Leading AI-intensified teams

How to build teams that think better, impact more and feel good in an AI-accelerated world?

Leaders are under intense pressure to deliver AI productivity gains and ROI from all the investments. The promise of AI was to free up your people to deliver higher value and be creative; the reality is very different.  It turns out, our default responses with the new technology are making things worse: teams are getting busier and delivering more output but less impact. Busyness is a choice, driven by three things: ineffective daily habits, a dumb success strategy and people taking the easier path.  

To deliver team impact, leaders need to create the conditions for people to make better choices. This talk applies the Busy framework, grounded in the latest research into the psychology of AI, to the leadership context: as a map for leading differently. The leaders who get real ROI from AI aren't those who drive hardest. They're those who help people make better decisions: to use AI to elevate their thinking; to focus on what truly matters; and to catalyse the conversations that need to happen for change and thriving to happen.

Team attention management

Leaders shape the attentional environment their people work in, often without realising it. While pressure is real, an environment focused on velocity and volume drives busy mediocrity.  People start more projects (because AI reduces the cost of starting to near zero), meaning more spinning plates. This is AI ‘pluscrastination’ at work; at a team level it strangles collective focus. As the pace rises, employees cope by offloading more thinking to AI. Producing increased output with less insight. When this is rewarded, the problem accelerates. And the expectation that team roles are expanded, running multiple agents and workstreams creates a hyper-paralleling trap that fragments the sustained focus and can lead to AI brain fry. 

This section gives leaders the diagnostic tools to see what's happening to their team's attention across all three dimensions: direction (where people are focused), depth (how well people think) and duration (how distracted they are). It gives leaders the strategies to redirect attention deliberately; not through mandates, but through the questions they ask, the behaviour they model, and the environment they foster.

Strategic focus as the editor-in-chief

The leader's job in an AI-enabled world isn't to generate more output. It's to be the editor-in-chief: amplifying the value drivers and subtracting everything else, constantly. In a world where AI makes productive output infinite, the hardest and most valuable leadership act is deciding what not to do. Addification - the organisational bias toward adding initiatives, processes and expectations - runs unchecked without active leadership intervention. The efficiency trap means every AI productivity gain becomes a raised bar rather than freed capacity. 

This section focuses on three concrete leadership moves: translating strategy into the Big 3 — the three things that matter most right now — and doing it again as the landscape shifts; applying strategic subtraction as a standing discipline, naming what stops before anything new starts; and reimagining workflows rather than accelerating them, asking not "how do we do this faster?" but "should we be doing this at all?" These aren't one-off interventions. They're the ongoing editorial role that separates leaders who create focus from those who create noise.

A team culture that unlocks change

The most productive AI-enabled teams are both highly accountable and highly safe; and most teams are neither. Expectation creep makes accountability feel punishing rather than motivating. Workslop cascading from AI-enabled colleagues creates friction that teams rarely surface directly. Behind almost all busyness is a tough decision not taken, or a difficult conversation avoided. Staying busy is the easier and safer option in most teams. The leaders who build genuinely high-performing AI-enabled teams create the conditions for hard trade-off choices and honest conversations. An environment where people can make different decisions, and explain why; where people can push back – on you or on team members - on expectation creep and workslop. To learn together, recognizing AI requires rethinking how work is done, how trust is built. 

This section gives leaders the tools and the language to support their team to make tough choices and have the conversations they've been putting off. When this is handled with candor and consideration, it unlocks lasting change but also better, more honest relationships. 

Three things you'll take away

• A new diagnosis. The language and the lens to see what's actually driving busyness across your team: pluscrastination, addification, amplifatigue, the efficiency trap. Most leaders know something is wrong; this talk gives them the precise vocabulary to name it and the awareness to see their own role in it.

• Three leadership moves. Concrete, research-grounded strategies across all three sections: the diagnostic tools to read your team's attention, the Big 3 and subtraction discipline to create strategic focus, and the culture-building moves that make both accountability and safety possible simultaneously.

• An AI-learning mindset. You'll leave not just with tools but with a different sense of what leadership looks like in an AI-intensified world. The leaders who build the best human-AI teams aren't the ones who know most about AI. It´s the ones who are most curious; who create environments where their teams learn their way to success.