Navigating The Promise And Peril Of Generative AI In HR

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?

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.

What is a Skills-Based Organization?

One of the most significant shifts taking place within the realm of HR and talent management is the transition to a skills-based organization. Rather than focusing solely on job titles and traditional hierarchies, organizations are recognizing the importance of assessing and leveraging employees’ skills and capabilities to better drive success and foster innovation. But what exactly does it mean to transform into a skills-based organization? Why is it seemingly crucial for HR professionals to lead this paradigm shift?

Understanding the Skills-Based Organization

A skills-based organization places skill sets and capabilities at the core of its talent management strategy. Instead of relying on job titles and formal qualifications, enterprises instead shift their focus to identifying, developing, and utilizing the skills their employees possess so as to effectively match individuals to best-fit projects, initiatives, and roles.

What are the benefits of becoming an SBO?

  • Agility and Adaptability. In today’s rapidly changing business environment, enterprises need to be nimble and adaptable. By focusing on skills, companies can quickly respond to market shifts and reconfigure their teams as required. Skills-based organizations have the advantage of assembling cross-functional teams with complementary skill sets, empowering them to tackle new challenges and seize opportunities efficiently.
  • Talent Optimization. Traditional hiring practices often rely on predefined roles, limiting the potential of employees who may possess valuable skills outside their designated functions. A skills-based approach allows organizations to tap into the full potential of their workforce by unlocking hidden talents and engaging individuals to contribute in areas where they excel.
  • Employee Engagement and Growth. Engaged employees are more likely to be motivated, productive, and loyal to their organizations. In a skills-based organization, workers have opportunities to develop and showcase their skills, leading to increased job satisfaction and a sense of fulfillment. By promoting skill development and growth, organizations can foster a culture of continuous learning, which modern professionals highly value.
  • Diversity and Inclusion. Traditional job descriptions can use terminology that inadvertently creates barriers to entry. A skills-based approach promotes inclusivity by focusing on what an individual can do rather than where they come from or what their previous job title might have been. By removing biases associated with traditional hiring practices, enterprises can build diverse and dynamic teams.

In our next post, we’ll go over the key steps involved in transitioning to a Skills-Based Organization.

 

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

HR Evolution in the Age of Talent Intelligence

This article originally appeared in Forbes.

In a year defined by the stark contrast of looming layoffs and a continued skilled worker shortage, it’s likely that 2023 will highlight the importance of HR’s role in leveraging data-driven insights.

At the end of last year, recruiting was a top priority for 46% of HR leaders, with enterprises revamping sourcing strategies to meet the demand. At the same time, 61% of business leaders were predicting layoffs at their companies. None of that slowed the nation’s quit rate, which landed at 4.1 million workers for the month of December 2022, the same time Robert Half’s “Job Optimism Survey” reported that 46% of professionals were looking, or planning to look for, a new job in 2023.

Such contradictory data can make an HR leader’s head spin. Figuring out how to manage it all on budgets tightened by economic instability is the icing on a very bitter cake. The answer?

In 2023, organizations need to be creative and efficient in their approach to achieving HR goals when using data-driven insights.

HR leaders need to synchronize talent acquisition, talent management and organizational skills mapping to create an agile and continuously growing workforce. By acting on AI-fueled, data-driven insights, enterprises can gain a better understanding of their organization’s job and skills architecture and plan for future skills demand—that is, if HR approaches talent intelligence properly.

HR’s Role In Talent Intelligence

Here are some tips for HR leaders on how to approach talent intelligence:

  1. Avoid the DRIP Problem

To compete within the volume, speed and disruption of today’s talent landscape, data is king—but actionable information and knowledge are the castle. Amassing data for data’s sake holds little value and can often lead to a DRIP problem: being data rich, information poor. Conversely, organizing, analyzing and interpreting data can provide rich knowledge and actionable insights needed to fuel better business decisions.

Given the continued talent shortage, expedited skills identification can be a great differentiator for high-performing recruiting teams. To source, screen, hire and retain the right employees with the in-demand skills needed for business success, enterprises should focus on harnessing the true value of data. By actively converting insights into strategies, HR leaders can proactively address skills gaps, plan for future skill needs and develop a more engaged workforce.

  1. Consider starting with job architecture and skills mapping.

To remain competitive and future-proofed, HR innovators should evaluate the skills their employees have, those they need and those that will likely become critical in the future.

More HR leaders are starting with job architecture, building a skills framework using unified skills language to better understand their people and spot hidden talent, diverse capabilities and skills gaps. They can then deploy talent efficiently during times of rapid change, scaling teams up or down as needed. Given the economic uncertainty, knowing where the risks lie can empower HR innovators to upskill, reskill and redeploy—rather than lose—good people.

  1. Don’t fall victim to talent scarcity.

Today’s talent shortage has negatively impacted businesses for well over a year, with more than 77% of CEOs reporting the ability to hire and retain skilled talent as an important factor in achieving growth. Traditional sourcing strategies aren’t enough; HR leaders must be more targeted and efficient than ever to navigate inevitable shifts in the market.

