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AI in HR: Creating Value With New Technology

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As artificial intelligence becomes more deeply embedded in everyday workflows, it is rapidly transforming the way businesses operate. For example, the recent rise of generative AI and data-driven insights provide an exciting glimpse into future possibilities. In fact, McKinsey estimates that AI could contribute an additional $13 trillion to the global economy by 2030. But what does this mean for AI in HR?

Many employers are eagerly embracing new AI-driven capabilities. And as the co-founder of an innovative HR tech platform, I’ve had a front-row seat in witnessing AI’s early impact.

But despite the enthusiasm, a central question remains: While navigating these uncharted waters, how can employers make sure AI has a meaningful, positive impact on their workforce as well as their business results? Here’s my perspective…

Moving From Hype to Measurable Value

In the HR tech sphere, many tools and service providers are racing to integrate AI into their platforms and processes — often to demonstrate tech prowess. But this, alone, doesn’t create business value.

That’s why problem-solving must be a top priority. Especially now, in this early adoption phase, it’s paramount for solutions to address the real needs of HR leaders, practitioners, managers, and employees.

If this is the goal, what truly matters? AI isn’t just about automation — it’s also about helping organizations save time, improve performance, enhance the employee experience, and provide actionable insights when and where they’re useful. In our world, this translates into feedback processes that are more responsive, managers who are more effective at coaching their teams, and employees who are more engaged and empowered to grow and perform their best.

Mapping AI to Employment Cycle Stages

To understand the tangible benefits of AI in HR, it’s helpful to look through the lens of the employee lifecycle. From talent acquisition to performance management, and from training to retention, AI is shaping each step in the employee journey. Let’s examine what that means for each stage:

1. Rethinking Talent Acquisition: Beyond the Resume

As the initial touchpoint in the employment cycle, hiring is pivotal in defining the employee experience. Traditional recruiting methods may be effective, but they often fall short in capturing the intricate nuances that determine a candidate’s fit for a particular role. This is where the transformative power of AI can propel employers beyond the limits of a conventional resume.

An excellent case is HireVue. This platform uses AI-driven predictive analytics to evaluate a candidate’s suitability based on numerous factors, including facial expressions and tone of voice during interviews. These innovative capabilities work hand-in-hand with recruiters to complement and enhance their human observations. This leads to a more comprehensive assessment that looks beyond surface-level qualifications and reduces unconscious bias.

How AI Adds Value

In a world where first impressions and gut feelings tend to drive decisions, AI adds a more objective layer of analysis. Plus, it helps “read between the lines” of a candidate’s responses for a more holistic, data-driven approach to talent acquisition.

As a result, employers can feel more confident they’re hiring people with personal attributes that fit their company culture and long-term objectives, as well as the right skills and experience.

But the true magic of AI lies in its potential to help decision-makers rethink their perceptions of candidates. Suitability indicators shift from qualifications, alone, to a nuanced combination of skills, culture fit, and long-term potential.

Ultimately, this promises to improve employee satisfaction, engagement, and retention by making it easier to find the strongest talent for each role, right from the start. However, AI can’t run on autopilot. For the best outcomes, employers and platform vendors will need to work together so they can avoid bias in AI algorithms while preserving the human touch that elevates the candidate experience.

2. Redefining Performance Metrics: Objective Evaluation

Performance assessment has long been a foundational HR function. But now, AI adds a new dimension to this process, reshaping how we track and evaluate employee contributions.

With AI algorithms, employers can extract insights that were once beyond reach. This means organizations can more quickly and accurately pinpoint high-potential talent, predict employee burnout, create a comprehensive analysis of any individual’s performance, and identify where they’re making the biggest impact.

How AI Adds Value

To illustrate how this works, consider the case of Fractl, a fast-paced digital marketing firm that relies on the WorkStory platform to drive employee pulse surveys, streamline performance reviews, and support continuous development for its fully distributed workforce.

What’s next? According to MIT Sloan, some organizations are taking this a step further by using AI to generate employee key performance indicators. These KPIs are carefully calibrated and dynamically adjusted to consider each employee’s past performance, while also considering their team’s objectives and their organization’s broader mission.

Although momentum is growing for AI-supported employee evaluation, several fundamental challenges remain. Employers need to foster workforce trust by ensuring their process is transparent and free from bias. As success stories become more widespread and best practices emerge, these barriers to adoption should diminish.

The shift to AI-enabled performance evaluation marks a pivotal moment in the evolution of HR practices. By providing more objective, dynamic, data-driven assessments, it’s possible to unlock new levels of employee potential and improve productivity, while significantly enhancing employee engagement and retention.

3. Empowering Growth: Tailored Learning Experiences

Continuous learning is vital in today’s fluid business environment. And AI is already transforming employee development from a formal one-size-fits-all experience to a personalized and highly adaptive journey.

