Pre-flections on GenAI and HR: Where to Go and How to Get There

GenAI has become one of the most rapidly adopted technology innovations ever as many have used ChatGPT to write lyrics, create songs, compose images, explore questions, or draft documents. But GenAI is more than a hobby or parlor game; the information provided through GenAI will transform the entertainment, fashion, travel, education, health, energy, and professional services industries. Estimates are that GenAI will impact nearly 50 percent of working hours and create $10 trillion in economic value by 2038. For example, on only one day (February 22, 2024), the stock of Nvidia, a chipmaker firm powering AI, jumped a record 16 percent ($273 billion).

In the “HR” space, every conference, webinar, magazine, and podcast highlights GenAI as a dominant agenda item that will shape how to manage people and organization.

In a recent conference with senior academic and industry HR thought leaders, I asked them how far up the “S-curve” of GenAI for HR we are today. Their answer was in the 15–25 percent range, with a lot of variance (and uncertainty) about what to think and do today and an acknowledgement of a steep learning curve ahead (see figure 1).

Moving up this S-curve will reduce variance in how to think about and use GenAI for HR. While the aspiration at the top of this GenAI/HR S-curve may not yet be totally defined, let me suggest six “pre-flections” that characterize how the use of GenAI in HR might evolve from primarily a way to optimize information to more augmented or informed intelligence that leads to guidance (see figure 2).

Let me further suggest five specific actions (more will obviously be added) to make progress along this learning curve to more fully utilize GenAI in HR to offer guidance.

1.   Appreciate the value of GenAI-enabled information.

Information advantage comes from asymmetry—or when an individual or organization acquires, analyzes, and applies information better and faster than others (thanks to Wayne Brockbank for this insight). Information advantage has been relevant to organizations for some time. Jay Galbraith, the primary thought leader of organization design, said in 1973, “Information processing is the key concept concerning the theory of organization. The greater the task uncertainty, the greater the amount of information that must be processed among decision makers during task execution in order to achieve a given level of performance.” In today’s increasingly uncertain world, information asymmetry continues to differentiate successful individuals, leaders, and organizations. GenAI boosts exponentially the ability to access, analyze and apply information for personal and organizational advantage.

HR professionals can demonstrate GenAI as a means to perform advanced analytics that emphasizes the importance of information.

2.  Use GenAI to better optimize current HR practices.

We see numerous examples of GenAI quickly sharing what can be and has been done in many HR areas (see figure 3). GenAI democratizes unlimited historical information into shared patterns since anyone who runs a similar prompt will have quick access to what has been done.

HR professionals can use GenAI to report symmetrical or shared information about legacy benchmarks and best practices.

3.  Classify GenAI-enabled HR practices into a human capability taxonomy.

We have shared the importance of creating an integrated framework to organize and categorize the myriad of HR initiatives to standardize, simplify, and improve decisions; cumulate insights; and improve reports. The ability of GenAI to classify optimized individual HR practices becomes even more important to evolve up the S-curve towards guidance. Instead of improving isolated HR practices, they fit into the human capability framework with four domains: talent + leadership + organization + HR. Figure 3 highlights many HR-enabled initiatives from GenAI in each of the four domains based on remarkable reports from a few leading firms (Accenture, BCG, Conference Board, Deloitte, Gartner, KPMG, McKinsey, Mercer, and PWC).   In these examples, GenAI optimizes information to improve the current practices (column 1 of figure 2).

Figure 3 illustrates how HR professionals can begin to cumulate GenAI HR insights into an integrated framework to make progress.

4. Recognize new information asymmetries.

Moving up the S-curve, GenAI for HR will be able to create information asymmetry beyond optimizing and reporting legacy and shared best practices to offering guidance to personalize which practices deliver results that matter to stakeholders. Guidance comes from first identifying desired stakeholder outcomes (e.g., employee productivity, strategic revitalization, customer share, investor confidence, or community reputation) and then using GenAI to optimize and prioritize which human capability initiatives best deliver these outcomes.

Today, a number of knowledge reservoirs are being created with thought leadership ideas (figure 4). People can access these resource pools to ask a question they are interested in that will lead to actionable insights (blue in figure 4). In the future, a GenAI diagnostic can be applied to identify where the individual or organization can best improve to meet their goal. Then the general actionable insights become tailored guidance (yellow in figure 4). 

HR professionals can use GenAI to diagnose where to prioritize opportunities on what adds the most value to provide tailored guidance.

5. Manage the logistics and risks of GenAI for HR.

The journey to using GenAI in HR for guidance will have many logistics and risk tasks, including but not limited to:

• Who should champion, sponsor, participate in, and be accountable for this journey?
• What individual skills and organization capabilities will be required to make GenAI in HR happen?
• What will be the regulatory and legal policies and risks associated with the effort?
• What metrics of value-added GenAI for HR will be most useful and tracked?

Many thoughtful colleagues have and will continue to address these important issues.

HR professionals can ensue that the logistics, risks, and processes for GenAI in HR occur with proficiency.

Not the Conclusion

My pre-flections in this post are to envision the journey ahead for applying GenAI to HR work, and to offer some possible actions to continue progress.

GenAI will help shape HR’s future by offering both information symmetry to synthesize and optimize the past and present and information asymmetry to create and guide the future.

On June 18 and 19, the RBL Institute will hold a two-day in-person think tank in Miami, Florida (USA), to turn these pre-flections into actions. If you are interested in participating and learning more about the Institute, contact Joe Grochowski , Managing Director of the Institute jgrochowski@rbl.net.

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Dave Ulrich is the Rensis Likert Professor at the Ross School of Business, University of Michigan, and a partner at The RBL Group, a consulting firm focused on helping organizations and leaders deliver value.