When trying to convince teams to adopt a new technology, the most effective strategy is to implement the solution for them. Presenting a finished, working migration is a much easier conversation than asking them to take on a large, uncertain task themselves.
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To drive adoption for an internal tool, identify the teams most frustrated with the existing solution by scraping support channels. Then, schedule small, bespoke tech talks directly for those teams. This targeted approach generates highly engaged and grateful early adopters.
When rolling out the Odin platform at Uber, the team intentionally avoided a big-bang launch. They started with their own systems, then expanded to friendly teams, using an incremental approach to build momentum and prove value before approaching more resistant groups.
Forcing innovations to "scale" via top-down mandates often fails by robbing local teams of ownership. A better approach is to let good ideas "spread." If a solution is truly valuable, other teams will naturally adopt it. This pull-based model ensures change sticks and evolves.
Instead of large, multi-year software rollouts, organizations should break down business objectives (e.g., shifting revenue to digital) into functional needs. This enables a modular, agile approach where technology solves specific problems for individual teams, delivering benefits in weeks, not years.
To win over skeptical team members, high-level mandates are ineffective. Instead, demonstrate AI's value by building a tool that solves a personal, tedious part of their job, such as automating a weekly report they despise. This tangible, personal benefit is the fastest path to adoption.
To transform a product organization, first provide universal access to AI tools. Second, support teams with training and 'builder days' led by internal champions. Finally, embed AI proficiency into career ladders to create lasting incentives and institutionalize the change.
To overcome widespread resistance and inertia, companies should avoid company-wide digital transformation rollouts. Instead, create a small, empowered "tiger team" of top performers. Give them specialized training and incentives to pilot, perfect, and prove the new model before attempting a broader implementation.
To scale their new notebook platform, "Bento," at a rapidly growing Meta, the team focused on making it the default for all new hires in boot camp. This created network effects by capturing users with no legacy habits, bypassing the difficulty of converting entrenched employees.
To gain organizational buy-in for AI, start by asking teams to document their most draining, repetitive daily tasks. Building agents to eliminate these specific pain points creates immediate value, generates enthusiasm, and builds internal champions for broader strategic initiatives, making it an approachable path to adoption.
When implementing a new productivity system, success depends more on team comfort than on the tool's advanced features. Forcing a complex platform can lead to frustration. It's better to compromise on a simpler, universally accepted tool than to create friction and alienate team members.