For instance, imagine tailoring training modules and performance support resources to an individual’s organizational role, career aspirations, and learning patterns. With AI-enabled tools like Degreed, Coursera, EdCast, Docebo, and Cornerstone OnDemand, you can easily identify relevant skill gaps and deliver targeted learning, assessments, and coaching.

How AI Adds Value

These AI-powered platforms curate personalized learning paths, recommend relevant courses, and analyze individual learning behaviors, so employees can develop the knowledge and skills they need to thrive in their current roles. At the same time, they can prepare for future opportunities.

Organizations are rapidly embracing AI-based learning strategies because they see tremendous value in helping employees take charge of their professional growth while remaining aligned with existing business goals.

4. Fostering Retention: Finding the Pulse of Employee Engagement

Employee engagement is the lifeblood of every organization. With AI-based analytics tools, employers can gain deeper insight into subtle engagement indicators. By analyzing informal and formal feedback and communication patterns, organizations can better understand the strength and direction of workforce sentiment and proactively work to improve engagement.

How AI Adds Value

Organizations like KPMG are using an internal AI chatbot and predictive analytics to identify employees who are at risk of quitting, so they can intervene. And in 10-20% of cases, these interventions succeeded.

In this context, predictive analytics depends on historical data and AI algorithms to forecast future outcomes. For employee engagement, it can mean predicting which employees are more likely to leave based on their interactions, sentiments, and previous work patterns.

When the system identifies “at risk” employees, HR can take timely action to address underlying issues. For example, to resolve conflicts with a manager, a disaffected employee may respond to job restructuring, reassignment, coaching, or new development opportunities.

This proactive, personalized approach contrasts with traditional talent management methods that rely on periodic pulse surveys and subjective assessments, both of which may miss real-time fluctuations in employee sentiment.

Fusing AI and HR: Beyond Today’s Challenges

Integrating AI with HR is a journey filled with endless possibilities. But despite the benefits and buzz, HR professionals need to recognize the risks and ensure AI tools are used ethically and effectively.

This isn’t just about efficiency. It’s also about building a workplace that is more empathetic, empowered, and engaged.

In a few short years, AI-enabled HR tools will be ubiquitous. The burden of routine, repetitive tasks will fall more heavily on machines. At the same time, information will flow much more freely, giving business and HR professionals the ability to better understand their work environment, anticipate the need to adjust, and prepare for the road ahead.

As Harvard Business Review says, “These new capabilities remove barriers of expertise and time from the process of data preparation, insight discovery, and analysis and make it possible for ‘citizen data analysts’ to create insights and take actions that improve their businesses.”

We will learn and adapt. New jobs and industries will emerge that we haven’t even anticipated yet. In fact, The Institute for the Future predicts that most of the jobs that will exist in 2030 haven’t been invented yet — and many of those jobs will be created as a result of AI.

As employers move toward a world where AI is seamlessly integrated into HR processes, I think one guiding principle will determine the difference between failure and lasting success. When you’re trying to balance tech innovation with the human touch, ask yourself, “Will this truly help members of our workforce feel more connected, valued, and supported in their professional journey?” If so, you’re on the right track.

Transforming Talent Decisions With Ethical AI

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Sponsored by Reejig

Countless HR tools, applications, and platforms now rely on artificial intelligence in some form. Users may not even notice that AI is operating in the background — but it can fundamentally change the way we work, think, and make talent decisions.

This raises several big questions. What should we really expect from AI? And is this kind of innovation moving us in the right direction?

For example, what role should AI play in skills-related talent acquisition and workforce mobility practices? With stellar talent in short supply these days, this topic has never been more important for employers to consider. So join me as I look closer at key issues surrounding ethical AI in HR tech on this #WorkTrends podcast episode.

Meet Our Guest:  Jonathan Reyes

Today, I’m excited to talk with Jonathan Reyes, a talent advisor and futurist who has been helping technology and banking industry companies navigate hypergrowth for nearly two decades. Now, as VP of North America for Reejig, he’s on a mission to build a world with zero wasted human potential.

Defining “Zero Waste” in Humans

Jonathan, I love the phrase “zero wasted potential.” What exactly does Reejig mean by this?

We envision a world where every person has access to meaningful work — no matter their background or circumstance. In this world, employers can tap into the right skills for the right roles, whenever needed. And at the same time, society can reap the benefits of access to diverse ideas through fair and equitable work opportunity.

The concept of sustainability is emerging in every industry. Now, sustainable human capital is becoming part of that conversation, and this is our way of expressing it.

So, with zero wasted potential, decisions aren’t based on a zero-sum game. When employers make human capital choices, individuals or society shouldn’t suffer. Instead, by focusing on talent mobility through upskilling and reskilling, we can create a new currency of work.

Workforce Intelligence Makes a Difference

Why do you feel workforce intelligence is essential for employers as they make talent decisions?

Organizations have so much human capital data. With all the workforce intelligence available, there’s no reason to hire and fire talent en masse — and then rehire many of the same individuals just months later.

