Talent acquisition software company Radancy acquired Ascendify, a cloud-based talent engagement software platform. According to the company, the acquisition enhances Radancy’s suite of solutions focused on helping enterprises find the talent they need to strengthen their business.

Comeet, a recruiting software provider, launches a new AI assistant that aims to enable better hiring decisions, improve candidate experience and promote diversity and inclusion. According to the company, the solution leverages OpenAI’s GPT to create job descriptions, pre-screening questions and email templates. In addition, the company said the assistant will soon be able to make interview questions and scorecards.

Oyster announced Oyster Total Rewards, a new suite of solutions meant to help companies design a compensation strategy and offer salary, equity, and benefits for teams. The company said the solutions are competitive, compliant, aligned with budget and—most importantly—aligned with employee expectations.

HireRight acquired a background screening provider based in Argentina. The company said this will Inquiro Vitae allow for more targeted local support for its customers hiring across Latin America.

Launched as the U.S stands on the precipice of recession, the Conference Board Job Loss Risk Index measures the likelihood of layoffs in individual industries, based on factors such as demographics, labor shortages and sensitivity to monetary policy. The Index measures the likelihood of layoffs in individual industries based on several key factors including demographics, labor shortages, and sensitivity to monetary policy.

Likewise, a pullback in e-commerce and discretionary spending on goods is likely to cause job losses in transportation and warehousing, while construction is at risk due to weakness in the housing market amid rising interest rates.

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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.

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With evolving market dynamics, logistics companies need to stay ahead of the curve when it comes to hiring and retaining great-fit talent. In this article, we discuss how HR leaders in logistics can optimize recruitment for better hiring outcomes.

Overcoming the Talent Challenges in Logistics Industry

Here are some trends to keep in mind for companies looking to hire new talent:

1. Technology and Automation or Employee Skill Development: What’s the Answer?

Consumer demand is increasing and, according to a survey by Accenture, it is one of the most significant causes for transformation. As a result, companies are turning to technology and automation tools to meet evolving customer expectations. Moreover, data analytics and artificial intelligence (AI) are revolutionizing logistics by minimizing errors, using predictive maintenance, assisting inventory management with real-time feedback, and forecasting demand and potential bottlenecks. However, increasing investment in AI-powered and automated solutions begs an obvious question – how does it impact human jobs?

While training and implementing digital models seem easier, human labor remains integral to supply chains. This means that for companies to attract and retain talented employees, it is vital to pay attention to how the physical and digital worlds collaborate to create a more valuable workforce. It is time to invest in tech and humans, equally.

With such advancements in technology and automation, you need employees who are comfortable using digital tools and software like transportation management systems and data analytics. This is where upskilling and skill development come in. Although there is a need for digitally-skilled employees, only 45% of companies invest in effective skill development programs, and it’s a deal breaker for new talent! Forty-four percent of employees would stay in their current company, but only on the condition of reskilling and development. To set yourself apart from the competition, focus on creating upskilling programs, career growth opportunities, and apprenticeships and internships to sustain critical employees and experts. Such options will also help you gain new talent.

2. Leveraging Flexibility and Remote Work Options

Given the changing business landscape, flexible and remote work options have become ordinary – and most employees prefer it! More control over one’s schedule makes for a supportive work environment which encourages better work-life balance. This can mean a few different things based on your needs.

First, businesses have adopted contingent and temporary workers in response to changing market conditions. It presents a win-win situation for both – companies can scale up efficiently when required, while employees enjoy the benefits of higher flexibility. Next, introducing (or continuing) remote work options for certain employees will help retain them longer. Many functions like quality control measures and technical support can be performed remotely. Encouraging and creating a collaborative environment for remote workers will enhance efficiency, morale, and productivity. It also allows you to curate a positive company culture that values teamwork, collaboration, and open communication and fosters a positive and supportive work environment – which is crucial to attracting and retaining new talent.

Lastly, when talking about attracting new talent, a robust application and hiring process is a must. But don’t make it long, confusing, and tedious – candidates will drop out. Leverage recruitment solutions to streamline the application and make it more flexible for the candidates. For instance, invest in digital platforms that centralize the application, provide 24/7 support to candidates, and allow you to communicate on the go. This will also enhance the overall candidate experience and impact your conversion rates and return on investment. Including these best practices in your hiring will allow you to attract and retain top talent.

