browser extension
  • Reporting and analytics
  • Integrations with 70+ apps including email, calendar and background check 
  • Diversity features (anonymized screening, demographic data reporting…)

RingCentral

The average executive loses an hour per day searching for lost and misplaced information. RingCentral’s unified platform can help prevent wasted time by aggregating all of your communications and contacts with colleagues, customers, vendors and everyone in between. 

Once you’ve short-listed your ideal candidates, you’ll need a reliable web-based video conferencing tool for setting up online interviews. It’s ideal to use software that allows you to sync your calendar.  For example, with RingCentral, you can connect your Microsoft or Google Calendar to schedule, view and join meetings on the RingCentral app.

Key Features: 

• • Сloud phone system
  • AI-powered contact center
  • HD video meetings
  • Unlimited team messaging
  • Integrations and APIs
  • Privacy and security features

The Benefits of Recruiting Automation

These various sourcing and recruiting technologies help you save time and money in three major ways. They allow you to: 

See more candidates with fewer resources. The ongoing turbulence in tech these last few months has seen some companies forced to lay off parts or all of their recruiting team to cut costs. 

But unless a company is pausing hiring altogether, they still need to be ready to sift through hundreds of applicants per job posting. Leaning into recruitment automation tools can allow smaller talent acquisition teams to quickly screen out resumes from all but the best candidates.

Boost your diversity hiring. Relying on professional networks and job boards for potential candidates can replicate existing demographic imbalances in your hiring process. 

AI sourcing tools can target candidates from nontraditional backgrounds and underrepresented groups, identifying potential candidates that might otherwise go unnoticed by human recruiters. By standardizing processes and tracking demographic data, AI solutions can also help you remove bias from your hiring process.

Multiply the efforts of your human recruiters. You want to evolve your recruitment process to the point where humans are only doing the things that only humans can do: nurturing a good candidate relationship, separating the minimally qualified candidates from the top talent and speaking face-to-face during the interview and hiring process.

Anything else — any manual tasks that don’t put you in front of candidates — should be considered a potential use case for recruiting automation software. Simple.

Wrapping Up: Why AI Recruiting Automation is the Future of the Recruiting Industry

You might have noticed a trend amongst the recruiting automation software we’ve discussed so far: they all involve handling large volumes of data in some form or another.

With 90% of the world’s data created in just the last two years, it’s clear the technological revolution is coming to all corners of the world — including talent acquisition.

Deftly handling large volumes of data is practically the definition of artificial intelligence, and talent teams and the future of talent acquisition belong to recruiters and hiring managers who skillfully augment their recruitment process with AI.

The post Recruiting Automation Software to Save Your TA Team Time and Money appeared first on RecruitingDaily.

Flexibility is now one of the top three concerns candidates prioritize when they’re considering a new role, along with compensation and job fit, according to a report from Qualtrics. The findings illustrate how employee expectations have changed dramatically over the course of the pandemic, as millions of workers experienced working from home – and how difficult those expectations would be to change.

Even with a record number of job openings in the U.S., many candidates say they are struggling with their job search, according to staffing firm PeopleReady. Over half of the  job seekers it surveyed – about 54% – said it has been “difficult” or “extremely difficult” to find a job that fits their preferences. The top reasons that people were looking for a new job in the first place include flexibility, higher pay and job satisfaction.

PivotCX released the beta version of its Real-Time Video communications package, which will be an addition to its talent acquisition communications hub. The company said the addition of video will provide a high level of interoperability across  existing channels already in place.  

HireVue announced a new pre-hire assessment to measure a candidate’s agile mindset. In a job market filled with constant change, the company said, this assessment helps employers identify candidates with a propensity for faster thinking, efficiency and flexible ways of working.

Oyster announced the launch of its Guided Hiring Process. The Guided Hiring Process is meant to reduce the complexity of global hiring, while helping organizations gain access to a larger pool of global talent.

Phone screening platform Qualifi announced a strategic partnership with Fountain, developers of an ATS for high-volume hiring. The two platforms are now directly integrated to streamline, scale and expedite the recruiting process for both applicants and recruiters.

Eightfold AI rolled out Eightfold Talent Flex, an AI-based solution that helps both HR and Procurement specialiasts source and manage high quality contingent workforces more efficiently.

WorkGenius acquired JBC, a New York-based staffing company. The company said it will leverage its proprietary algorithm, to better match its talent pool using factors that can reduce unconscious bias, including gender/sex.

Consult PR, a digital marketing firm, completed a successful beta program and is now offering recruitment process outsourcing for its clients.

The post HCM Talent Technology Roundup October 14, 2022 appeared first on RecruitingDaily.

