Future of Work
I host a podcast, “Navigate Change. Amplify Potential.,” and I’m a contributing writer for Highlight Georgia. Both give me the chance to talk with a lot of leaders across a lot of industries. This week, I sat down with three of them. Dr. Vicki Wright Hamilton, MBA came on the podcast still lit up from decades of climbing her way through the C-suite, helping people see the leader they couldn’t see in themselves. Alan Boyer, who has spent his career figuring out how colleges and companies actually build capability in people, not just hand them a syllabus. And Benny Lee, who brings big brand experience, a problem solver’s instinct, and a fierce protectiveness over the creative process.
There was a common theme running through every one of those conversations.
Businesses are expecting AI to change how work gets done in a way that increases productivity and efficiency. What they aren’t paying nearly enough attention to is how people build the capability this new work actually demands: working effectively alongside AI, questioning what it produces, exercising judgment, thinking strategically, collaborating across functions, adapting quickly, and bringing real creativity and initiative. Without those skills, none of it works out.
AI is changing the work. Who is developing the workforce?
This problem started long before AI
I spent years at New Horizons Computer Learning Centers, back when technology change had a rhythm you could plan around. Microsoft would roll out a new version of Office, then Cisco would roll out an update to its networking certifications. Companies figured out what their people needed to know, and training followed.
Then the pace changed. Cloud computing, Web 2.0, SaaS, social media and continuous digital disruption broke that old training cycle wide open. Companies couldn’t predict what people would need to know next quarter, let alone next year. So professional development became self-service.
You could watch the whole shift happen in three stages. First it was we’ll train you. Then it became here’s the learning library. Now it’s go figure out what you need.
Somewhere in that shift, we confused giving people access to learning with actually developing them.
AI is making the weakness in that model impossible to ignore.
Figure it out yourself is reaching its limit
Organizations today need people who can work effectively with AI, question what it produces, exercise judgment, think strategically, collaborate across functions, adapt quickly, spot opportunities, experiment and create. None of that develops because someone assigns an AI course or buys a seat on a learning platform.
And the pace of change means a company can’t build a curriculum once and call the workforce trained. The workforce isn’t just learning new tools. The nature of the work itself keeps moving.
Giving people AI isn’t the same as preparing them for AI
Benny put this well when I talked with him. His definition of AI literacy goes past knowing how to operate the technology. It’s knowing where AI belongs, where it doesn’t, what it can actually do today, and where our expectations have gotten ahead of reality. He talked about how AI is built to sound confident even when it’s wrong. It picks the tokens and the format that look right, whether or not the underlying answer is right. For a lot of everyday tasks, that’s a minor annoyance. When people start leaning on it for financial decisions, medical decisions, or something as personal as therapy, the stakes climb fast.
Alan brought the human side into focus when we talked. “Teaching with AI is not the same as working with AI,” he told me. Knowing how to use the platform is one skill. Knowing how to validate the output, how to catch the hallucination buried on page twelve of a twenty-page document before it throws off everything downstream, is a different skill entirely. When he ran a capability assessment for a university AI program, the gaps that showed up weren’t in the computer science content. They were in global and cultural fluency, in the ability to influence and persuade, and in what he calls fluid adaptation, the capacity to keep working on your original data set while five new ones land on your desk in the same afternoon.
Put those two together and a real distinction emerges. AI proficiency is knowing how to use the technology. AI readiness is knowing how to think while you’re using it.
We’re asking for capabilities many workplaces spent years suppressing
Widen the lens past AI for a second. Companies are suddenly asking for curiosity, creativity, adaptability, initiative, and cross-functional collaboration. Meanwhile, a lot of organizational systems were built around compliance, specialization, standardization and permission.
Alan’s work on enterprise risk and governance points to part of why that tension exists. He talks about needing a fence that’s twenty times higher for AI than for software, because access and data flow through so many more doors. Companies build guardrails for good reasons. But those same guardrails, applied without much thought, can quietly train people to ask permission instead of taking initiative.