3. Expand Your Talent Pool with Data-driven Sourcing

Another great way to optimize your tech stack is to back the hiring process with a data-driven approach. In a tight and competitive labor market, hiring managers, talent acquisition (TA), and HR leaders are hard-pressed to find quality candidates. Often, sourcing challenges also arise from using outdated channels instead of updating and expanding your options.

Data analytics and workforce management solutions do an excellent job of providing you with the right type of data to enhance your candidate search. Apart from that, data also provides insight into your hiring needs by identifying open priority roles, hiring costs, and future needs of the business to consider while making hiring decisions.

Equipped with this data, you can opt for sourcing solutions like programmatic advertising to optimize ad spending and target the great-fit candidates. Programmatic solutions automatically select and allocate funds among the best job boards and display your ads to desired candidates. Read more about how programmatic solutions can help with candidate sourcing: Thrive Amid Volatility with Data-Driven Talent Sourcing

In addition, you can also use social media platforms to reach and recruit new candidates. Millennial and Gen-Z workers frequent companies’ social media accounts; using them correctly, you can reach and attract them. A variety of content, like images, audio, and video, enables you to connect and engage with a broader audience. If you still need more reasons to include social media in your recruitment strategy, read 8 Reasons Why Social Media Is the Best Platform for Recruiting

Conclusion

Logistics, supply chain, and transportation industries have struggled with labor shortages in the last few years. The pandemic, global economic challenges, and disruptions have only exacerbated these issues and are likely to continue well into this year.

Companies that prioritize employee skill development and growth while investing in helpful tech and automation (combined with flexibility and remote work options) will be well-positioned to attract and retain top talent in the logistics industry. Furthermore, businesses must look into their hiring process and make it easier, quicker, and more streamlined. Lastly, most companies often fall back due to their outdated sourcing approaches.

To learn more about how you can use Joveo’s award-winning programmatic platform to find great-fit talent, see us in action!.

The post Top Logistics Talent Challenges in 2023 – And How to Overcome Them appeared first on RecruitingDaily.

Interviewing is still a primarily analog process, which makes hiring more subjective than it could or should be. In fact, HR teams report that 85% to 97% of hiring is based on gut instinct. That’s right, one of the most important and impactful processes in HR is still based primarily on instinct rather than data.

It’s no wonder that turnover rates are high and 60% of candidates report a poor interview experience. Turnover can be due to many factors but is often related to expectation setting and proper transparency during the interview itself. In a tight labor market like we’re facing today, startups and HR teams face massive challenges in filling open positions and can no longer afford to be hindered by ineffective analog interview processes. Gut instinct must be fact-checked with data.

Fact-checking Gut Instinct With Data

Gut instinct may always remain a reality of hiring, but what if we could augment instinct with objective data? Conversational analytics solutions now provide a way to automatically gather, synthesize, and present summarized, objective candidate data that helps recruiters and hiring managers compare their instinct with objective findings from the interview. Also referred to as conversational intelligence or conversational AI, these solutions extract data and insights from human-to-machine or human-to-human conversations.

A common use case for conversational analytics in human-to-machine interactions is leveraging chatbots to field customer service issues. The chatbot collects data to determine what the problem is and whether the customer is satisfied with the answers provided. In the area of human-to-human interaction, we’ve seen conversational analytics applied to the sales domain. Solutions such as Gong and Chorus listen to calls to extract “sales intelligence” to analyze the quality of opportunities.

Finally, we’ve arrived at the era of conversational analytics applied to HR, where solutions like HireLogic listen to job interviews and extract “interview intelligence” for a comprehensive understanding of candidates and what was covered during the interview.

How Conversational Analytics Radically Changes Interviewing

Conversational analytics provides interview intelligence automatically after an interview is completed. Some solutions in the market claim to provide interview intelligence, but instead, provide “interview metrics” like talk time and talk ratio, and allow users to manually highlight snippets of the transcript for review.

