1. Learn to work with AI, not just use it
The biggest shift is not tools, but workflow.
Individuals and teams should experiment with AI as a thinking partner, research assistant, and rapid prototyping engine. This means learning how to frame questions, critique outputs, and iterate collaboratively with AI systems.
2. Redesign how teams make decisions
AI dramatically reduces the cost of generating information.
The bottleneck now becomes sense-making and decision-making inside the team. Organisations should revisit how decisions are made, who owns them, and how human judgement integrates with machine-generated insights.
3. Clarify roles between humans and machines
In AI-augmented teams, roles become fluid.
Some work shifts toward AI, while human roles move toward direction-setting, synthesis, relationship building, and creative judgement. Teams should explicitly discuss where AI adds leverage and where human expertise remains essential.
4. Build shared literacy around AI
AI capability varies widely across organisations and even within teams.
Developing a baseline understanding of AI tools, strengths, and limitations helps teams collaborate more effectively and reduces the risk of over-reliance or misuse.
5. Learn how to launch teams effectively in the first place
AI will not fix poorly formed teams.
The ability to start teams well—aligning purpose, expectations, roles, and ways of working from the beginning—becomes even more important when AI tools accelerate the pace of work.
Workshops such as the Team Liftoff Masterclass help leaders and teams learn how to launch high-performing teams quickly and confidently in this new environment.