Leaders built their careers on having the answers. That foundation is cracking, and Nicole Gams, Vice President of Talent, Learning and Leadership for the Central Region at BTS, spent a recent episode of Brandon Hall Group’s Excellence at Work Podcast explaining why and what leaders should do about it. Rachel Cooke, COO of Brandon Hall Group™, hosted the conversation, pulling from her own experience running teams through the same shift.
Gams brings a wide lens to the problem. She has built leadership capability across technology, retail, fast-moving consumer goods and biopharmaceuticals. Gams started in television before joining BTS, a global consultancy that equips people with the skills, mindsets and behaviors to lead, sell and perform when it counts. BTS, a Gold-level Brandon Hall Group™ Smartchoice Preferred Provider, partners with senior leaders and teams to accelerate performance and drive transformation from the C-suite to the frontline.
Knowledge Stopped Being the Prize
AI broke the old scoreboard. For decades, leaders earned credibility by knowing more than everyone else in the room. Gams argues that knowledge and expertise, once the sharpest differentiator a leader could have, are becoming commoditized because AI now puts that same information within reach of anyone at any level. The advantage hasn’t disappeared. It has moved. Leaders who once won by having the answer now need to win by doing something AI can’t: exercising judgment about which answer actually fits the moment.
She Gave Up the Skill She Worked Hardest to Build
Gams offers herself as proof of how disorienting this shift can feel, even for someone who studies it professionally. She spent years mastering the art of structured communication, building tightly reasoned PowerPoint decks and bringing in outside experts to sharpen the craft. Then AI rewired her toolkit. She rarely opens PowerPoint anymore. She builds interactive HTML instead, letting AI handle the construction while she focuses on the argument. The theory she spent years learning still holds up. The medium she poured that theory into does not, and losing it stung more than she expected. She still asks herself daily what to keep and what to release.
Cooke sees the same pattern playing out across companies that extend reskilling programs to senior leadership instead of stopping at entry and mid-level staff. Expertise doesn’t need to go out the window. Habits do, and habits take real time to rebuild because they’re tangled up with judgment and identity, not just process.
Hold the Why. Release the How.
Gams draws the line sharply: judgment, discernment and the reasoning behind a decision belong to the leader and always will. Execution is fair game for reinvention. She even pushes back on her own choice of words, arguing that “letting go” undersells what’s happening. The work isn’t being abandoned. It’s being challenged, rebuilt and reimagined by people willing to question how it has always been done.
Cooke tests that idea against her own calendar. Ahead of a recent offsite for 16 team members, she wrestled with how much of the day should come from her agenda and how much space she should leave for the room to shape it themselves. She also pushes back on the idea that AI created some brand-new flood of information. Leaders have always had encyclopedias, libraries and search engines. What changed is speed and volume, which means leaders now have to build real discipline around vetting sources, the same instinct that once sent people digging through a library’s card catalog to trace where an idea came from.
Automation Can Feel Like Loss, So Treat It Like One
When a leader’s core skill gets automated, Gams doesn’t rush past the discomfort. She names it first. Something real may be gone, whether that’s a task someone loved or a colleague they worked closely with, and she gives people room to grieve it rather than pretending the transition is purely exciting. Only after that does she start asking forward-looking questions: what worries them about what’s next, what they love about how they work, what impact they still want to make. That combination lets people figure out what to carry forward and where to reinvent themselves, and it gives them a genuine sense that they still belong in the organization’s future. Skip the grief and jump straight to reinvention, she warns, and people won’t buy in.
The Investment Everyone Is Skipping
Rachel brings up the question of where organizations are wasting their AI budgets and Gams doesn’t point to tools. She points to systems. Companies keep pouring money into individual AI capabilities without touching the workflows those capabilities sit inside, so the investment never scales into results. Real progress means redesigning who owns a process, who holds decision rights and what actually gets rewarded, not just handing employees a new piece of software. Brandon Hall Group’s operating model exists for exactly this reason, giving organizations a framework to evaluate their own readiness instead of guessing at it.
Confidence Isn’t Judgment
AI has made it harder to see how a decision actually got made. A call that once came from a room full of people debating options might now come from one person and a chatbot. Gams says the test hasn’t changed even though the process has: ask why, and you’ll find out fast whether someone actually validated their thinking or just accepted the first plausible answer. Cooke pushes the point further, arguing that what someone fed into the AI matters as much as what came out of it. Using AI is quickly becoming table stakes rather than a red flag, but that only raises the bar on how carefully leaders vet what it gives them.
Two Kinds of Honesty
Gams identifies two distinct forms of vulnerability leaders need right now. First, admit what you don’t understand about AI itself. Anyone claiming full expertise in a technology this new is, in her view, really just avoiding an uncomfortable truth, and admitting “I don’t know” is what actually opens the door to experimentation. Second, and harder, admit that nobody knows how AI will reshape jobs, careers or entire roles. Leaders can’t promise safety they don’t control, and pretending otherwise trades short-term comfort for long-term trust. Cooke agrees, adding that job security has never been guaranteed in any industry and that when executives visibly share their own fears and excitement about AI, that honesty cascades down and shapes how the rest of the organization handles the same uncertainty.
Celebrate the Right Things, Not Everything
Speed pressure hasn’t gone away, but Gams reframes what speed should mean: learning fast, not just moving fast. She wants celebration to work as a leading indicator tied to strategic learning goals rather than a trophy handed out after the fact for results alone. Celebrate everything and the gesture loses its power, so organizations need to decide deliberately what behavior they actually want more of, whether that’s early AI adoption or a specific capability the strategy depends on. Cooke compares the risk to a youth sports league that gives every player the same trophy. It feels generous, but it dilutes the very recognition it’s trying to create.
What Won’t Get Automated
Gams reflects on the next two years, an almost impossible ask given how fast the ground keeps shifting, Gams names the capabilities she still expects to matter: strategic thinking, creative thinking, emotional connection, trust and the ability to navigate a system’s messier dynamics. But one capability stands above the rest for her: the ability to actually rebuild how work gets done, not just describe how it should change. That means restructuring teams, redesigning meetings and figuring out how humans and AI agents work side by side, then following through on it. Cooke closes the conversation with three habits she watches for in organizations that are getting this right. They model learning. They build systems that support adoption. They measure what matters.
