I have been fascinated by artificial intelligence since before most people knew what to call it. I was a kid when War Games came out. A teenager watching a computer nearly started a nuclear war because it could not distinguish a simulation from reality. What fascinated me was not the destruction it almost caused. It was the two things happening simultaneously: the system was making consequential decisions no one fully understood, and it was learning from every move it made.
That combination never stopped being relevant. It is exactly what drove me to spend the last several months completing formal AI coursework at a serious level. My clients are making decisions about AI right now, and I needed to understand what I was advising them to communicate.
Over the last several months, I completed the AI for Business Specialization at the University of Pennsylvania's Wharton School, along with AI leadership certifications through Google, Microsoft, and LinkedIn. Here is what it confirmed about the work I do.
The governance gap is real, and most organizations are not ready for it.
The Wharton AI Strategy and Governance module was the most consequential of everything I completed. Organizations are adopting AI faster than they are developing the internal frameworks to govern it. Decisions about AI tool deployment and workforce implications are being made at the leadership level without clear communication strategies attached to them.
That is a familiar pattern. The decision moves faster than the communication thinking. By the time leadership is ready to talk about what is changing, employees have already drawn their own conclusions.
AI adoption follows the same pattern, at a faster pace and with higher stakes.
Ethics is not a footnote. It is a communications crisis waiting to happen.
The ethics coursework across Google and LinkedIn covered bias, transparency, accountability, and the organizational responsibility to communicate AI limitations honestly. It is the area where most organizations are least prepared.
When an AI system influences a hiring decision or a performance review, employees will want to know how and why. If leadership cannot answer that question clearly, the silence will be interpreted. It always is.
The organizations that get ahead of this treat AI ethics as a communications challenge from the beginning, not a legal disclaimer added at the end.
Applied skills matter more than most senior leaders think.
The Google coursework on prompting and applied AI use was the most practical. I came away with a clearer understanding of what these tools actually do well and where they break down. That understanding is directly relevant to advising leadership teams on what AI can and cannot do in high-stakes communications work.
AI can accelerate production. It can surface patterns across large amounts of information. It can draft. What it cannot do is exercise judgment about timing, read the specific dynamics of a leadership team, or anticipate how a particular workforce will interpret a particular message from a particular leader at a particular moment. That work still requires someone who understands the organization deeply and knows what the stakes actually are.
What this means for leadership teams navigating AI-driven change.
The leaders who manage AI transitions well are not the ones who understand the technology best. They're the ones who understand how to communicate change to people who are uncertain about what it means for them.
That has always been true. AI makes it more urgent.
The communication risks that come with AI adoption are not technical. They are human. Employees are interpreting what is changing, deciding whether to trust leadership's judgment, and forming conclusions about whether the organization can lead them through it. Most leadership teams are not prepared for the questions that follow.
That is the work I do. This coursework reinforced why it matters and sharpened how I do it.