AI in HR: Missing the Forest for the Trees

Serena H. Huang, Ph.D.

As I reflect on the current state of AI in Human Resources, I'm left with a sense of unease. Most of the conversations around AI I’ve heard at events this year center around the automation of simple back-office tasks and cost savings. While there's undoubtedly potential in these areas, this narrow focus overlooks the broader implication of AI for HR. We seem to have lost sight of the grander vision of a future-ready workforce that is empowered by AI to innovate and thrive in a changing world.

There are three big-picture issues that HR can focus on to ensure the company's future readiness:

1. Strategic Workforce Planning

Strategic workforce planning (SWP) is about preparing the organization for future talent needs. It involves understanding the skills required to meet long-term business objectives and ensuring that the workforce is equipped to deliver on these demands. Traditionally, organizations have had to wait for competency models to be built and survey or assess employees to have detailed data on employees for planning purposes. It doesn’t need to be the case anymore with technology advancements. AI can significantly enhance SWP by providing near-real time data on employees’ skills, predicting talent needs, and identifying skill gaps. Once the gaps are identified, AI can even help you create tailored learning programs for each employee, based on their skills and career goals.

Having implemented workforce planning technology in large organizations, I’d suggest having in-house expertise on the topic. While most vendors and implementation partners can provide consulting support, they would not have the business context for your organization. Translating business forecast into headcount needs properly, for instance, will often require deep understanding of how your business operates.

While AI increases the ease of implementing SWP, there is also now an urgent need for organizations to figure out (1) how AI will impact the jobs employees currently hold, and (2) how to prepare the organization to work effectively with AI. A recent LinkedIn study estimates 55% of jobs will be changed, either augmented or disrupted. Your employees are likely wondering what this means for the job security and career progression. It’s critical to start communicating how the leadership is thinking about reskilling and listen to employees during these times of change.

Is your organization ready for AI? According to IMF research, different countries and regions are at a different stages of readiness in leveraging the benefits and managing the risks of AI. One of the first areas many companies trim is in training and development. While I understand times are uncertain, it can be short-sighted for organizations to cut funding, especially when it comes to AI and data literacy training or other emerging skills that will be critical in the future.

2. Responsible and Ethical AI

The second big picture area is to ensure ethical and responsible use, especially where decisions such as hiring and promotion impact people's lives. AI algorithms can perpetuate existing biases if not carefully designed and monitored. Sometimes the discrimination be less subtle.

The US Equal Employment Opportunity Commission (EEOC) settled its first-ever AI discrimination in hiring lawsuit, reaching an agreement with iTutorGroup Inc., which allegedly programmed its recruitment software to automatically reject older applicants. The settlement comes amid the EEOC’s push to target discrimination that can occur when employers rely on AI for hiring and other talent decisions.

What are some practical ways of ensuring the AI systems are developed and deployed responsibly and ethically? I have seen success personally from standing up ethics council that includes a cross functional team of privacy, legal, HR, and IT. Many organizations already have responsible AI principles for how customer data are handled. You can start with those principles and apply them to talent decisions. IBM’s CHRO, Nickle LaMoreaux, shared the following on the Digital HR Leaders podcast with David Green:

“So, the first layer we've done it is for all of our AI, regardless of where it's deployed, internally with clients and products that we build, we adhere to kind of five AI principles: explainability, the AI must never be a black box, it must always be something that you explain how it's working, when it's working, where it's working to the user; fairness, so again, we believe that actually AI can help humans, it can assist humans in making unbiased decisions, but fairness is a very key point of the AI.  The third thing is robustness.  It must be secure.  If it's ingesting data, particularly HR SPI data, we need to make sure the platform, the algorithms themselves are secure.  Transparency, what data is it using; why is it using that data; where in the recommendations?  And then last, privacy, is there certain data that the AI algorithms will not use?  So, those are five principles that we are very clear are principles that every AI solution must uphold. 

