The leadership advantage AI can’t automate: Attention

AI promises to help organisations move faster. But at two Asana executive dinners held in Sydney and Melbourne in August, a different leadership question emerged: what should we choose not to accelerate?

The challenge is not finding more hours in the day, but creating better conditions for the hours people already spend.

Led by author and neuroscientist TJ Power and moderated by Jo Gaines, General Manager, APAC, at Asana, the conversations explored attention, decision fatigue, and the future of work. The takeaway was clear: as AI takes on more tasks, the quality of human attention will become more valuable, not less.

Attention is becoming a leadership advantage

In his keynote presentations, Power explained how constant digital stimulation, rapid task switching, and the pressure to remain responsive can erode the conditions needed for sustained attention. Leaders may be busy all day while getting little time for the deep thinking their hardest decisions require.

Power’s idea of “deceleration” offers a useful strategy to counter the drain on attention. Screen-free meals, quiet walks, and brief pauses give the brain space to shift out of constant execution mode. These moments can feel unproductive, but they are often when ideas connect and strategic thinking becomes possible.

The brain requires rest to rebuild, just like an athlete requires rest to perform.

TJ Power

Author and neuroscientist

Protecting attention, however, cannot rest on better personal habits alone. The way work is designed also matters.

Decision fatigue is an organisational problem

When priorities are unclear, information is fragmented, or ownership is ambiguous, people carry those open loops in their heads. Every status update to chase and every decision with no clear owner adds to the cognitive load. Leaders often absorb the greatest share because uncertainty keeps escalating to them.

The dinner discussions showed what a better division of labour can look like. Participants described using AI for rules-based, time-consuming work such as transcribing calls, processing claims, validating information, and synthesising reports. Just as importantly, they kept people involved where judgment, accountability, or unintended consequences mattered.

That distinction is essential. Adding AI to an overloaded system can simply produce more output, faster. The opportunity is to redesign work so technology removes cognitive load rather than creating more of it.

Keep human attention where it matters

TJ Power applies that distinction in his own work, keeping AI away from writing his next book while using it to reduce routine cognitive load.

Wherever it can alleviate overwhelming levels of decision making that just don’t need to be made by me, I do that.

TJ Power

Author and neuroscientist

Applying that discipline across an organisation requires shared context. Asana’s Work Graph connects work, people, priorities, and goals, acting as an external memory that both people and AI can draw on. Instead of critical context living across individual minds and disconnected tools, it sits in a shared system that both people and AI can act on.

As the operating system for human-agent teams, Asana is designed to make that collaboration visible and governable, with clear ownership and humans involved at the moments that require judgment.

The organisations that lead in the AI era may not be those doing the most with AI. They will be those that make the clearest choices about what technology should carry, what people should own, and where human attention can have the greatest impact.