When teams move from in-person to distributed work, managers often assume communication is the challenge. The real challenge is clarity.
In an office, unclear priorities can stay hidden because people constantly fill in gaps through hallway conversations, meetings, and proximity. In remote environments, those gaps become impossible to ignore. Employees quickly feel when expectations, goals, or decision-making aren't clear.
AI can help managers communicate more effectively, but it doesn't solve the underlying problem. Leaders still have to create alignment around priorities, strategy, and outcomes. And as markets, products, and business priorities continue changing faster than ever, providing clarity has become one of the hardest parts of leadership.
Vinícius shared:
"Mediocre clarity or bad clarity becomes very visible in the remote environment."
The lesson: Before worrying about AI adoption, make sure your managers can answer three questions for every employee:
One of the most interesting themes throughout the conversation was the shift from managing work to designing systems that enable work.
Historically, managers spent much of their time directing execution, staying close to day-to-day tasks, and overseeing operational details. But as AI automates more administrative work and provides faster access to information, that model starts to break down.
Instead, leaders are increasingly responsible for building systems that create consistency, accountability, and scale. Their value comes less from personally driving every task and more from creating environments where great work happens predictably.
Vinícius shared:
"They become less operators and more system architects for how people and how work happens."
The best managers of the future won't be the people with all the answers. They'll be the people who design the best operating systems.
There's been no shortage of speculation about whether AI will eliminate managers. The panel's perspective was more nuanced.
Instead of one standard manager role, organizations will likely choose from several different models. Some managers may oversee larger teams because AI helps synthesize information and automate administrative work. Others may become player-coaches who both lead people and actively contribute as builders. And some organizations may use AI to free up managers to spend significantly more time developing talent.
Brandon said:
"We're going to get some time back. We have to choose how we want to use that time."
What's important is that leadership teams intentionally decide which future they want.
Do you want:
There isn't one correct answer. But there does need to be a choice.
This was arguably the most important talent conversation of the entire session.
Across organizations, employees continue saying they want more development opportunities. Yet when leaders dig deeper, they often discover employees are really asking for one thing: promotion.
The challenge is that flatter organizations, higher retention, and AI-driven efficiency are reducing the number of traditional management opportunities available.
As a result, organizations need entirely new ways for people to grow. Vinícius shared:
"If you only think that you can grow in your career if you grow vertically, I might not have a space for you in the company."
That doesn't mean growth disappears. It means growth starts looking different:
The companies that win will create development systems that reward contribution, capability, and influence—not just title changes.
One of the strongest examples came from Zapier's creation of a new role: the AI Automation Engineer.
These employees identify opportunities to redesign work, build systems that improve workflows, and teach others how to operate more effectively. Interestingly, every AI Automation Engineer at Zapier has been hired internally.
Why?
Because success in these roles requires more than technical skill. People need business context, organizational knowledge, and the ability to coach others through change. Brandon shared:
"Anything good that our teams will ever do with AI is going to be anchored on a problem that's actually worth solving."
That's an important reminder for HR leaders.
The biggest opportunity may not be teaching employees how to use AI tools. It may be helping employees transition into entirely new categories of work that AI makes possible.
Perhaps the most practical takeaway was that no one actually has the playbook yet.
Every company is experimenting. Every leadership team is learning in real time. The organizations that navigate this transition successfully won't be the ones with perfect answers. They'll be the ones that involve employees in shaping what comes next.
Carmen compared the current moment to the early days of COVID, when leaders had to rapidly redesign how work happened without clear precedent.
The companies that adapted best weren't the ones that dictated every solution from the top. They were the ones that co-created solutions with their employees. Carmen shared:
"We really need to be working with employees at all levels of the organization and understanding how these tools impact workflows."
AI transformation isn't a leadership exercise.
It's an organizational exercise.
And the people closest to the work are often the ones who see the future first.