With the wealth of talent data, both internally and externally, organizations are incorporating it to make data-driven people decisions. Talent intelligence enables organizations to collect and process data of current and past employees, prospective candidates and competitors. Organizations then can build a realistic picture of the job market, identify trends, create an optimal employee experience and hire the best talent.

Talent intelligence is particularly helpful in talent acquisition and talent management, helping organizations reduce candidate acquisition cost and time-to-hire, promote internal mobility and retain employees.

This article will look at how organizations can get the most out of talent intelligence.

Getting Started With Talent Intelligence

Talent intelligence is gathered from multiple websites, tools and systems. Organizations can collect the right talent intelligence data points with the right system in place. Here is a list of tools to get started:

• • Talent acquisition (TA) software: Talent acquisition and talent intelligence software solutions like SeekOut empowers companies and people to grow and win together. TA software gives the complete picture of all talent, both internal and external – the people you have and the people you want. With dynamic and comprehensive data, powerful people search, and easy-to-use analytics. Organizations can also integrate the platform with their ATS or CRM to gain granular insights into the talents’ skills, experience, salary, etc.
    Along with talent optimization features, robust talent analytics tools help organizations understand the talent market.

• • Compensation websites: Compensation comparison websites and third-party reports provide organizations with information on how talent is compensated based on their skills, experience, education and location.

• • Surveys: When searching for specific information, it helps to conduct a well-designed survey. For instance, if an organization hasn’t been able to bring down the time to hire, it can survey its hiring managers to understand the causes.

How to Leverage Talent Intelligence for Optimal Results

Here is how organizations can leverage talent intelligence to meet their objectives:

Talent Mapping

Talent mapping orients the talent acquisition strategy based on the organization’s long-term objectives. This includes defining new roles, updating existing jobs and planning career paths for internal mobility.

Organizations can utilize talent intelligence for talent mapping in the following ways:

1. 1. Identify successful employees’ skills, experience, education and behavioral traits and build ideal candidate profiles (ICP).
   2. Analyze hiring activities and candidate pool of competitors.
   3. Build a talent pipeline of passive candidates that match the ICP. Organizations can also tap into their ATS to identify silver medalist candidates.

Meet DEI Objectives

The first step in using talent intelligence to meet DEI goals is to understand the current state  of the organization. Organizations can analyze the workforce based on various dimensions of diversity such as age, gender, ethnicity, race, etc., and identify patterns in salary, seniority, hires, promotions, attrition and department against these dimensions. This is how organizations gain insights into potential issues, such as a gender pay gap or high attrition rates for underrepresented groups.

Organizations can set goals based on these findings.

The next step is to use talent intelligence during hiring. Many recruitment platforms prevent unconscious hiring bias by masking candidates’ identifiable information so that recruiters are screening candidates purely on merit. A complementing feature is diversity filters that allow recruiters to source and screen candidates from underrepresented communities.

Reduce Employee Turnover

Pew Research Center tried to uncover the reasons behind the Great Resignation. The top three reasons people left a company were low pay, no advancement opportunities and feelings of disrespect at work.

Employee turnover causes the organization to lose out on its top talent plus replacing the talent is expensive and time consuming.

Organizations can use talent intelligence to identify the reasons behind the attrition. For instance, if the organization observes massive turnover in one department, it can get to the root cause of it using talent intelligence. The reasons could be from the one we discussed earlier, or it could be due to not fitting in with the organizational culture. HR managers need to collect this data during exit interviews.

If better pay was the reason for quitting, the organization could look into salary reports, comparison websites and TA software to establish the salary benchmark.

Predict Upcoming Labor Market Trends

Trends like remote work, flexible schedules and the gig economy existed before 2020. But their adoption was forced on organizations due to the COVID-19 pandemic. While the circumstances in which these trends were introduced were completely unexpected, organizations already experimenting with them got a head start.

With so much information collected during the hiring process, internal surveys and industry reports, organizations can analyze this data, forecast trends and build more resilient practices to prepare themselves for change.

Promote Internal Mobility

With ICPs in place, organizations know the skills and mindset required to succeed in a role. Talent intelligence presents organizations with their employees’ skills, strengths and weaknesses. By mapping the skills and strengths to the right job, organizations can offer better opportunities to their employees to move up or laterally in the organization.

Organizations may want to create a customized learning path and a mentorship program for each career path to implement this program better. This will equip the employee with the necessary knowledge to grow in the new role.

Analyze Competition

Talent platforms enable organizations to tap into competitive intelligence through their people analytics function. Organizations can gather company insights such as job roles, diversity, seniority, etc., for a particular region at a company. Organizations can also compare themselves against competitors to learn where they stand regarding diversity, location of talent, experience, skills, salary bands, etc.

