Leading through more disruption than any agenda can hold
Every C-suite conversation I have right now starts with some version of the same question: where do we begin?
As I wrote in the article AI Isn’t a Tool, It’s a Superpower, and That’s Exactly Why People Freeze, the choices are overwhelming, the pressure is high, and the cost of starting in the wrong place feels significant. So leaders look for the move that’s fast enough to satisfy the demands coming from the board, their employees, or the market, and thoughtful enough not to blow up the organization.
Here’s what I’ve learned after twenty years of watching technology transformations play out: the answer to “where do we begin” almost never starts with the technology.
For example, earlier this month, Canva’s Chief Customer Officer described what happened when Canva gave 5,000 employees a full week to do nothing but explore AI. Best tools available. Full calendar cleared. No meetings, no inboxes, just time to experiment. The expectation was transformation. What they discovered was the bottleneck wasn’t the technology or the calendar. It was the people.
It wasn’t because the employees lacked capability. As I explored in last week’s article, the society they grew up in hadn’t built the conditions for genuine exploration. People felt guilty stepping away from their inboxes. They defaulted to the use cases they already knew. They waited for permission that nobody had thought to give. It’s what happens when people have spent their careers being rewarded for compliance and are suddenly asked to exercise the self agency nobody ever taught them to use. The conditioning runs deep, and you can’t overcome it by clearing a calendar.
Rob Giglio’s conclusion was direct: “The tools were ready. The humans weren’t.”
Perhaps Canva was asking the wrong initial question. It shouldn’t be “where to begin?” Perhaps it should be “Who do you want to be when this is over?” Because the decisions we make right now, under this much pressure, with this much uncertainty, are already answering that question — whether we’ve asked it or not.
The Promise Always Outpaces the Readiness
In the mid-2000s, I launched the Enterprise 2.0 Special Interest Group at the Technology Association of Georgia because I was genuinely fascinated by a simple idea: what if social technologies could fundamentally change how organizations worked?
Blogs, wikis, online communities, internal social networks. I spent a number of years immersed in this world, surrounded by people who believed these tools would flatten hierarchies, break down silos, and make organizations more collaborative. I was in conversations with brilliant leaders exploring what the future of work might look like. The potential was real.
But the organizations weren’t ready for it. Not because the technology failed to deliver. It was that the structures, incentives, habits, and fears that shaped how people worked proved far more durable than the software. Giving employees a collaboration platform didn’t automatically create a collaborative culture. Installing new technology didn’t erase old ways of thinking. The tools evolved faster than leadership did, and the gap between what the technology made possible and what organizations could actually absorb swallowed most of the promise.
For years, I wondered if we had simply overestimated the power of technology to transform organizations.
Now, watching the rise of AI, I see that experience differently. Maybe we weren’t wrong. Maybe it wasn’t the right time. In a recent discussion I was exploring the idea of how the social technologies we thought were so transformative might have actually just been the bridge.
AI has the potential to reshape work in ways social technologies never could. It doesn’t just help people communicate differently. It changes how decisions are made, how knowledge is created, and how value is generated. It may finally force organizations to rethink assumptions that have survived every previous wave of digital transformation.
But the gap is still there. Technology is moving faster than it ever has. Organizations are not. And if the last twenty years taught me anything, it’s that the size of the promise has never determined the outcome. Readiness has. But readiness isn’t just operational. It’s about knowing who you are and what you stand for before the pressure makes that question harder to answer honestly.
Speed Doesn’t Care About Your Organization
Boards are pushing CEOs to move faster on AI. The pressure is real and the fear behind it is understandable. No one wants to be the organization that was cautious while competitors pulled ahead. Vendors are promising efficiency, competitive advantage, and cost reduction. The market is rewarding companies that show AI progress in their earnings calls.
None of that pressure comes with a pause button. It’s more like the need for speed just increases. But speed doesn’t care about your culture, your people, your values, or the trust you’ve spent years building. It just moves. And right now, speed has a lot of people in its corner: boards, investors, vendors, analysts, and competitors. What it doesn’t have is a stake in your organization’s long-term health.
It’s not just that leaders want to move fast. The problem is that speed has become a proxy for strategy. When that happens, the questions that actually determine outcomes stop getting asked. Not because leaders don’t care about them, but because there’s no room left in the agenda. Speed crowds out judgment. And in a transformation this consequential, judgment is the one thing you cannot outsource — not to a vendor, not to a timeline, and not to the technology itself.
