Category: Blogs

Skills Architecture is the key to SBO – and AI is the tech enabler

Posted on by Isabelle Bichler

Talent acquisition specialists are continuously challenged to match candidates with the right skills to positions that feed evolving business needs. Technology and data are the one-two punch that empowers HRs to do so effectively.

Skills Architecture: Building the SBO Foundation

A comprehensive skills architecture helps HR leaders start the process with a clear understanding of what skills are already within their talent pool and where the skills gaps lie so they can target the right candidates more quickly. 

As such, skills architecture acts as the blueprint that defines and structures the skills within an organization, unifying skills language and moving beyond traditional job descriptions to establish an agreed-upon nomenclature. It’s the foundation on which a centralized Skills-Based Organization is built, pulling together skills data across teams to form a larger, more strategically malleable view.

“We’ve always historically said that this system doesn’t talk to this system, and this system doesn’t talk to this system, and the spaghetti plate of systems is what disables us from getting data or from making informed decisions that are embedded and rooted in true data and analytics,” says Sadia Ayaz, VP of Talent Management for Veolia. “Here we are today, capable of doing that. AI can take all of that unstructured data and make sense of it.” 

AI: The SBO Tech Enabler

AI’s machine learning algorithms and expedited data analytics are the technological backbone of a sophisticated skills architecture. This is due to its ability to: 

  • Ingest vast datasets to identify both existing and emerging skills within an organization 
  • Detect patterns and trends, allowing HRs to stay ahead of critical skill gaps or areas that require upskilling
  • Reveal hidden talent within an existing workforce, uncovering internal job candidates for consideration

Beyond talent acquisition, AI-driven technologies also fortify talent management strategies in a Skills Based Organization. Through personalized learning paths and recommendations, AI enables employees to acquire new skills in alignment with organizational goals, while also benefiting from individualized professional development. 

By harnessing the power of AI to construct a detailed and dynamic skills architecture, and engaging AI as the tech enabler for a successful Skills-Based Organization, HRs can hire and retain the right talent to fuel an SBO workforce model. Synergy between skills architecture and AI is the cornerstone of shaping the future of talent acquisition and organizational success.

Learn more about the power of retrain.ai’s Talent Intelligence platform here.

Mastering Hiring Challenges: How AI Levels the Field for Companies of All Sizes

Posted on by Isabelle Bichler

Large enterprises and smaller organizations have similar challenges when it comes to hiring: Finding the right people for best-fit positions quickly, accurately and efficiently.

This at a time when 53% of in-house recruiting pros predict their recruiting budget will decrease or stay flat this year.

Fortunately, the emergence of AI-driven talent intelligence platforms has leveled the playing field, providing companies of every size with powerful tools to attract, hire, and retain top talent with the skills needed for success. 

The AI Advantage

A December 2023 report from Gartner names technology as the No. 1 investment area for HR leaders–for the third year in a row. The reason? HR increasingly relies on technology to meet a growing list of business demands, including fulfilling employee experience needs, enabling talent agility and continuing HR tech transformation.2

AI-driven talent intelligence platforms act as force multipliers, by automating time-consuming tasks, enabling the agility needed for companies to achieve more with fewer talent resources. 

Data insights generated by AI can also empower companies to target their efforts more precisely, ensuring that every investment in talent pays off in the quest for sustainable growth and competitiveness in the marketplace.

AI-driven platforms provide an advantage by: 

  • Analyzing vast amounts of data at lightning speed, providing actionable insights to help HRs make informed hiring decisions
  • Streamlining the sourcing and screening process, reducing time-to-hire and ensuring HRs can compete effectively for top talent
  • Personalizing internal mobility opportunities, using skills data to predict potential career pathing options for employees.

AI-driven automation frees up HR professionals to focus on larger strategic initiatives; and just as importantly, to spend more time on the face-to-face, human-centric aspects of the job. 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo.

SBO moves from theory to practice; AI matures as the tech enabler

Posted on by Isabelle Bichler

As AI-driven HR technology advances, and as Skills-Based Organizations move from strategy to execution, the SBO workforce model is primed to mature in 2024. 

First, the technology.