This data can act as an input for various initiatives and HR activities such as setting hiring goals, salary benchmarking, and diversity.

Setting Up for Success

Talent intelligence presents a holistic picture of the labor market, including the present scenario and future possibilities. These crucial insights help organizations optimize their hiring and internal mobility efforts to meet their business objectives.

To utilize talent intelligence to its full capacity, organizations must hire folks who swear by data, integrate tools in the HR tech stack properly and keep updating the system with changing times.

The post Succeeding with Talent Intelligence in 2022 and Beyond appeared first on RecruitingDaily.

eTeki and Candidate.ly have partnered to help staffing teams evaluate and submit tech candidates more quickly. Together, the companies will allow talent managers to get a complete picture of each candidate, with all data used for decision-making on one screen.  

Workplace flexibility continues to be the top priority for employees, according to research by McLean & Company. The firm’s research highlights how improperly structured and implemented flexible work programs can exacerbate existing challenges in an organization or create new ones. McLean recommends organizations uncover the unique needs of specific employee segments to offer the kinds of flexibility their workforce wants.

SilkRoad Technology unveiled the addition of person-to-person texting and SMS notifications to its RedCarpet Onboarding solution and On-demand Talent Campaigns. The addition will enable organizations to easily communicate with candidates and new hires, speeding up the process to source, attract, convert, engage and retain talent amid recent workforce changes.

Diversity recruiting and retention platform PowerToFly secured over $30 million in funding, which will allow the company to build a membership portal to help HR and people operations leaders learn best DEI practices.

CV-Library acquired Brilliant Jobs, a platform that uses AI and programmatic technology to connect candidates with employers. The acquisition was part of a strategic move to own and integrate a  programmatic product within CV-Library’s existing technology stack and to expand the company’s product line.

High-volume recruiting technology company Grayscale Labs landed a $7.5 million investment from Atlanta Ventures, according to Atlanta Inno.

The post HCM Talent Technology Roundup September 30, 2022 appeared first on RecruitingDaily.

And, if what I saw at HR Tech is any indication, that’s where the industry has landed when it comes to its most precious commodity: they’re the worst. From a tight labor market, constant turnover, candidate ghosting, hybrid work, gig work, etc., the industry is enduring a shared trauma, and some of the approaches (and, thus, tools) we’re deploying reflect that.

We’re loosening standards left and right to get butts in seats – over cocktails is when you get this sort of information from VPs of Talent (and you’re never allowed to attribute) – which means riskier hires and impacts on work culture leading to higher turnover.

We’re worried about req overload, burnout, skills and confused as ever by tech. And, for fun, we’re still stuck in the position where no one seems able to agree on what buzzwords like AI and employee experience really mean.

Also: talent intelligence.

That’s the new hot kid on the block, people. The one with the cool parents who leave them home alone every weekend with the liquor cabinet unlocked. Everybody wants to get to know talent intelligence. No one knows what it means. Aside from that it has something to do with people… and they’re the worst.

Can We Trust ‘em? Really?

Consider that there were 16 background check vendors at HR Tech (which feels like a record, at least from my recollection), and it’s positively buzzy.

This is a category which used to be one of the most consistently unsexy of HR functions (which is saying something). A necessary evil. One best avoided unless you were worried about things like compliance and lawsuits.

If you were at Fidelity, they were critical. If you ran a Beau-Bo Cafe? Maybe you let that part of the process drop. Which means you’d see the same relatively same short list of vendors at the expo every year, generally pitching slightly different shades of the same color. That seems to be shifting. And I think it’s because of employer PTSD. Fear of consequence. Burned fingers that flinch when they go to use the stove.

In the good-old-days, if your employee dragged his drunken ass behind the wheel of your garbage truck one sunny morning in Brooklyn, and then proceeded to drag said truck along the sides of, oh let’s say 20+ cars in a quiet street (where more than one tree grew), that would make for a headache for HR.

The whole thing, along with the ensuing foot chase by an angry mob of Brooklynites, several cops and finally Tasering, lands on YouTube. As long as the driver had a clean record when you hired them, and there hadn’t been any reports of on-the-job drinking, it was just a social media headache. That’s changing. And it’s reflected in a newly excited background check vendor scene.

The category is going through a tectonic shift from pre-screening to constant monitoring. The economic model providers like First Advantage, HireRight and Sterling are moving increasingly toward is pure SaaS, which is interesting. In the old days, we would run a background check on our driver candidate before an offer letter was created.

