To get Google's TPU team to adopt their AI, the AlphaChip founders overcame deep skepticism through a relentless two-year process of weekly data reviews, proving their AI was superior on every single metric before engineers would risk their careers on the unconventional designs.
Related Insights
To secure buy-in for its risky "Platform 2," Zipline built a rough prototype and held a "conviction milestone" event for the whole company. Witnessing the tangible demo converted even the most ardent skeptics on the leadership team, aligning everyone to bet the company's future on the new product.
Generic use cases fail to persuade leadership. To get genuine AI investment, build a custom tool that solves a specific, tangible pain point for an executive. An example is an 'AI board member' trained on past feedback to critique board decks before a meeting, making the value undeniable.
A key driver for AI prototyping adoption at Atlassian was design leadership actively using the new tools to build and share their own prototypes in reviews. Seeing leaders, including skip-level managers, demonstrate the tools' value created powerful top-down social proof that encouraged individual contributors to engage.
Google's AlphaChip team initially failed to impress the internal TPU team by optimizing for standard academic benchmarks. The breakthrough came when they co-developed cost functions with the TPU team that directly targeted the real-world metrics engineers were evaluated on, like congestion and power consumption.
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.
When introducing AI to a skeptical executive, a detailed, multi-week rollout plan can be overwhelming and trigger resistance. A more effective approach is to showcase one specific AI capability within an existing tool to solve a tangible problem. This "dip your toe in the water" approach builds comfort and demonstrates immediate value.
Amplitude's CEO notes that unlike previous tech waves, AI adoption was pushed by executives, not engineers. Engineers were initially skeptical, viewing the hype as "grifting," which created internal friction and required a deliberate internal education campaign to overcome.
Many technical leaders initially dismissed generative AI for its failures on simple logical tasks. However, its rapid, tangible improvement over a short period forces a re-evaluation and a crucial mindset shift towards adoption to avoid being left behind.
Many engineers at large companies are cynical about AI's hype, hindering internal product development. This forces enterprises to seek external startups that can deliver functional AI solutions, creating an unprecedented opportunity for new ventures to win large customers.
When leadership pays lip service to AI without committing resources, the root cause is a lack of understanding. Overcome this by empowering a small team to achieve a specific, measurable win (e.g., "we saved 150 hours and generated $1M in new revenue") and presenting it as a concise case study to prove value.