Generative AI was the tech buzz of 2023, spotlighting its almost unlimited potential to automate tasks and streamline business processes. As such, AI has quickly become vital to the Skills-Based Organization workforce model; specifically in its ability to screen hundreds of resumes at lightning speed and to pull skills information from resumes, job descriptions, and any labor related content. retrain.ai’s Talent Intelligence Platform which was built on the next generation AI from the ground up, offers the Skills Architecture Module as the foundational element for managing the workforce and understanding the current organizational skills state, benchmarking it against the skills required in the industry and recommending which top skills to adopt and enhance, allowing significantly greater agility in acquiring, developing and deploying talent. 

Organizations enamored with the idea of AI for AI’s sake, however, can find themselves with more applications than are needed to address their specific needs, with the additional costs that come with them. In 2024, HR leaders will continue to evolve into more tech savvy professionals, collaborating with their counterparts to first identify problems to solve, and then carefully choose platforms that offer the right solutions to talent acquisition and talent management challenges.

Then, the data.

With the best technological solutions in place, HR leaders are on the right path to solving business problems. Ultimately, though, the goal is reached with data.

“We need to think less about platforms and more about data,” says Dr. Sandra Laughlin, Chief Learning Scientist and Global Head of Talent Enablement & Transformation for EPAM Systems. “As new tools are coming out, new and better data sources are revealed. Generative AI can offer feedback on things that are difficult to observe and coach.” 

To fuel efficient skill-based talent acquisition efforts, for example, AI-driven data insights enable precise candidate matching based on exact skills and attributes required for specific roles. Skills-focused data–and the lack of demographic and other potentially biased data–supports diverse talent pools and an inclusive pipeline.

“The big difference [between the types of AI companies] is that a great AI company is a data company. They get a lot of data, they know what the data means, they spend a lot of time making sense of the data,” says analyst Josh Bersin of The Josh Bersin Company. “They use the data in your company matched against (exterior) data so that the data in your company can be classified and used in a more and more intelligent way.” 

retrain.ai was honored to be recognized as one of the “built on AI” type of  companies, based on billions of labor market data points, with accurate and automated skills detection and assessment, enabling in-depth skills analysis and forecasts to inform and improve strategic workforce planning efforts, increasing quality of hire when used to match internal and external candidates to open positions, and empowering reskilling and upskilling initiatives to improve learning and career path recommendations.

Learn more about the power of retrain.ai’s Talent Intelligence Platform here.

Gartner report: Mitigate Bias From AI in Technology

Posted on by Isabelle Bichler

The following is a summary of “Mitigate Bias From AI in Technology,” a report from Gartner. The full report is available for download here (For Gartner Subscribers). 

Summary

Organizations are rapidly adopting AI in HR, while regulations are struggling to keep up. As part of their HR strategy, HR leaders must promote responsible AI in their applications by mitigating bias that poses risks to talent management, the employee experience, DEI and more.

Key Findings from the Gartner report

  • Fifty-three percent of HR leaders are concerned about potential bias and discrimination from AI. Bias in AI is unavoidable; however, HR leaders can establish best practices that mitigate this bias.
  • Thoroughly vetting HR technologies for bias requires an understanding of business processes. Broad overarching assessments can lead to missed sources of bias, or to inaction due to fear of getting it wrong. The organization should assess each use case individually.
  • AI regulations, including HR-specific measures relevant to bias, are gradually taking effect. Since many HR functions plan to buy AI capabilities built by vendors, HR leaders face the need to monitor technology providers for their regulatory compliance and ethical considerations.
  • HR leaders are positioned to take a leading role in advancing practices that bolster openness about the potential impacts of bias from AI applications, and 35% of HR leaders recently reported they expect to lead their organization’s enterprise wide AI ethics approach.

Gartner Recommendations

HR leaders responsible for technology strategy must:

  • Map possible sources and outputs of bias for each AI use case in HR to assist in flagging areas of risk and monitoring vendors for their commitment to responsible AI practices.
  • Require and evaluate bias mitigation from HR technology providers offering AI functionality by assessing criteria related to their data, algorithms, organizational context, regulation compliance and ethical considerations.
  • Promote transparency into the potential impacts of AI’s bias by collaborating with external and internal stakeholders to take decisive steps in protecting the organization, the future of work and society at large.