The second thing is then, you must, for whatever the use case is, apply certain principles.  So, as an example, in HR, we believe that talent decisions should be made by humans.  That's why we've put in the principle, AI will never be a decisionmaker. “

The potential of AI in HR extends far beyond hiring. Many organizations are in the middle of compensation cycle. Consider this: what if AI can automatically make salary adjustments based on external benchmarking and employee performance data? In one of my recent AI workshops, we had a productive debate about the implications of using AI in compensation practices.

3. Clear Ownership: Who's Driving the AI Train?

Every CEO I’ve talked with in the past six months is asking about how to leverage AI for innovation and growth. We are starting to see Chief AI officers as the hottest job in the C-suite. The adoption of AI has also accelerated. The 2024 McKinsey survey found that AI adoption has jumped from 55% to 72% and genAI usage has increased from 33% to 65% from 2023 to 2024. These numbers are inline with the informal polls I’ve conducted in various conferences this year.

AI adoption for the company requires a clear vision and leadership. Who is ultimately accountable? Having a Chief AI Officer can champion AI adoption, but it’s not a one-person job. It’ll require cross-functional collaboration and joint ownership at the most senior level. There should also be a dedicated council that oversees AI usage across the organization, including any technology and process that impact talent decisions such as hiring, compensation, or promotions.

The HR function has a critical role to enable AI adoption, from attracting and retaining AI talent, to upskilling the enterprise to work effectively with AI, including HR, and preventing harms AI might cause in talent practices.

Some companies have stood up a separate Transformation office or Innovation COE to ensure they can stay ahead in the AI race. These new COEs create excitement and possibilities, but also sometimes confusion for teams that are outside these dedicated groups. I’d advise CHROs to take an active role in ensuring the roles and responsibilities are clear to enable the success of AI adoption and digital transformation.

The Path Forward

AI can transform organizations. HR is at a infliction point and we need to think beyond automation and data analytics. The time to act is now. By focusing on strategic workforce planning, responsible and ethical AI, and clear ownership for AI adoption, HR can become the strategic AI champion the organization needs.

Coming Up Next:

• [SAVE THE DATE] I've partnered with University of Wisconsin Madison on their annual conference and will be the HR track opening keynote speaker on 10/1 as well as the GenAI bootcamp instructor on 9/30. Please consider bringing your team and recommend it to your colleagues! For just $300, you and your colleagues can go from novice to pro on using GenAI.  
• Hello (again) NYC! I'm excited to have found a nonprofit partner and will be hosting a mini retreat in NYC near Central Park to reduce stress and boost resilience & collaboration for teams. This one-of-a-kind experience is ideal for both seasoned managers who are new to a team and first-time managers who want to spend time getting to know their team outside the office setting. If you know of leaders in NYC who care about the wellbeing of their team, please connect us and I can invite them directly! (There is a capacity constraint of 5 teams.)  

ICYMI

I am still pinching myself for making the list of 2024 AI Keynote Speakers to Watch alongside all these fantastic speakers! A big thank you to everyone who has attended my talk or given me the opportunity to share my knowledge over the years.

Do you need listening Materials? Here are some of my recent podcast interviews.

• “Getting Unstuck in Your Data Career with Dr. Serena Huang of Data with Serena“ on Women Lead Data with Lindsay Murphy. Listen on: Spotify, Apple Podcasts.
• “Modern Careers in People Analytics & GenAI Training Classes” on Directionally Correct with Cole Napper & Scott Hines. Listen on: Spotify, Apple Podcasts
• “New to People Data? Here are the First 3 Things Nonprofit Talent Development Leaders Should Do“ on Learning For Good with Heather Burright. Listen on: Spotify, Apple Podcasts
• “Using Data to Create a Better Employee Experience” on Practice Disrupted with Evelyn Lee. Listen on: Spotify, Apple Podcasts.

Dr. Serena Huang is a globally recognized speaker and innovator, renowned for her ability to bridge the gap between data analytics and the human side of business. She brings a unique perspective, having served as a data executive at Fortune 100 companies and later as a Chief Data Officer in a startup environment. Her insights are not just about numbers; they're about understanding the human impact of data and harnessing its power to create a more productive and healthy workplace. A forthcoming author, Dr. Huang is also a regular guest lecturer at top MBA programs, where she shares her passion with the next generation of business leaders.

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