Obviously, that’s an emotional and human experience for employees. But also, organizations are spending unnecessary money to find people and let them go, only to invest again in rehiring them.

Focusing instead on internal mobility is far more cost-effective.

Where Ethical AI Fits In

Many companies are unsure about AI in talent acquisition and management. What’s your take on this?

There are no universally accepted standards for ethical AI. This means vendors across industries can say technology is “ethical” based on self-assessment, without input from legal, ethical, or global experts.

But we’ve developed the world’s first independently audited, ethical talent AI. In fact, the World Economic Forum has recognized us for setting a benchmark in ethical AI.

The Impact on Internal Mobility

How do businesses benefit from shifting to a zero-wasted potential talent strategy? 

When companies manage internal mobility well, they extend employee tenure by 2x. And we know that people who stay and continue growing and developing are much more engaged.

This can create a significant downstream benefit. It’s one of the biggest reasons to invest in this kind of talent management capability.

 

For more great advice from Jonathan about why and how organizations are leveraging AI to make better talent decisions, listen to this full episode. Also, be sure to subscribe to the #WorkTrends Podcast on Apple Podcasts or Stitcher. And to continue this conversation on social media, follow our #WorkTrends hashtag on Twitter, LinkedIn, and Instagram.

Using Ethical AI Technology to Champion DE&I Efforts

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Anyone can launch a DEI initiative. The big challenge is to succeed.

What’s the biggest roadblock? Human unconscious biases.

Psychologists have shown over and over in research studies that our biases are ingrained and automatic. Even if we think we’re champions of equality, the associations are likely still there. For example, studies show that it’s not just men that associate being male with being smart. Women do it too.

Why do we have unconscious biases? And why is it so hard to shake them?

Biases are shortcuts. They are quick ways to make choices. That doesn’t make them good ways to make choices. They just help us navigate our world quickly in a way that feels good. These biases become particularly prominent in situations where we have to make a high volume of decisions quickly. There is simply no time to be thoughtful in these cases.

In the world of HR, the steady stream of resumes and constant pressure to hire is the perfect setup for unconscious biases to have free reign. Recruiters hire candidates that feel like the “right fit” and base these choices on biases. There is really no other way for the human brain to process that volume of information in a more effective or objective manner.

So how do we move towards hiring equity and remove these biases? Embrace AI technology.

Using AI technology in HR can be off-putting for two reasons:

  1. Some feel concerned about the “ick factor” of having not enough humanity in the HR process. In other words, who are machines to tell us how to hire?
  2. Others feel concerned about having the worst of humanity hard-wired into the HR process. They wonder: What if the technology learns our bad choices and implements them more broadly?

In either case, the AI technology underpinning any HR solution must stay ethical. In the HR space, there are many AI solutions. But not all of them are created equal. To ensure the technology you’re selecting is part of the solution and not an unethical part of the problem, you must be an active consumer of these technologies.

How to find the ethical AI technology for your team

To keep AI tech providers honest and their solutions ethical, you’ll need to avoid the following common pitfalls:

  • Baked-in biases: Unethical AI can embed inequity into the HR system itself. Make sure you are not codifying biases in hiring and making them more pervasive.
    • How to avoid them: Start with good, bias-free data. Be choosy with the data that your AI learns on. Bad data is worse than no data.
  • One-size-fits-all approaches: Unethical AI tries to be the universal solution for everything. AI doesn’t work well when its expertise is spread too thin.
    • How to avoid them: Narrow your AI’s focus. AI is at its most powerful when targeted to a specific space like human resources. This keeps AI-driven answers fast and accurate.
  • “Black box” systems: Unethical AI lacks transparency and may have unclear or opaque scientific methodology and/or output. This can lead to legal defensibility issues.
    • How to avoid them: Create a feedback loop where the humans that make up your HR team and the AI tech they rely on can learn from each other. Make sure you understand both the science behind the technology and its output.

How to partner with AI technology

We shouldn’t be using AI tech to replace humans, but to augment them. AI can radically alter how work gets done and who does it. It can help humans amplify their strengths, extend their capabilities, and free up their time.

But humans also need to do their part to support AI in return. They need to:

  • Help AI train to perform its tasks
  • Be able to explain these tasks to relevant stakeholders (which sometimes includes the AI itself)
  • Have a level of oversight to make sure these tasks are being completed responsibly

Creating a collaborative process where AI plays an objective gatekeeper role that is focused and transparent will help HR personnel feel confident adding ethical AI to their processes. It will also reassure HR professionals that the humanity of Human Resources will remain intact and can even be enhanced by incorporating AI. When AI and humans stay in the lanes that they excel in, everybody wins. AI gets to do what it does best, and so do humans.

Make sure to keep the lines of communication open between your AI technology and your human team. When AI and humans learn from each other, the people that you hire will feel the difference. And you’ll be confident you’ve hired the best person for the job–bias-free.