Gartner, Mitigate Bias From AI in HR Technology, By Helen Poitevin, 16 October 2023

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

How Generative AI Transforms Talent Intelligence

Posted on by Isabelle Bichler

For businesses competing in today’s fast-paced landscape, leading the market means having the right people with the right skills in the right roles. Generative AI has risen to the top of this conversation as a way to more efficiently and accurately reach that goal. 

But what is Generative AI, and how can it revolutionize talent intelligence? If you’re a CHRO, technical innovation leader, or workforce strategist looking to harness the power of AI for HR, here’s what you need to know.

What is Generative AI?

Generative AI is a subset of artificial intelligence that focuses on creating new, original content, rather than simply analyzing or processing existing data. Using vast datasets to learn patterns, relationships, and styles, generative AI technology is able to generate human-like content, whether it’s text, images, or even music.

Generative AI in Hiring

Finding the right talent has always been a critical challenge for HR professionals. When it comes to sourcing, screening and securing the right candidates with the skills needed for business success, generative AI can assist in multiple ways:

  • Skills Extraction and Matching: By analyzing resumes and job descriptions with unprecedented speed and accuracy, Generative AI solutions can quickly identify candidates who best match the required skills and qualifications for an open role. This means talent acquisition specialists can cut time and cost to hire by zeroing in on the right people to move through the hiring process.
  • Candidate Engagement: Chatbots powered by Generative AI can interact with candidates, answer questions, and schedule interviews, ensuring a seamless and efficient recruitment process while freeing HR leaders up to focus on more interpersonal elements of the hiring process.
  • Diversity and Inclusion: Generative AI can support a fair and inclusive hiring process by focusing solely on qualifications and skills, eliminating demographic and other information that can introduce unintended bias.

Generative AI and Internal Mobility

Fostering internal mobility is essential for employee growth and retention. In fact, it’s been shown that employees with a clear view toward future opportunities are more likely to stay with an organization, making proactive upskilling channels a business imperative. Generative AI can assist by:

  • Skills Mapping: Generative AI can help identify employees’ skills, capabilities and interests in order to more accurately suggest potential career paths within the organization.
  • Learning Recommendations: When opportunities are identified in the form of open roles, gigs or projects, Generative AI can produce relevant upskilling pathways to help them acquire the new skills required to pursue them.
  • Succession Planning: By analyzing employee data around skills, capabilities and aspirations, Generative AI can aid in identifying high-potential employees and preparing them for leadership positions.

Generative AI and Skills-Based Organizations

The traditional job-centric approach to workforce planning is quickly becoming outdated, as more companies shift to a skills-focused model. Generative AI supports this transition through:

  • Skills Gap Analysis: By powering a data-driven skills architecture, Generative AI can analyze the skills already present in a workforce, those needed in the future, and how to bridge the gap between the two with employee upskilling or reskilling recommendations.
  • Skills Tagging: Generative AI can automatically tag skills to employees based on their experiences and achievements, creating a comprehensive, continuously updated skills inventory.
  • Adaptive Training: Personalized training plans can be fueled by Generative AI, ensuring employees are continually developing the skills necessary to excel in their current and future roles.

Considerations for CHROs

While Generative AI holds immense potential to elevate HR functions, there are some critical considerations for CHROs when evaluating AI platforms for their HR technology stack:

  • Data Privacy: Ensure that data privacy regulations are followed rigorously, including the safeguarding of sensitive employee and candidate information.
  • Ethical Use: Develop Responsible AI guidelines to comply with regulations and prevent bias, discrimination, or misuse of technology in hiring decisions.
  • Integration: Ensure the AI system can seamlessly integrate with your existing HR software to maximize its efficiency and avoid the delays of a rip-and-replace solution.
  • Training and Support: Invest in staff training to help HR teams understand and effectively use Generative AI tools as well as welcome user feedback.
  • Continuous Improvement: Keep in mind that AI is not a static, set-it-and-forget-it solution. Technology solutions require regular updates and fine-tuning to remain effective.