True interview intelligence goes beyond metrics to provide time-saving insights that help with hiring decisions. It detects the skills, job functions, industries, and titles discussed, reports how much of the conversation covered those topics, and flags portions of the transcript to surface candidate characteristics such as leadership qualities, aspirations, likes, and dislikes. This succinct analysis helps hiring managers understand how thorough an interview was, whether the interviewer’s recommendation is reliable, and what type of follow-up questions might be required.

To reduce bias and ensure compliance, interview intelligence flags potentially inappropriate questions around age, gender, marital status, or other personal traits so that employees can be coached on how to be better interviewers. For example, asking a candidate how old their children are may seem innocuous but could lead to age-related discrimination. Oftentimes, people don’t even realize they’re doing it, so it’s helpful to have AI attempt to detect and identify opportunities to improve interview compliance.

Having been a founder, a board member, and a C-Suite leader at several companies, I know how important interviewing is to find the right team member. Even the most seasoned manager can find it challenging to simultaneously think of the right questions to ask, listen carefully to the response, and take good notes that can be used for objective hiring decisions, all while trying to build rapport and engage with the candidate. When you compound this challenge across multiple team members, candidates, and positions, it quickly becomes apparent that having objective data to make informed hiring decisions helps tremendously to fact-check instincts and unconscious bias. Having used conversational intelligence to help gather this data automatically during calls, I never want to do another interview again without it.

Imagine the Data From 30 Million+ Interviews per Month

At the start of 2023, there were approximately 11 million job openings in the U.S. If you assume conservatively that there are three interviews conducted per opening, that’s over 30 million interviews a month, or roughly 1 million interviews happening every day in the U.S. alone. This is a significant amount of time and resources that organizations are spending to conduct interviews for hiring, and it’s still a mostly subjective process prone to unconscious bias.

If all that data could be instantly gathered and applied to augment the interview and hiring process, organizations may save countless hours, reduce unconscious bias, and experience less turnover. But most exciting above all is the prospect of helping both hiring managers and job seekers finally find the right fit for a productive and beneficial relationship.

The post The Last Analog Process: Job Interviews appeared first on RecruitingDaily.

Cornerstone OnDemand unveiled what it calls the industry’s first holistic career growth, mobility and talent marketplace. Available through the company’s Talent Experience Platform, Opportunity Marketplace combines AI with the principles of human-centered design. The goal is to unlock new possibilities for employees while helping organizations improve engagement, retention, workforce agility and internal mobility, the company said.

Phenom released new products and features at last week’s IAMPHENOM conference, including tools to improve talent acquisition’s efficiency, monitor and manage the skills-related needs of both employees and managers, and leverage AI to automate content creation and eliminate a number of tasks normally shouldered by users throughout the talent acquisition process.

Eightfold AI said it’s integrating recent versions of generative AI large language models in order to create two role-specific Talent Intelligence Copilots. On top of that, Eightfold’s Talent Insights will reflect the changing skills and roles created by generative AI in the labor market. Eightfold said that with the changes, the Talent Intelligence Platform will offer greater assistance for both employees and recruiters, increasing both effectiveness and productivity.

Talent acquisition software company Radancy acquired Ascendify, a cloud-based talent engagement software platform. According to the company, the acquisition enhances Radancy’s suite of solutions focused on helping enterprises find the talent they need to strengthen their business.

HireRight appointed Venkat Bhamidipati to its board of directors. In addition, the company said he will serve on the audit committee.

The post HCM Talent Technology Roundup April 07, 2023 appeared first on RecruitingDaily.

But lately, there’s been a shift. Talent leaders are starting to take artificial intelligence more seriously, especially as smaller teams and budgets are forcing teams to adopt technology that can help them scale with less. Those same leaders are also seeing the impact AI has had in other functions like sales, marketing, and R&D, dramatically improving their ability to work at scale.

And yet, new regulations like New York’s Local Law 144, would seek to limit how recruiting teams use AI.  For the unfamiliar: Local Law 144 would require employers to conduct bias audits on automated employment decision tools (AEDTs), including those that use AI and similar technologies, and would require employers to provide specific notices about such tools to employees or job candidates who reside in New York City. Others have pointed out the ways in which this particular legislation might not actually have much impact, but the law and its passing illustrates the ways in which we’re still thinking about AI in recruiting all wrong –– ultimately, this law and others like it could materially slow down the adoption of software that can benefit recruiting teams that are serious about scaling their diversity recruiting efforts.