The organizations that will look back on this period with confidence won’t necessarily be the ones that moved fastest. They’ll be the ones whose leaders knew who they wanted to be before the speed made it impossible to ask.
What Happens When Ethical Agents Work as a Team
The question isn’t only what’s possible, it’s what we should be paying attention to while it becomes possible.
History offers a warning about optimizing for what works before understanding what it costs. When tetraethyl lead was added to gasoline in the 1920s, it solved a real problem. Engine knocking was a genuine engineering challenge, and lead worked. The companies involved resisted oversight for decades, and leaded gasoline wasn’t fully phased out in the United States until 1996. The long-term public health consequences were severe for at least two generations of society, and they were ignored for most of that time because performance was measurable and consequences were ignored.
We are in a similar moment with AI. Except this time the thing we don’t fully understand isn’t a chemical additive. It’s an evolving layer of intelligence that is still revealing its own behavior to the people building it.
Anthropic’s own researchers recently published a study that makes that point better than I can. They put individually aligned AI agents into teams, gave them shared business goals, and measured what happened. The individual agents behaved ethically when tested alone. The teams did not. The teams did outperformed on the business objective, but underperformed on ethics — not because anyone programmed them to, but because that behavior emerged from the system itself.
This isn’t a software bug. It isn’t a configuration error. It’s what happens when you combine components that each behave one way and the combination behaves another. The researchers called it diffusion of responsibility. I’d call it a signal that we are still in the early stages of understanding what we’re working with.
The vendors won’t tell you that. The earnings calls won’t reflect it. But the researchers building these systems are telling us directly: we don’t yet know everything this technology will do when it operates at scale, in combination, and under pressure to perform.
That’s not a reason to stop. It’s the most important reason to slow down your thinking even if you can’t slow down your timeline.
And when the technology itself is still figuring out what it does, your own clarity — about your values, your people, and what you are unwilling to compromise — becomes the most stable thing in the room.
The Real Question Isn’t on Most Leadership Agendas
“How fast can we deploy?” is the wrong question. No organization should set out to become faster at the expense of everything else. The goal could be to become better. Speed is a dominant metric because it’s easily measurable. Better is harder to quantify. Those are different destinations, and conflating them has a cost.
But the questions that will actually determine your outcomes aren’t on most leadership agendas right now. Who do we want to become?
I’ve watched organizations burn through significant money on core initiatives because nobody stopped to ask what they were trying to become on the other side. When you don’t know the answer to that question, every decision becomes reactive. You’re not building toward something. You’re just responding to whatever pressure showed up this quarter.
I’ve also watched what happens when accountability stops living with people and starts living with the process. Nobody designs it that way. It drifts. Decisions get handed off, then handed off again, until the original reasoning is long gone. Eventually someone on your team hits a wall and the only explanation available is “this is just how we do it.” Nobody can change it because nobody owns it. That’s not efficiency. That’s organizational paralysis wearing efficiency’s clothing.
Early in my career I walked into a volunteer board position and made the classic mistake — I focused on what needed to change before I understood what people needed to hold onto. I was treated like a heretic until the results started coming in. What I learned wasn’t that the system was sacred. It was that people’s sense of identity and safety was wrapped up in it. There’s no shortcut through that. There’s only leadership.
AI adoption isn’t the only transformation bearing down on your organization right now. Supply chains are absorbing shocks that haven’t fully hit household budgets yet. The labor share of US GDP is at its lowest point since 1947. The displacement of middle-class work is already underway, and the math on that is not waiting for your deployment timeline. This is the scope of what you’re actually leading through. Who do you want to be when you get to the other side of all of it? (source: This Isn’t a Recession. It’s Worse)
What People Will Remember
Years from now, AI will be unremarkable. It will be infrastructure, like electricity or the internet. No one will remember which platform you chose or whether you moved six months ahead of a competitor.
What people will remember is whether you led with intention during one of the most complex convergences of technological, economic, and social disruption in modern history. Whether your employees trusted you when everything felt uncertain. Whether your customers felt respected or processed. Whether, when the pressure was highest and the incentives were loudest, you paused long enough to ask what you were actually building toward.
That’s what is at stake right now. Most organizations haven’t framed it that way yet.
You still can.