By automating processes, reducing biases, and focusing on skills, Generative AI enables HR professionals to make more informed decisions and create a workforce ready for the challenges of the future. As a CHRO or HR leader, embracing Generative AI can lead to a more agile, efficient, and innovative HR function, giving your organization a competitive edge in the talent market.

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo.

HR Tech 2023 Highlight: Generative AI Isn’t a Trend, It’s a Problem Solving Tool

Posted on by retrain.ai

At HR Tech 2023, retrain.ai Co-founder and COO Isabelle Bichler-Eliasaf sat down with Dan Riley, co-founder of RADICL, to talk about the surge in Generative AI solutions in the HR space and the importance of its ethical, responsible use. Below are excerpts from their conversation; the full recording can be viewed here.

DR: You brought up responsible and ethical AI. How are we doing? Not just retrain.ai, but the industry in general. Are we getting there?

IBE: This year, everybody is talking about AI. Specifically, everybody’s talking about generative AI, and ChatGPT was a great demonstration to show the amazing abilities of AI. But it also showed the pitfalls. It showed it to be erroneous, biased and very generic, not stable enough. So Responsible AI is all about that; putting safeguards on the AI. It’s just a tool, right? So you need to use it wisely with the right safeguards. 

Responsible AI principles span from explainability and bias reduction to consent and embedded privacy rights and so forth, and that’s what we’ve been doing at retrain.ai from the get-go. This is something that’s very important to me, it’s something that I’ve done as part of my research as well around the risks of AI. So now I’m happy to see that a lot of people are thinking about it and starting to do something about it. 

Too often, we either blindly trust AI or we blindly distrust it. But it can’t be a binary conversation. So how do we find that middle ground? How do we challenge it and use it for good? What are some of the things retrain.ai is doing to make sure that happens?

It’s about design, development and deployment. It’s about the safety that we put into the technology, first of all to understand the data that we need to be distributed. And, you have to have representation for different protected classes, for example, to prevent biases. You also have to constantly measure the output and understand if it’s having an adverse impact on certain protected classes – gender, age, ethnicity, and so forth. Those safety guards must be in place all the time.

There’s also a lot of regulation emerging now to enforce that. Local law 144 in New York City is actually mandating that companies show and prove that their output isn’t biased. Beyond biases and discrimination, it’s also about explainability. With our product, we explain why a person is a good fit for a position based on their skills. It’s not a black box; the tool has to be transparent and explainable. 

So we’re here at HR Tech, where for the most part if you talk to any vendor, they’re going to talk about what they’re doing with AI. What’s your advice for the industry in general?

I think you first need to really understand the problem that you’re solving. AI is a tool; so it’s not just about saying hey I want to bring in AI, I want to bring efficiency. What is the pain point? What is the problem you’re solving? What’s the use case? And then, do you have the right tool for it? Once you have that, you’re okay. But just adopting AI across the board because it’s something trendy or because the notion of efficiency is there, or productivity, it’s not enough. You need to know the problem you’re solving. And depending on the use case, you need to have technology with deep AI; not just augmentation and chatbots. It’s really the data that’s used, and the algorithms, and the generation of AI. You need to use really advanced models based on LLMs, with safety guards, in place to give you the results you want. 

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo. 

AI’s Role in Revolutionizing Talent Acquisition and Retention

Posted on by Dr. Shay David

This article originally appeared in Forbes.

As corporations grapple with the challenging task of attracting and retaining highly skilled talent in an intensely competitive market, AI-assisted HR tools are creating a new paradigm. Of course, these innovations can create potential ethical issues during the recruitment and internal mobility processes. Here are things that HR leaders must consider when weighing the pros and cons of implementing these technologies.

AI In Talent Acquisition

Traditional recruitment methods, often laborious and time-consuming, require HR leaders to sift through hundreds of résumés for every open position. These processes can potentially cost thousands of dollars if a position remains unfilled, even reaching six figures when considering senior or technical roles. Furthermore, hastily rushing the recruitment process can lead to improper fitting, resulting in higher turnover rates. With AI-powered platforms, HR leaders can streamline their processes by ensuring a more accurate selection of candidates and accelerating the hiring timeline.