HR leaders can aim to expedite time and labor-intensive tasks—like scanning CVs for skills—so talent acquisition leaders can focus on more complex work. The goal is to find the right people quickly and accurately. In working alongside talent intelligence, HR leaders should focus on skills-based candidate profiling to revive past candidates as additional potential hires.

  1. Focus on internal mobility for talent retention.

Pursuit of the right talent doesn’t end once HR leaders hire people into open roles. Enterprises must proactively “recruit” their employees throughout their tenure via professional growth opportunities. Employees without a clear vision of their future within their organization are statistically more likely to leave.

Career development for today’s workers means learning and evolving within a multidirectional framework, with space to explore open roles, projects, gigs or mentorships, and with access to learning opportunities to reach them. As such, HR innovators can identify hidden talent within their workforce and visualize internal mobility pathways through skills development, increasing the likelihood that their best people will look for their next opportunity within the organization rather than leave to seek out other options.

Learning Curves And Challenges With Talent Intelligence

As HR leaders continue to define their role in the age of talent intelligence, it’s important to note the current limitations, challenges and learning curves associated with the technology.

Regulations And Responsible AI

As AI becomes more embedded in HR processes, so does the responsibility placed on enterprise leaders to manage the potential implications of AI adoption and to implement responsible AI principles. Responsible AI sources and screens applicants based on capabilities, masking demographics or other factors that can introduce unintended bias.

Regulations mandating bias audits, fairness algorithms and explainability to ensure responsible AI compliance are already on the rise. Regulations take shape from municipalities to states and globally, with compliance guidelines being defined in real time. Enterprises must continue tracking these developments to ensure their responsible AI parameters are in place.

HR Tech: What’s Working, What’s Not

Finally, the explosion of new technologies and AI-driven solutions in the HR space has put more data and automation in the hands of enterprises than ever before. HR leaders under pressure to make business decisions that fuel success, and to do so under tightening budget constraints, are taking a closer look at their HR tech stack to determine what’s adding value and what isn’t.

Overlap between HR tech solutions, or inefficiencies within them, represent an unnecessary expense that’s no longer considered the cost of business. Evaluate your tech stack to ensure there are no redundancies.

As 2023 continues to unfold, HR leaders can solidify their role in the age of talent intelligence.

 

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 in one, data-driven solution.

To see it in action, request a demo.

 

Sources:

What Will HR Focus on in 2023? | Gartner | October 2022

When Does Your Salary Become a Threat to Your Job Security? | NASDAQ News | 2023

80% of workers who quit in the ‘great resignation’ have regrets, according to a new survey | CNBC make it | February 2023

Nearly Half of U.S. Workers Plan to Look for a New Position in the New Year | Robert Half | December 2022

 

Event Recap: Responsible HR Forum 2023 presented by retrain.ai

There’s something incredible that happens when thought leaders and knowledge seekers gather to explore a critical topic. Such was the vibe at the first-ever Responsible HR Forum presented by retrain.ai. Below, find a brief overview of the day’s sessions, which you can now access as podcast or vidcast recordings.


Keynote: EEOC Comm
issioner Keith Sonderling

Starting off the day, keynote speaker Commissioner Keith Sonderling of the EEOC shared insights on the expansion of Responsible AI governance across the U.S., emphasizing that current regulations put the onus on businesses using AI systems to ensure they generate fair end results–not on the makers of AI systems.

Watch the vidcast | Listen to the podcast

 

Ready or Not, RegulationAre Coming 

Talk of Responsible AI continued into the first panel discussion, where Commissioner Sonderling was joined by Scott Loughlin of Hogan Lovells, Rob Szyba of Seyfarth Shaw and Niloy Ray of Littler to discuss the new AI Audit Law in New York City, the far-reaching implications of seemingly local regulations, and how the European Union’s approach to AI governance differs from the U.S.

Watch the vidcast | Listen to the podcast


The Paradox of the HR Mission: Creating a Multidimensional View of Talent

In conversation with retrain.ai’s Amy DeCicco, Dr. Anna Tavis of the Human Capital Management Department at New York University and Dr. Yustina Saleh from The Burning Glass Institute posed provocative questions, encouraging attendees to think about questions like whether empathy is truly a skill or a trait, or how HR leaders can tell from a skills profile whether or not a candidate will be able to do the job needed.

Watch the vidcast | Listen to the podcast


Becoming a Skills-Based Organization: More Than a Trend?

With more enterprises talking about transforming to an SBO model, Dr. Sandra Loughlin of EPAM Systems shared lessons learned from her company’s transformation, while Heidi Ramirez-Perloff discussed The Estee Lauder Company’s exploration into SBO strategy. Urmi Majithia of Atlassian delved into executing technology to help overcome the challenges of becoming an SBO, and Ben Eubanks of Lighthouse Research & Advisory broke down the larger SBO concept to a tangible level regarding individual employees and hiring managers.

