GoKawiilThe Model’s the Easy Part - How to Get, and Keep, Value
Here’s how I see the evolution of AI in enterprises over the last few years:
Autumn of 2022, the world thinks it’s going into a recession. IT budgets are frozen for 2023.
November 30, 2022: ChatGPT launches, and the non-technical parts of the C-Suite have a tangible interaction point with AI - a simple chat interface available online.
CEOs, CFOs, CROs go home for the holidays and are wowed by early-stage GenAI - making Taylor Swift rap like Eminem, summarizing emails, chatting about travel plans. Impressed, they unlock IT budget only for GenAI pet projects in 2023.
2023: pet projects, experimentation. The only new budget was in GenAI, so that’s where all IT teams focused.
2024: the great culling of 90% of GenAI pet projects not being promising, and the 10% that were starting to go through GRC for deployment.
2025: applications go into production, with varying levels of guardrailing, cost tracking, and ROI measurement. (Also, agentic coding becomes real in late 2025 - so product deployment velocity increases.)
2026: internal and external usage of GenAI in production explodes. Annual budgets are blown away in months or less. Concerns around system and data ownership increase with sovereign AI discussions and increased government involvement with frontier labs.
Put simply, we’ve moved from "should we experiment with AI?" to "why isn't this in production yet?" to “what’s the ROI, and my lord how much did that cost?!, and where did my data go?!.”
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