Algorithms can process vast amounts of data swiftly, eliminating the painstaking manual review of résumés. By leveraging natural language processing and machine learning, AI-powered tools analyze and use skills extraction to identify the most relevant skills for a given role. These systems go beyond simple keyword matching; they can apply context to infer skills that aren’t explicitly mentioned in résumés. Semantic skills extraction reduces missed opportunities that occur using only keyword search, creating a selection process that’s more comprehensive for recruiters and more fair to candidates.

At a time when enterprises are rapidly transitioning to skills-based models, introducing an AI-powered platform can help HR leaders quickly assess and rank internal and external candidates based on their skills and capabilities. This not only saves time by revealing best-fit candidates faster but also goes even further by enabling role matching.

Finally, recruitment professionals can use AI to enhance the candidate experience with personalized interactions. Tools like chatbots and virtual assistants provide real-time updates on application status and offer tailored job recommendations, reducing candidate effort and time.

AI In Employee Retention

High employee turnover can significantly impact a company’s bottom line. A survey showed that 63% of employees changing jobs cited lack of advancement opportunities as a main factor. In this context, AI can help HR leaders understand their employees’ needs and aspirations better, then use that knowledge to enhance their journey within the organization.

With AI platforms, talent management teams can analyze large volumes of data to gain insights into factors contributing to employee attrition, such as job satisfaction, work-life balance and career growth opportunities. This personalized insight, regardless of workforce size, allows HR professionals to identify and address at-risk employees’ concerns proactively. For example, an employee who’s remained in one position for a long time may have unrealized potential to succeed on another team in the company. A proactive HR leader will capitalize on AI-driven insights to spot that opportunity and present it to the employee, offering a new challenge and possibly keeping them from looking elsewhere.

Performance management and feedback systems receive support from AI technologies that provide objective evaluations of employee performance. This can help HR leaders and people managers provide personalized coaching and development plans, enhancing overall job satisfaction for employees.

Ethical Concerns And Potential Biases

While AI technology offers numerous advantages, it does raise ethical concerns that HR leaders should stay aware of. These systems can unintentionally perpetuate biases and stereotypes present in historical data. In 2018, Amazon came under fire when it was revealed that an AI-based recruitment system discriminated against women when hiring for technical roles. The platform sought top candidates by positions on their résumés, and considering women had held only about 24% of STEM jobs in the U.S., the majority of résumés fed into the system were from men. As a result, the algorithm developed male preference and gradually deprioritized résumés from women.

Clearly, unintended bias like this can have devastating consequences for an enterprise on several fronts beyond skewed workforce growth. The ripples can be felt throughout brand reputation, customer backlash, candidate trust and more.

Such dangers have prompted an increase in regulation around responsible AI, including Local Law 144 in New York City. The new law requires independent audits of what it categorizes as automated employment decision tools (AEDT) used in hiring within, or from within, New York City—an expansive reach, given the city is a global business hub. While it can be argued that AI-driven platforms don’t automate decisions but rather inform humans’ decision-making, the systems present within an organization’s HR tech stack are included in the regulations.

To remain compliant, HR leaders must ensure diverse and representative training data for any AI systems they implement. Additionally, systems should comply with the five pillars of responsible AI: explainability and interpretability; bias mitigation and fairness algorithms; data robustness and granularity; data quality and rights; and accountability through regular audits and monitoring of the AI’s decision-making process.

HR innovators looking to employ responsible AI-based systems will benefit from first researching available platforms and asking potential vendors the important questions: Is your solution transparent? Can you easily explain how its algorithms work? What bias mitigation is in place? What client onboarding experience can we expect and what training is included?

AI Is Here To Stay

Artificial intelligence is undeniably transforming the world of HR, especially in talent acquisition and retention. The benefits of AI, like streamlined recruitment processes and improved employee engagement and satisfaction, are significant for organizations. By employing ethical, responsible AI-driven systems, enterprises can future-proof their workforce and reap immense benefits.