Bias for Good

Recruiting is a special use case, and concerns around AI’s potential to negatively impact candidates who are part of underrepresented groups aren’t unfounded, especially as tools touch ever more elements of the recruiting and hiring pipeline –– from how candidates find roles, to resumé scans, to facial and voice recognition software leveraged in the interview process.

But there’s a flip side to that coin: tools that use AI specifically to support the hiring of underrepresented groups. While AI can unintentionally filter out candidates for certain groups based on keywords and NLP, it can also –– when applied intentionally –– do the exact opposite, and surface candidates from underrepresented groups to help diversify pipelines. Regulation that doesn’t acknowledge that there are tools and applications that are specifically designed to support underrepresented groups by quite literally filtering candidates with different backgrounds into candidate pools. Thinking only of the ways AI and automation can result in negative outcomes demonstrates a too-narrow view on these tools, and could do more harm than good in their attempts to prevent bias in hiring.

Optimizing for Candidate Control

The ethics around AI application for the talent acquisition and hiring process depends heavily on where the technology is applied: it might be an issue if it’s automating the pipeline for recruiters and potentially weeding out qualified candidates before they’re reviewed by a human, but not if it’s designed to support candidates in finding and applying for relevant roles. For example, algorithms that match candidates with skill-relevant, available job opportunities so that qualified candidates don’t miss out on opportunities, or even better, algorithms that uncover ‘inferred skills’ to match candidates with roles they wouldn’t have applied for otherwise.

AI tools can also analyze the behaviors of a candidate on any given platform to understand and surface roles in which they’re actively interested; this a fantastic way to optimize the process for job seekers.

AI vs Referrals

Many companies –– from startups to Fortune 500s –  rely on referrals to fill open roles, which data shows can lead to a homogeneous workforce. This is in part because referrals lend a helping hand in narrowing down vast quantities of applicants to vetted candidates. But AI done well can do the same, and when it’s designed to surface candidates that meet predetermined D&I thresholds, it can support the hiring of talented, qualified candidates who might have otherwise been overlooked, or who because of their background, wouldn’t have come in via referral.

Not only is prioritizing DE&I objectively the fair and right thing to do and an important part of a forward-thinking, equitable society, but it’s also simply good for business; companies that prioritize these efforts are more productive and successful, while employees are happier and stick around longer. And as Gen-Z enters the workforce, the candidate pool is objectively becoming more diverse, so preparing to attract underrepresented candidates contributes to future proofing any business.

It’s the People Team’s Turn

Sales, marketing, and R&D have had all the fun with AI –– it’s far less prone to amplifying systemic issues in those contexts. But now it’s the people teams turn to embrace this technological shift, while giving feedback on all the ways it can disenfranchise the very people we serve and thinking of ways to use these advances to support positive outcomes, rather than regulating them out of processes point-blank in service of “less bias.”

The opportunity to adopt technology now to support diversity efforts at scale is a massive one, especially as companies experience a slower pace of hiring relative to the frenzied pace of the last few years. If you’re not laying the foundation for attracting underrepresented people in new, tech-enabled ways, companies risk losing out on exceptional talent –– and losing the competitive edge that AI can provide.

The post Leveraging AI In Recruiting To Uplift Underrepresented Groups appeared first on RecruitingDaily.

The company said, the system uses GPT technology to break down job descriptions into search criteria such as job title, required skills and preferred skills. From there, it analyzes over 800 million profiles in SeekOut’s talent database to find the best matches.

As such, the only task for recruiters is to paste a description into the software and wait for the list of qualified candidates to be generated, cutting down on the time and effort usually spent seeking out potential candidates manually.

Personalized Outreach at Scale

The best recruiters research candidates and craft highly personalized messages to increase their email response rates. SeekOut Assist generates a personalized message to the candidate based on their unique qualifications for the role.

In addition, SeekOut Assist analyzes the information in each candidate’s SeekOut profile, including skills and experiences. The technology uses the candidate profile and job description to write a personalized outreach message to the candidate, improving the chances of a response.

SeekOut believes its new approach to generative AI could have a serious impact on how recruiters get their jobs done in the future. To use Josh Bersin’s words, “Generative AI will be a total game changer in HR.”