You can’t spend years rewarding people for staying in their lane and then announce an AI initiative and expect everyone to become curious, experimental, cross-functional thinkers overnight. This is a leadership and organizational design problem. It isn’t an employee deficiency.
Employees have responsibility too
I don’t want any leader reading this to think the responsibility for developing capability sits with the organization alone. Dr. Vicki Wright Hamilton would push back hard on that reading, and she should. Her framing is that everybody is the CEO of their own life. That means paying attention to your skills, your network, your resources, your reputation, and where your value is moving next.
Here is one example she provided. Before AI, a content writer’s job was to write the content. After AI, the content gets written in seconds. So the writer has to reposition. “Bring me all the AI you got,” she says. “I’m going to take it and make it better. I’m going to validate it. I’m going to humanize it.” AI can get you from step one to step three, she told me. The human still has to get you from step three to step ten.
Employees should own their careers. Leaders still have to develop their workforce. Those two things aren’t in competition. They’re complementary.
Stop thinking about development as training
The answer isn’t rebuilding the corporate training model from twenty years ago. Training has its place, but capability gets built through experience. Alan put it about as plainly as it can be put: “Elevate the human, you got to. There’s no choice.”
If you want people to develop judgment, give them room to make decisions. If you want curiosity, give them room to explore. If you want innovation, let them experiment. If you want collaboration, stop rewarding the silo behavior your incentive structure is quietly encouraging. If you want AI literacy, let people work with AI in a properly governed environment and learn firsthand where it holds up and where it doesn’t.
You don’t build an adaptable workforce by telling people to be more adaptable. You build environments where adaptability gets practiced.
AI can become part of the development system
This is where AI stops being just the disruption and starts being part of the answer. Benny described using AI to compress the mundane middle of a task rather than replace the whole process. The human sets the direction, AI accelerates the pieces in between, and the human evaluates and decides. He compared it to running a large company. You don’t personally handle every decision at every level. You delegate, and you save your own judgment for the calls that actually need it.
I’ve found the same thing true in my own writing. When I don’t have a room full of people to bounce an idea off of, AI becomes something close to a third space, the kind of place where ideas used to get challenged and expanded over coffee. It pushes back on my thinking before I ever start writing. That only works if I’m using it to think, not handing my thinking over to it.
AI can be a tutor, a brainstorming partner, a challenger, a simulator, a research assistant, and a source of fast feedback. But only if people are encouraged to think with it instead of surrendering the thinking to it entirely.
Leaders need to ask a different question
Most leaders are still asking what AI tools they should deploy. The better question is what capabilities their people will need because of the changes the business is already making. From there, ask what capabilities you already have, where the real gaps are, which of those gaps need formal training and which need experience, what has to change about incentives and authority and workflow, and where AI can actually help people develop instead of just produce.
And ask yourself honestly what you’re still leaving employees to figure out entirely on their own.
The new learning bargain
Dr. Hamilton would say people need greater ownership of their own careers. Alan would say that as AI accelerates the work, organizations have to intentionally elevate human capability. Benny would say AI literacy means having enough judgment to know where AI belongs and where it doesn’t.
The old bargain was, “We’ll train you.” Then it became, “Figure it out yourself.” The next version has to be closer to this: “You own your development. We will build the environment where you can actually develop.”
We can’t predict every skill our people will need five years from now. We probably can’t predict most of what they’ll need two years from now. That doesn’t mean leaders are powerless. It changes what we’re developing.
We’re not simply preparing people for the next piece of technology. We’re developing people who know how to learn, question, experiment, collaborate, judge, create, and adapt as the technology keeps changing underneath them.
AI is changing the work. That part isn’t up for debate anymore. Employees have a responsibility to keep developing themselves, to stay curious about where their value is headed instead of waiting to be told. But here’s the part leaders can’t hand off. If your business strategy depends on people validating AI output, exercising judgment, adapting to problems nobody wrote a playbook for yet, and those capabilities don’t exist in your organization today, then building them isn’t a nice-to-have sitting next to your strategy. It is your strategy. A plan that assumes capabilities you haven’t developed isn’t a plan.
So who is developing your workforce?