Update: NYC AI Audit Law (Local Law #144)

Posted on by Isabelle Bichler

As of July 2023, Local Law #144 in New York City is in full effect for enterprises using Automated Employment Decision Tools (AEDT) to assist in hiring decisions. The complete rollout of the new regulation includes punitive enforcement for those found in disagreement with the law.

Given the prospect of a civil penalty for non-compliance, HR leaders are well-advised to keep up to speed on specific requirements of the law, starting with AEDT audits. The law mandates that:

  • AEDT system audits be conducted by an independent entity
  • Summarized audit results be posted on the employer’s website
  • Alternative selection processes or accommodations be provided to job candidates who opt out of AEDT-assisted selection

Despite being known as a NYC-based law, Local Law 144 has generated questions about its actual domain. The geographical guidelines now clarify: 

  • If the role is located in New York City: A bias audit and notice must be sent to NYC residents
  • If the role is located outside of New York City: A bias audit and notice are not required
  • If the role is fully remote but the company has only a New York City office: A bias audit and notice must be sent to NYC residents
  • If the hiring company does not have an office in New York City: A bias audit and notice are not required
  • If the hiring company has offices both in and outside of New York City: Specifics of the role will dictate the need for a bias audit and notice

To break the law down further, let’s start with a few, tangible moves HR leaders and Talent Acquisition specialists can make now to plan for Local Law 144 compliance:

  1. Conduct internal assessments to find out what tools are currently being used that may qualify as an AEDT
  2. Build an inventory and tracking plan for identified AEDTs, including where and how they’re used
  3. Monitor and track AEDT performance, including data input and outcomes, to test accuracy
  4. Develop policies and procedures for storing demographic and selection data needed for AEDT audits
  5. Create a compliance team of HR leaders, legal advisors and tech representatives to prepare or adapt compliance disclosures 

As stewards of Responsible AI, we at retrain.ai are keenly aware that the issues raised by Local Law #144 directly impact the talent intelligence space. Automated, accelerated, bias-free hiring processes powered by innovative technology act as the key to growing and supporting a diverse and inclusive workforce; Responsible AI is the key to reaching DEI goals and remaining compliant.

If your organization is considering integrating an AI-driven solution into your HR tech stack, be sure to check out our Buyer’s Guide to Talent Intelligence to learn more about what to look for, what questions to ask, and how to engage your teams in the process. 

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see it in action, request a demo.

Navigating The Promise And Peril Of Generative AI In HR

Posted on by Dr. Shay David

This article originally appeared in Forbes.

Language has long been the bedrock of our human world; it’s the collective operating system that powers the way we think, feel, interact and make sense of our surroundings. But with the rapid advancements in artificial intelligence (AI), language has also become a crucial interface bridging the gap between humans and machines. Particularly in the HR sector, this evolution comes with both significant opportunities and challenges.

Generative AI, designed to create content that mirrors humanlike patterns of speech and writing, is already beginning to transform HR operations. Leveraged responsibly, it has the power to augment the employee and candidate experience significantly, specifically enabling organizations to identify, attract and retain the best talent effectively while also supporting diverse workforce growth. Conversely, misuse or misunderstanding of these tools can lead to significant pitfalls, from spreading misinformation to challenging trust, authenticity and identity altogether.

The Promise Of Generative AI In HR

Firstly, let’s consider the potential benefits. Generative AI offers unprecedented efficiency and accuracy and can enable the automation of routine HR tasks like screening résumés, answering frequently asked questions and scheduling interviews. This automation not only saves HR professionals’ valuable time but also minimizes the risk of human error, enhancing the fairness and accuracy of these processes.

Organizations are increasingly taking advantage of generative AI for these specific action items in the pre-employment phase. In a recent Littler study, among respondents whose organizations said they are deploying AI and data analytics in workforce management, nearly 70% reported using AI and analytics tools in the recruiting and hiring process.

Secondly, generative AI is a potent tool for improved decision-making. By analyzing patterns and predicting trends, it can generate actionable insights to empower more informed HR decisions. For instance, a generative AI solution could help identify which candidates are most likely to excel in specific roles or flag employees who might be on the verge of seeking new opportunities.