“SeekOut Assist is a big step forward in solving real business problems with the power of Generative AI and will make our customers radically more productive and effective,” said SeekOut Co-Founder and CTO Aravind Bala. “We’re excited about the future of AI in the HR technology space, and look forward to working with our customers and partners to build new tools that make recruiters’ contributions to their organizations even more strategic.”

What This Could Mean

This could be a step in the right direction for the use of AI in hiring. Recruiters have been focused on the role of AI in the field since long before the introduction of ChatGPT because of the variety of uses and the possibility of timesaving. As we’ve said in the past, recruiters and hiring teams need to practice caution when it comes to new software like ChatGPT. But that doesn’t mean that these technologies are useless.

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Paradox announced its conversational ATS focused on front line hiring. The system uses a conversational UI for engagement built around hourly hiring and deskless workers, who primarily use mobile devices to get their work done. With the solution, Paradox aims to reimagine the high-volume hiring process and deliver better experiences for both candidates and hiring managers.

HR platform Deel partnered with talent acquisition solution provider RAMP Global to help organizations grow teams at scale, across a range of areas and skills. According to the company RAMP Global supports HR, procurement and finance departments by streamlining the candidate supply chain, increasing access to talent and reducing hiring costs. With the collaboration, the companies hope to further their goal of helping fill vacant roles quickly at a time when talent is hard to attract and retain.

SourceWhale added enhancements to its platform, allowing customers to gain a deeper insight into their outreach performance metrics such as conversion rates, channel performance and sentiment. As such, the company hopes to help organizations improve decision-making and efficiency while engaging their target audience.

Background screening and identity services company Sterling acquired A-Check Global, a global workforce management, employment and procurement solutions company. According to the company, the deal will expand Sterling’s presence in key U.S. verticals, including Healthcare, Industrials and TechMedia.

The global recruitment process outsourcing market size is projected to reach $21.6 billion by 2027, at a CAGR of 17.0%. According to Valuates Reports, the two primary factors driving market growth are the need for an effective recruiting process and the reduction of overhead costs.

The post HCM Talent Technology Roundup March 31, 2023 appeared first on RecruitingDaily.

At this time, it’s important to balance hype with caution. While the temptation to embrace tools of this nature will be strong, using generative AI in recruitment is not something that can be recommended right now. There’s no doubt that the versions of generative AI tools we’re seeing today will improve. But as it stands today, these platforms often provide inaccurate information, the process by which they produce output is opaque (which can make a company vulnerable to legal and regulatory challenges), and they’re prone to making biased judgments.

However, this doesn’t mean HR teams should dismiss AI altogether. By using the technology with rigorous controls and oversight in place – in conjunction with other proven inputs – they will be able to develop more efficient and data-driven hiring processes.

Efficient, Sure… but Worth the Risk?

The efficiency capabilities of generative AI make it tempting to use in the hiring process. One way to think about generative AI is that it saves you the trouble of consulting the Internet and instead produces a neat summary of what the internet says, or is likely to say, for you. The information provided by Generative AI tools can sometimes be used directly, or as inspiration for your own content. However at this time, there are several issues that could arise when using these tools to create content for HR purposes.

Let’s start with a less risky use case and see how it stacks up. Generative AI can be used to generate content such as job advertisements. This use case poses less concern, mostly because the internet is awash in job ads and this means that there’s lots of content for the model to draw on. Writing jobs ads can be pretty tedious for humans, so it seems like a great use case for generative AI. Even in this case, though, it’s not without risk. If existing jobs ads use language that is biased according to age, race, or gender, then these biases will also be present in jobs ads produced by the tool. It could produce content that misrepresents your job or which is factually incorrect. And you could inadvertently breach another party’s copyright if the tool reproduces existing text exactly.

Another use case is using Generative AI to create a formal job description. This is riskier because a document such as a job description can have important legal consequences in the event that a selection decision is disputed – the job description, and what’s in it – is often relied upon as the source of truth for job duties and required knowledge, skills, abilities and other characteristics.

