Leadership Insights Series: Cutting Through the AI Noise in HR – A Conversation with Jaison Williams
A veteran talent and culture executive on why most HR organizations are further behind on AI than they think, and how focused leaders can start making real progress.
Jaison Williams has spent more than 20 years bridging business goals and human capability, with leadership roles at Fortune 500 companies including Warner Bros. Discovery, Expedia Group, Google/Fitbit, and GSK. As EVP of Talent & Culture at Warner Bros. Discovery and SVP of Talent Management, Capabilities & Culture at Expedia Group, he helped pioneer AI-powered, skills-based approaches to the talent lifecycle well before most organizations knew where to start. Today, as a strategic advisor, he guides organizations modernizing their workforce, talent, and culture models for the AI era. He recently sat down with Beth Ann Namey, Partner in our Technology/Digital practice, for a candid conversation about where organizations really stand, and what it takes to cut through the noise.
AI is everywhere, but strategy is not
Ask Williams where most HR organizations are in their AI journey, and his answer is direct: disjointed and ad hoc. Platforms have AI embedded in them. Teams have Copilot, ChatGPT, or Claude as productivity tools. Individuals are building an agent or two to offload parts of their work. What is missing is the ability to rewire practices and processes at a holistic level, with a centralized strategy that the entire people function executes against.
He is careful not to frame this as failure. The pace of change is relentless, with model updates arriving what feels like multiple times a week. But that pressure is exactly why he believes now is the moment to pause and get intentional.
“Right now is actually the time to start thinking about how we develop a cohesive, ROI-driven AI roadmap.”
The misconceptions holding leaders back
Williams sees two blind spots repeated across organizations. The first is a blanket assumption that everyone understands AI equally well and has the same level of skill with it. They do not, any more than everyone has the same skill with Excel or the same aptitude for managing people. Leveling up an organization is hard when its people are starting from very different places.
The second is underestimating how much rework and redesign lies ahead. Organizational design, operating model design, and workflow re-architecture were levers most companies rarely pulled, and few teams kept that muscle strong. Now those capabilities are suddenly strategic. Williams notes that transformation offices, which had largely gone out of style, are returning as AI transformation centers, because the reality and the hype are two different things and closing the gap requires a collaborative, integrated approach.
He also stresses that HR cannot go it alone. The people function sits within a broader ecosystem alongside finance, legal, and IT, and the biggest question of all sits above every function: what is our timeline for moving from a human-led workforce to one that is human and AI-driven? That question starts in the C-suite, but the answer has to reach everyday practices and processes.
First steps: do not boil the ocean
For leaders ready to act, Williams starts with what not to do. The noise says change your whole organization. The signal says pick two or three problems worth solving, or opportunities worth pursuing, and go after them with intention. Focus keeps the effort collaborative rather than disruptive.
From there, his advice gets contrarian. Instead of starting with the technology, start with the work.
“You need to do a bit of backward thinking before you can go forward. If you stay in a tech-forward mindset, you are looking at what the technology can do instead of asking what intelligence is best suited for doing this work.”
That question, which intelligence is right for each step of a workflow, requires journey mapping, because the answer can change along the way. It also requires a cross-functional team, since work rarely lives in any single function. Williams recommends that those teams include what researchers at Carnegie Mellon University have called an “AI handler”: someone fluent in workflow design, governance, and risk mitigation who can guide the group so that not everyone needs to be an AI expert. Every organization has people who are heads and shoulders above the rest on AI skills. This is how to use them.
A five-stage journey map
Williams has codified his proven approach into a five-stage AI transformation journey map :
- Discover. Assess AI readiness, identify the highest-value problems to solve, and take an honest look at what the workforce can absorb.
- Build. Assemble a cross-functional squad to design the initial human-and-AI solution, working in sprints.
- Pilot. The same team tests the result against reality, uncovering the scenarios no plan accounts for.
- Scale. Lessons learned from the pilot carry into the broader rollout.
- Optimize. The solution goes into practice, but refinement never ends as technology continues to evolve.