Lastly, generative AI can personalize the HR experience. By understanding individual preferences and needs, it can tailor communications and recommendations, offering a more customized, engaging experience for employees and candidates alike.

The Perils Of Generative AI In HR

However, the advent of generative AI in HR is not without its hazards, most notably the significant risk of misinformation. So concerning is this risk that according to Gartner, by 2027, 80% of enterprise marketers will establish a dedicated content authenticity function to combat misinformation and fake material.

In HR, for example, this could mean an AI system inadvertently disseminates incorrect or outdated information about a company’s policies or job roles, leading to a ripple effect of confusion and potentially serious legal complications.

In addition, bias remains a thorny issue. AI models learn from existing data, which may unintentionally reflect historical biases. Without careful management, these AI systems have the potential to perpetuate these biases, leading to skewed hiring or promotional decisions.

Moreover, privacy and trust are critical concerns. The use of AI in HR often involves collecting and analyzing personal data, which raises privacy questions. As has been emphasized by increasing AI regulations, organizations need to be transparent about their AI usage and take robust measures to protect employee and candidate data.

Lastly, the issue of authenticity and identity cannot be ignored. The line between human and machine interactions becomes blurry with AI. If a candidate interacts with a generative AI system during the recruitment process, they may question whether their responses are genuinely understood or valued. Again, the onus is on the organization to quell these concerns as part of transparent candidate communications.

Navigating The AI Landscape In HR

As we traverse this new landscape, it’s essential to use generative AI tools in HR responsibly. Transparency, fairness and privacy should be the cornerstones of any AI implementation strategy. It’s also crucial to recognize that AI does not make for a “set it and forget it” scenario. Organizations must continually monitor and adjust AI systems to prevent the potential spread of misinformation and the unintended perpetuation of bias.

The future of HR is undeniably intertwined with generative AI. Despite its many benefits, there is still no substitute for the human touch, especially in a field as people-centric as HR.

As we integrate these powerful tools into our HR practices, we must do so with our eyes wide open, keeping in mind that AI should augment human capabilities, not replace them. Maintaining this balance is key to harnessing the promise of AI while avoiding its perils.

 

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to hire the right people, keep them longer and cultivate a successful skills-based organization. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture all in one, data-driven solution. To see retrain.ai in action, book a demo.

What are the steps to become a Skills-Based Organization?

Posted on by Isabelle Bichler

Our previous post discussed the key benefits of transformation into a skills-based organization, including agility, adaptability, talent optimization, employee engagement and DEI support. So how does an enterprise make the shift to an SBO model?

Here are five key steps:

  1. Skills Assessment. An enterprise’s first step is determining which skills are already in its workforce. A comprehensive skills inventory can be built using skills assessment tools, self-assessment questionnaires, and feedback mechanisms to capture the diverse skill sets present within the organization.
  2. Skills Mapping. Next, HR leaders need to identify the critical skills required for each role and project within the organization, mapping the existing employee skills against these requirements to identify skill gaps and potential opportunities for upskilling or reskilling.
  3. Skills Development. To engage employees in the process, enterprises need to create a culture of continuous learning and skill development, offering training programs, mentoring opportunities, and access to relevant resources. HR leaders can then encourage employees to take ownership of their skills development and provide avenues for them to showcase their skills within the organization.
  4. Skills-Based Hiring and Talent Mobility. Transitioning to an SBO model needs buy-in across the board, meaning hiring practices must focus on skills rather than traditional job titles, skills-based assessments and interviews are used to identify best-fit candidates, and employees are empowered to move across teams and projects based on their skill sets and interests.
  5. Technology Enablement. Leveraging Responsible AI-driven HR technologies can facilitate skills tracking, mapping, and matching at scale. Enterprises must invest in tools that allow employees to showcase their skills, create skill-based profiles, and connect with others via an internal talent marketplace.

retrain.ai is a Talent Intelligence Platform designed to help enterprises hire, retain, and develop their workforce, intelligently. Leveraging Responsible AI and the industry’s largest skills taxonomy, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation. retrain.ai fuels Talent Acquisition, Talent Management and Skills Architecture, all in one, data-driven solution. To see it in action, request a demo.