Using a Generative AI tool to help develop a job description means that the content of that description is based in part on information about the job (i.e., the prompt that was supplied to the tool) as well as information that effectively boils down to “words that tended to co-occur with the prompt text on the internet”. Using Generative AI in the process of creating documents like this could seriously undermine the utility and legal defensibility of those documents.

Similar issues apply when using Generative AI to develop interview questions. Interview questions need to be relevant to the job to be legally defensible. There is always the risk that interview questions generated through Generative AI will be related to typical descriptions of the job that were part of the training dataset but that do not match the actual specific job being recruited for.

A Lack of Guard Rails

Experience with Generative AI to date suggests that there are few guard rails that prevent the language model from producing content that is nonsensical or incorrect. If the training data does not provide sufficient information for a meaningful response, the Generative AI tool will rely on the probabilistic nature of the language model to produce a response that is “likely” given its data. This may especially be a risk when generating interview questions for jobs that are highly specific and unusual.

A language model is purely based on the likelihood of text appearing in the context of other text. While the nature of AI chatbots can lead users to believe that the tool understands issues of intent and applicability or is guided by some kind of knowledge-based process, the systems have no understanding of what the user is trying to achieve, or how the produced content may be used. This can result in content, in interview questions for example, that may be illegal or discriminatory in some jurisdictions.

Consistency (And Lack of Bias) Not Guaranteed

There is a much higher level of risk when Generative AI is used to process or draw conclusions from applicant data. For example, using a Generative AI tool to summarize a candidate’s resume, or using the tool to compare two candidate’s resumes. Doing this may violate a host of data privacy and data processing regulations, depending on your legal jurisdiction. Additionally, when used in their off-the-shelf on-line services, Generative AI tools do not guarantee that the same input data will result in the same response. A baseline requirement for using AI and automation to evaluate candidates is that identical input should produce identical output. The probabilistic nature of the language models used means that this will not occur without special modifications or settings being applied. Tools such as ChatGPT have not been validated for use in employee selection contexts – there’s no evidence that they produce judgements which aid in the selection of high performing employees. The results that they produce can reflect the same kinds of biases that are seen in online text that was used in their training data, including bias based on protected classes such as race, gender and age.

Given that the Generative AI tools are trained on the basis of internet text, perhaps a good analogy is whether it would be reasonable to post a summary of an applicant’s resume on Reddit and ask users to comment on how suited the applicant would be to the job. If that strikes you as inappropriate, then using a Generative AI language model to do the work is essentially the same.

Developing a Reliable and Holistic Hiring Process

Considering the growing interest in developing AI-powered hiring processes, HR professionals need to figure out how these processes can be implemented productively and with minimal risk. SHRM’s 2022 survey found that 85 percent of HR professionals who use automation and AI for hiring do so to save time and increase efficiency. But just 18 percent believe these technologies improve their “ability to identify more diverse candidates,” while 46 percent want resources that will help them “identify potential bias when utilizing automation or AI tools.”

These findings indicate that HR professionals are rightly circumspect about using AI for hiring, and should extend this caution to the question of Chat GPT. There are many ways employers can address concerns about inaccuracy and bias – for example, they can develop a hiring process that incorporates multiple inputs to generate a strong talent signal and filter out information that isn’t job-relevant. Trained hiring professionals can use AI to retrieve basic information about candidates, but they should also use objective assessments, structured interviews, and other resources to fairly evaluate potential hires.

There’s no doubt that generative AI is an extremely powerful tool that will only become more useful in the coming years. But we’re also learning more about the limitations of these models every day, as well as the difficult task of improving them. This is why HR professionals should use AI with care and remember that there are many other ways to make the hiring process as fair and predictive as possible.

The post How Hiring Managers Can Avoid Dangerous Misuses of Generative AI appeared first on RecruitingDaily.

The talent engagement and analytics platform helps organizations to streamline workflows and manage the recruitment process all in one location. In addition, the solution creates a way for recruiters to leverage data and automation to engage talent, build pipelines and hire at scale with ease.

The integration also allows Gem and SAP users to:

• Build Diverse Talent Pipelines: Discover and attract qualified candidates across any channel, including past applicants, prospects on social networks and talent communities.
• Deliver Better Candidate Experiences: Automate reminders, follow-ups and report sharing so you have more time to make every candidate feel taken care of.
• Shift From Reactive to Strategic Recruiting: Analyze funnel, benchmark performance and forecast capacity needs to plan for future growth.
• Get the Most Out of An Existing TA Tech Stack: Accelerate ROI with a central system for engagement, collaboration and productivity.