Watch the vidcast | Listen to the podcast


The Hidden Architecture of a Skills-Based Organization

Following the panel discussion, Dr. Loughlin sat down for a one-on-one with retrain.ai CEO Dr. Shay David to go more in depth into EPAM’s experience developing a thriving SBO strategy, sharing benefits, pitfalls and lessons learned along the way.

Watch the vidcast | Listen to the podcast

 

Can Innovation and Regulation Co-Exist? How ChatGPT Sparked the Conversation

No discussion around Responsible HR would be complete without an exploration of the huge impact ChatGPT and other generative AI solutions are having on the tech space.  Leading a fascinating discussion on the topic were Yuying Chen-Wynn of Wittingly Ventures and Art Kleiner of Kleiner Powell International, who examined the potential of generative AI to greatly improve business systems, as well as the ethical AI use questions that remain in the midst of growing regulation.

Watch the vidcast | Listen to the podcast


Continuing the Conversation: The Responsible HR Council

To conclude the Responsible HR Forum, retrain.ai announced the formation of our Responsible HR Council. Like the Forum, our Council will involve experts from academia, law, enterprise, government and nonprofit sectors. We’ll meet quarterly to get up to speed on new AI legislation, new AI technologies, and the melding of the two within Responsible HR practices. Check back for details soon! 

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, and 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

ChatGPT Is Changing the AI Game, But Enterprises Need More

Chances are you’re one of the millions of people who have played with ChatGPT, the game-changing generative AI assistive technology released by OpenAI. Designed to interact conversationally, the advanced chatbot can engage in dialogue with a user to provide answers, respond to follow-up questions, correct mistakes, and adjust tone and voice when provided with direction. 

A consumer-focused tool, ChatGPT aptly showcases the groundbreaking ability of generative AI to use machine learning to index retrievable content and mimic writing styles. As such, it has prompted a conversation around its possible business uses, garnering opinions from those who see great potential–and those who fear for their jobs. Some even suggest that we are nearing the singularity, or at least seeing for the first time machines that can pass the (in)famous Turing test.

>> Book a demo to see retrain.ai’s generative AI in action

As leaders in the AI space, we see ChatGPT as an example of a set of tools with the potential to transform business processes. Yet it has notable limitations when viewed through the lens of an enterprise-level solution. There are four main areas in which this differentiation is most apparent:

  1. AI-driven technology designed for business incorporates features optimized for a particular industry. retrain.ai, for example, was built from the ground up as a specialized solution for the HR space. As such, our technology expands beyond a ChatGPT-level machine learning model to one which can organize, analyze and structure data precisely enough to inform critical business decisions. We anticipate that in each industry, vertical-specific leaders will emerge who build AI models that are based on industry know-how and language, and are tailored toward specific tasks.
  2. Explainability is another critical feature of specialized AI technologies that you won’t find in a general-purpose chatbot platform. Explainable solutions are referred to as white-box technology, meaning machine learning outcomes, and the methodology which produces them, can be explained using general business-speak. For enterprises trusting generative AI systems with critical decision assistance, this means they have a clear enough understanding to question or challenge the platform’s output. 
  3. Without white-box explainability, an AI system is lacking a key component of Responsible AI, a non-negotiable design element, when it comes to bias prevention in hiring processes. Only by using Responsible AI can an enterprise ensure candidates are being screened solely on skills, eliminating information that can introduce unintended bias. Increasing regulations will also hold enterprises accountable for making sure they are using Responsible AI in hiring practices.
  4. Enterprise-level solutions are implemented to directly impact business performance. They come with contractual assurances like Service Level Agreements (SLAs) to outline vendor expectations and set metrics by which the technology’s effectiveness will be measured. Open platforms like ChatGPT don’t offer performance metrics or customized services, leaving adopters with no recourse should something go wrong. The same is true about data sovereignty, and compliance with privacy standards like GDPR. We anticipate that the big vendors like Microsoft and Google will soon offer enterprise grade service assurances around consumer tools like ChatGPT (or Google’s Lambda), but until that time, the use of consumer tools cannot be relied upon.

The retrain.ai Talent Intelligence Platform uses generative AI with similar language processing technology to ChatGPT’s, but expands on the model to provide a fully explainable enterprise-level solution designed specifically for talent intelligence, while complying with SOC2, GDRP, and offering enterprise grade SLA. We’re excited to see how the market continues to develop and how enterprises transform years old practices with new tools. 

>> Book a demo to see retrain.ai’s generative AI in action

See how the retrain.ai Talent Intelligence Platform fuels your talent acquisition, talent management, job architecture and DEI goals, contact us today. 

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 architecture, enterprises unlock talent insights and optimize their workforce effectively to lower attrition, win the war for talent and the great resignation in one, data-driven solution.

Learn more: book a demo

What if we could navigate careers like we navigate traffic?

This article was written and originally published by Medium.

After 100+ years of hiring with a mass production mindset, it’s time to apply personalization to managing the workforce.

Continue reading “What if we could navigate careers like we navigate traffic?”