Integrating AI into Programs

Welcome to "Activating Employees on AI — Lessons from Asana." In this course, you'll unpack insights from Lisa Anne Logan's Transform 2025 session, where she shared how Asana activated 1,800 employees on AI by treating internal adoption as a people strategy — not a technology initiative. Across three units, you'll explore how to embed AI into every People program, structure an AI council with the right member profiles, and design employee-driven learning strategies informed by sentiment data and maturity frameworks.

Let's start with the foundational move that made everything else possible: making AI integration the expectation for every People program owner, not an optional side project.

You'll recall from the session that Lisa Ann Logan didn't position AI integration as a favor she was asking of her People team — she made it part of the job. Every program owner at Asana is now responsible for integrating AI "the same way that they are responsible for the strategy, the results, everything else about their program." This means two distinct types of integration: back-of-house improvements to how the program is administered, and employee-facing changes to how people actually experience it. Logan noted the split was roughly half and half across their programs.

Critically, this started with something accessible: she asked every program owner to call their vendors — engagement survey platforms, HRIS tools — and "find out what was coming on the vendor roadmaps that they could take advantage of." That single action gave program owners a concrete first step, built their AI fluency through their existing vendor relationships, and helped them plan change management well before new features rolled out. The insight here is that ownership creates momentum in a way that optional experimentation never will.

Building on that ownership mandate, Asana tackled the cultural barrier head-on — the quiet anxiety many employees feel about whether using AI in high-stakes processes is somehow gaming the system. At the start of performance review season, the People team came out "loud and clear" with explicit messaging: "This is not cheating. This is actually not just an invitation but an expectation that you are using AI to write your performance reviews." That language was embedded directly into manager and IC enablement programs, complete with guidance on how to use Asana's product to surface impact data and growth areas as a starting point for drafts.

This same principle extended to promotions and performance management. A promo scribe GPT helped nominators craft promotion arguments that were "clear, objective, unbiased" with greater consistency across candidates. And a no-code guided intake GPT now coaches managers through performance management triage — walking them through a conversational flow about the challenge they're facing, how far along they are, and whether it's time to involve their people partner. As Logan emphasized, "all of this is no code" — her team built these tools without engineering support, proving that program owners don't need technical backgrounds to create meaningful AI-powered workflows.