Partnering for Success

These announcements come as Gem recently began a partnership with SAP through the PartnerEdge program, which provides companies with enablement tools, benefits and support for building better applications. The company said the partnership and integration will “ensure Gem’s customers on SuccessFactors get up-to-speed even faster, ultimately accelerating return on investment.”

“We’ve partnered closely with the SAP team to build a deep integration that allows customers to get up-to-speed with minimal IT work and start seeing value from Gem almost immediately,” said Gem’s CEO, Steve Bartel. “Based on early feedback, we know that many enterprises are excited to join the Gem customers who are already using our solution to recruit strategically and build great teams.”

A 30-day free trial of Gem’s solution will be available on the SAP Store.

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Hireology announced an AI-powered recruiting assistant, called Beaker. It can generate job descriptions in a matter of seconds, the company said, empowering employers to attract the right candidates more quickly for their open positions. Beaker is powered by ChatGPT, an advanced language processing model developed by OpenAI. The product allows users to input details like a job title and location. Once they’re done, Beaker generates a clear and concise job description that is optimized for search.

High volume ATS provider Fountain added a conversational AI feature, Fountain AI, to its product suite. The feature helps recruiters to screen and qualify candidates efficiently and automates manual processes. Fountain AI aims to accelerate the hiring funnel and help hiring managers get candidates through the process faster, according to the company.

SkillGigs, a talent marketplace that pairs healthcare and technology job seekers with AI-matched work opportunities, unveiled a new platform experience for its users. With it, the company believes both employers job candidates can more effectively create listings, screen through matches and have more productive compensation negotiations during interviews.

Recruiting platform HeadRace raised $6 million in seed funding from Greylock, Susa Ventures and Breyer Capital with Packy McCormick, Kindergarten Ventures and Blue Lion Global participating in the round. The company also announced that its technology platform is now available to any recruiter or employer who wants to use it. For recruiters, HeadRace offers a technology platform that provides opportunities to connect with new customers and earn.

Talent assessment platform Plum announced that Greggory Moran has joined the company as senior director of partnerships. He brings a heap of industry experience including his most recent position as director of partnerships at PandoLogic.

The post HCM Talent Technology Roundup March 24, 2023 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.

The tech industry is booming, but DE&I falling short remains a problem. Black and Hispanic workers remain underrepresented in STEM professions, while women are particularly underrepresented in engineering and computer science. Despite the proven benefits, many companies struggle to foster a culture of diversity, equity, and inclusion.

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The post Building Diversity: A Recruiter’s Guide to Improving DE&I Outcomes in Tech Companies appeared first on RecruitingDaily.

There’s no denying that connection is a fundamental human need – one that doesn’t just go away when we’re working. And while distributed work provides benefits when it comes to well-being and flexibility, it can leave many of your employees feeling isolated and out of the loop. When you lack those meaningful moments of connection, productivity and engagement suffer.

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In this on-demand webinar, Andrea Dumont, CMO at Enboarder, and William Tincup, president at RecruitingDaily.com, give an insightful discussion about the role workplace relationships play in creating meaningful moments across the entire employee journey.

In this webinar you will learn about:

• New research on the state of connection, trust, and belonging at work
• The risk of letting critical employee connections dissipate
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This Program has been approved for 1.00 Webinar/Webcast/Podcast recertification credit hours toward aPHR, aPHRi, PHR®, PHRca®, SPHR®, GPHR®, PHRi and SPHRi recertification through HR Certification Institute® (HRCI®).

The post How to Design Meaningful Moments at Work appeared first on RecruitingDaily.

As demand for tech talent increases, recruiters and hiring managers need to find new ways to stand out and attract qualified candidates. CodeSignal’s comprehensive eBook provides an in-depth look at the fundamentals of incorporating technical assessments into your hiring process, from moving toward skill-based hiring to choosing the right assessment tool.

What’s Inside?

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The post A Complete Guide to Conducting Technical Screening & Assessments appeared first on RecruitingDaily.