Good morning. Good afternoon. Good evening, everyone, and thank you for joining. I'm LaCheryl Morgan.I lead legal strategy for AI innovation and acceleration at NBCUniversal, which means my job is to figure out how we move quickly and responsibly at the same time. And I'll tell you honestly, most days, those two things feel like they are in pulling in completely opposite directions. What I've learned from sitting inside this crazy world is sometimes things don't always appear as they seem, and I wanna share some information about that with you today. Because I think it changes how this whole AI moment feels and what your place in it actually looks like. Most of the anxiety people feel about AI right now does not actually come from the technology itself.

It comes from uncertainty, from not knowing where the lines are, how decisions get made, or what responsible actually looks like when it is working versus when it's just a document that no one reads. Here's what the data shows about that uncertainty. PwC studied organizations across industries and found that companies with a responsible AI framework are 1.7 times more likely to outperform their peers. In addition, their employees are twice as likely to trust what the AI is telling them. Twice as likely to trust it. Not because the tools are better, but it's because they understand the guardrails around them. And that understanding is what allows people to move with confidence instead of hesitation. Guardrails are not what slows innovation down. They're what give people permission to move.

And once you see it that way, you start to see this entire landscape differently, including your own place in it. The first thing I want to share is something that took me a while to fully appreciate, and I think it'll resonate with a lot of people in this virtual room. The most valuable person in any AI conversation is not always the most technical person. More often, it is the person who is willing to name what's unclear when everyone else is just kind of dancing around it. Think about what actually creates friction inside organizations when it comes to AI. It's never or rarely ever a capability problem. People know how to use the tool. The friction again comes from, our favorite word in this ten minutes, uncertainty, From not having a shared understanding of how we make these decisions, what is okay, what is not, and who's responsible when something goes wrong.

And in the absence of that clarity, people do one of two things. They either wait for someone above them to figure it out, which costs time and momentum, or they move forward and hope for the best, which costs trust when things do not go as planned. Neither of those is a good outcome from anyone. So what breaks that pattern is someone being willing to name the real question, not with the answers, just with the honesty to say, I think we need to slow down and get a clear understanding on what we are deciding here. What are we trying to accomplish? What problem are we trying to solve? What are we missing? And most importantly, what happens if we get this wrong? That kind of clarity is an act of leadership. It doesn't require a title or a governance background.

It requires paying attention and being willing to say out loud what you are noticing. And in my experience, the person who does that becomes the person people want in every k every conversation that follows. So here's something that surprised me when I first started doing this work, and I think it may surprise you too. The AI framework that actually holds and really sticks inside organizations, the ones that people genuinely follow are almost never the ones designated or designed by a small group and then pushed down from the top. They fall apart because they do not account for how things actually work on the ground. So the policy sounds right in theory, but creates friction in practice because the people closest to the work were not part of building it.

The frameworks that really hold are built within input from across the organization, from the people who understand how the tools actually behave in real situations, from the people who can see where the guidance breaks down, who knows what the policy is missing it in it because they are living it every day.

That means the perspective you have from where you sit, your honest understanding of what AI should and actually looks like in practice in your work is not just useful. In many cases, it's what the people making these decisions are missing entirely. Paying attention to that, being willing to say, here's what I'm seeing. Here's where the guidance does not match reality. That is real and meaningful contribution. And the last thing I wanna talk about is perhaps the most reassuring thing I can offer. Nobody has this fully figured out. Not the senior leaders, not the governance teams, not the companies that appear to be moving the fastest. AI is shifting quickly enough that everyone is adapting in real time. The frameworks being built today will need to evolve.

The conversations happening inside organizations right now look nothing like they did eighteen months ago, really even six months ago, and they will look different again two months from now, six months from now, and surely a year from now. I say that not to add to the uncertainty, but to release some of it because it means that you are not behind. You're exactly where everyone else is. The playing field is more level than it appears from the outside. The people who navigate this era well are not the ones who had everything mastered before things started changing. They're the ones who stayed curious, who paid close attention to what was actually happening rather than the what they expected to happening to happen, who are willing to revisit what they thought they knew when the evidence pointed somewhere different, and who kept adapting not because they had to, but that but because they understood that adaptation is the work.

That capacity, curiosity, combined with the willingness to keep learning is available to everyone. And it's the thing that compounds most reliably over time in a landscape that will not stop moving. So wherever you are right now, whatever country you're joining from, whatever stage of your career you are in, I want to leave you with this. The AI era does not belong only to the people who already have authority over it. It belongs to the people who are paying attention, who are willing to name what is unclear, who bring their honest perspective into conversations where it matters, and who stay curious as things continue to evolve. This is what leading with guardrails actually means. It's not a job title. It's not a function.

It is a way of showing up in the work that you are already doing. And when you do it, you're not just keeping up with the AI moment. You're helping to shape it. This is how responsible innovation moves forward, not in spite of the guardrails, but because of them. Thank you for your time.