Change management at a new tempo
Traditional change management had the luxury of time: plan, align, socialize, present, then go. Williams argues that those steps must now happen simultaneously, which is why he draws on product management and agile principles. Leaders owe their organizations vision and transparency: naming the three areas where the work starts, encouraging everyone else to continue experimenting, and updating the organization as things unfold. The people working those focus areas become de facto change agents, because unlike traditional change programs, this model puts the experts who live and breathe the work directly inside the effort.
He also borrows the product manager’s habit of designing for personas. Getting specific about exactly who a solution serves gives a team far more direction than naming a department, and he is unapologetic about resetting the pace. This is a move-fast-and-break-things moment, he argues, provided the breaking comes with accountability: if something breaks, figure out why and fix it. The goal is bias toward action, learning, and the next step.
There is a cultural payoff too. The constant drumbeat of AI headlines makes every organization feel ten steps behind. Picking up the tempo, even modestly, makes progress visible and keeps everyone moving on the same train together.
Creating space for transformation
When asked how leaders can create space for this work when teams are already at capacity, Williams starts with subtraction. During his time at Expedia Group, quarterly business reviews were followed by deliberate decisions about which work did not align to priorities and should be stopped. HR, he notes, is culturally quick to answer every request that comes its way, and learning to politely decline is itself a capacity strategy.
The second lever is reallocation. As AI absorbs rote tasks, the time saved must be pivoted toward higher-value work, and that often takes an explicit conversation about what higher value means. His example: a talent acquisition coordinator freed from operational tasks might instead call candidates back directly, adding human connection exactly where hard-to-close searches need it most. Wherever you want more human interaction than machine interaction, reclaimed time should go.
Measuring what the business measures
When HR leaders struggle to demonstrate impact, Williams suggests setting aside HR measures of success in favor of business measures that can be tracked and quantified. A strong people analytics function can point to the right areas to measure. Without one, leaders can still run a self-assessment: where does our function drive differentiated value for the organization, what would good look like, and how do we do more of it?
The bigger shifts ahead
Looking further out, Williams sees three areas of work that will define the next chapter. The first is redesigning work itself: deconstructing jobs and processes so work can be redeployed, and rethinking org structures, perhaps moving from the traditional pyramid to a diamond shape with AI at the core and people surrounding it. Leaders often assume this work belongs to a consulting firm. Williams disagrees.
“You know your business better than anyone; it is a matter of asking different questions.”
The second is culture. As employee value propositions evolve, he urges leaders to ask whether today’s culture will still be fit for purpose even 24 months from now, noting Gartner data that shows global employee engagement continues to decline.
The third, and perhaps the most overdue, is the role of the manager.
“We are no longer operating just with software as a service, which runs in routine. Now we are using dynamic systems, and that is very different. It is a different mindset. It is a different approach.”
Williams argues that managing people and managing AI agents require different skills, and not every manager will be equipped for both. Yet managers are increasingly expected to lead AI implementation where the work happens: at the team level. After years of adding more to the manager role, organizations now need to rethink it intentionally, potentially separating responsibility for managing people from responsibility for managing agents.
He flags one more emerging frontier: validating the credentials of the workforce. He points to the recent case of a former Air Canada captain charged with flying more than 900 flights over nearly 17 years without the required license. With AI expected to drive a further uptick in workforce fraud, from falsified backgrounds to lapsed professional licenses, he anticipates a new category of platforms focused on verifying that the nurse, the doctor, the lawyer, or the pilot is exactly who and what they claim to be.
One piece of advice
Asked what single piece of advice he would give leaders trying to cut through the noise and make real progress, Williams does not hesitate.
“Claim one area that you are going to make sure, with the help of AI, you knock out of the box. You are not going to knock five out of the box. But if you focus, you can get one, and that may lead to two.”
Leadership Insights is a series by Buffkin / Baker that profiles exceptional leaders across industries. To nominate a leader for a future interview or to speak with our team about a senior executive search, we’d love to hear from you.
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