Structuring Your AI Council

In the previous unit, you explored how Asana made AI integration a non-negotiable responsibility for every People program owner — from vendor roadmap audits to no-code GPTs built without engineering support. But program-level ownership only works if the organization signals that internal AI adoption matters at the highest level. That's where Asana's next move comes in: elevating AI activation to a company-level objective with the same visibility as revenue targets, and standing up an AI council designed not around technical expertise, but around a very specific human profile.

You'll recall that Lisa Ann Logan described Asana setting "about seven or eight company objectives" each year — the goals that translate long-term strategy into annual priorities. Internal AI adoption became one of those top-level goals, sitting "right up there with our ARR goals for the year." That placement wasn't symbolic. It meant the goal inherited the same accountability infrastructure Asana uses for everything else: named owners on every goal, defined success metrics, and "real candid red yellow green flags on whether it's off track or on track." The CIO was named as the accountable executive, and the goal was deliberately broken into sub-goals relevant to every function — finance, marketing, legal, and beyond — so each team felt invested rather than merely informed. As Logan emphasized, this created both visibility and a culture of accountability that made AI adoption impossible to quietly deprioritize when other business pressures mounted.

With the company-level goal in place, Asana needed a council to drive it forward. But rather than duplicating work already happening elsewhere, Logan's team identified a specific gap: "there was a huge gap that wasn't covered and that was how to think about our employees and how to get them on board." Subject matter experts in governance, security, and procurement were already handling their domains. The council's charter focused squarely on accelerating employee enthusiasm and functional adoption — what Logan called "accelerating our internal ROI."

The member profile followed from that charter. Logan described it as an "authentic galvanizer" — someone who is curious, excited to learn, skilled at program management, and deeply understands "how work moves across your function." Deep AI expertise was welcome but not required. Logan herself embodied this: "I am not an AI expert at all. What I am is an influencer... a seasoned program manager... and a galvanizer." Each function had a representative on the council, creating a "for the people by the people kind of vibe." And the council held itself accountable to a single, measurable North Star: increasing the employee AI usefulness score from their internal survey — how useful employees found AI in their day-to-day work.

One candid lesson Logan shared: the executive team initially promised council members 20% of their time for this work. In practice, "not a one" actually got that allocation, because the people tapped for the council were already high-performers stretched thin by what Logan called a "competency tax." The council became more of an elective commitment — but one people chose to show up for because "it's the most fun meeting of everyone's week" and the work was genuinely energizing.