Once they passed, they’d be hired. Simple. Now, there’s the option of constant monitoring, post-hire. That driver, the one sitting in a jail cell at the moment? He received a DUI three weeks ago, a week after you hired them. If you’d known about it, a theory that will likely get tested in court, then you could have suspended him pending the outcome. And saved a street full of cars in Brooklyn. And possibly a  life. The legal questions to be tested:

• • If an employer has the option of this level of monitoring, are they liable if they fail to monitor (ie. they can’t afford to play stupid)?
  • Flipping that a bit: what about the employee’s right to privacy? That’s likely the one the entire category is holding its breath on.

No One Has Met a Robot Yet

We are still obsessing over AI. Stop it. Get some help. Every few booths read, “AI powered/ embedded/ enthralled/ branded/ overlord.” With one exception: they didn’t really mean it. They really meant things like NLP, machine learning, chat bots and other pieces of the large whole.

It’s like walking into a shop that says “Bike Store” thinking they’re going to have… well, bikes. Only to discover they focus on selling wheels, and that they just acquired a tire vendor which they “haven’t integrated fully yet but you have to buy the tire even though it doesn’t exactly fit the rim.” But they’re working on a build that should fix that in 2024. Meanwhile, they think they integrate with the following list of frame vendors, none of which you use.

Reejig is the only vendor with ethical and independently audited AI. So, I believe them when they say AI. They seem to actually carry the whole Schwinn.

The Talent is Intelligent, at Least – Maybe

Ahh, buzzwords. Like the firework colors of a New England fall, they explode every autumn at HR Tech. This year’s buzziest? Talent intelligence.

Oooh… sexy. It’s got two cool words that together, implying we as an industry are getting into the intelligence game. That’s right: we’re all Jack Bauer now. Which means we have to master the art of going 24 hours without using a restroom. Not once. It also implies that we’re using data to do all sorts of cool predictive stuff when it comes to demographics, economics, labor markets. TA now has crack teams who can find signals in the noise and deliver talent on demand in time for a rapidly shifting economy and labor market.

It means we can start calling ourselves “Talent Intelligence Analysts,” maybe even “Special Talent Intelligence Agent,” right?

Nope.

The emerging category seems more like workforce planning that’s been churched up, versus truly sexy. (And, church ain’t sexy – well, not usually). Lots of people are fighting over who the hell actually owns talent intelligence. And yet, what you see when you dig down is that – much like big data and AI, talent intelligence is primarily reactive and or sexy dashboards.

To my knowledge, no one is doing passive at the signal level signally, which is where actual intelligence should come from. CIA analysts spend hours, days and weeks looking for the tiniest signals in the noise as they build their maps.

Until there are enough people at the corporate level that have this mind/skillset and know-how, and who know what tools to use to get their work done, we’re going to be relying on the vendor to define what we should be looking for. That’s a huge mistake. And one we should have learned from by now. You’re supposed to adapt the technology to your needs and process, versus the opposite.

Speaking of Confusion – Candidate Experience, Oh, My!

Caring for the candidate is nice, but by now we should know what it actually means, and what the data-driven business case is for why we should be given money to address. We’ve been talking about Candidate Experience for almost 15 years, and I’m still not sure that people give a shit.

Experience (candidate, employee, alumni) comes down to two basic human things: (a) give a shit about the people you interact with and (b) be transparent and communicative with the folks that you care about. I personally think it’s is a trojan horse for retention. This isn’t necessarily a bad idea but let’s call it what it is. Also, like with talent intelligence, who the fuck owns EX? Everyone and no one. Great, just great.

Payroll Gets Sorta-Giggity

Every single payroll provider is flummoxed by pay-on-demand models for hourly and salaried employees. What started as a nuanced thing for gig economy workers is now expected of firms with salaried employees. For instance, if you’re an Uber driver, you can easily tab out at the end of a ride, day, or whenever you want.

If you’re an accountant for Deloitte, you now have the same expectation. My day is over; I want my money. Payroll companies and companies themselves have grown accustomed to what we call “float” – the time between when work is done and payroll dates. Yeah, those days are over. Employee behavior and expectations have forever changed. It will be interesting to see how new players change the category.

We Know Where We’re Going, But We Don’t Remember Where We’ve Been

Bottom-line: it was a much busier conference than this writer has seen in years. People want to get out and see each other. Granted, it turned out to be a super-spreader, but that’s sort of our new reality of trade-offs. The industry is more jaded, and – interestingly – more confessional. And I don’t mean confessing work-sins (although that happened too). There was sharing. So much sharing. Oversharing, even. People just wanted to talk. Get things off their shoulders, share war stories.

We’re still trying to figure out the current thing. And, whatever the things were before. We see ourselves evolving (maybe in Jack Bauer), but we’re still making many of the same questionable moves we’ve been making as an industry for decades. Hey: maybe we’re the worst. We’re only people, after all.

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