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Challenges of AI Adoption and Internal Innovation in Big Tech

🗓 2026年5月17日· 📚 精选词库 · 👀 4

You're just changing so much, and the turnover of the code is fast enough that you're rewriting it several times before you ship.

It's hard for many people to collaborate on the codebase compared to before, when the code velocity was slower.

In a bigger company, managing who has permission to access data all needs to be worked out.

Identity and access controls are real challenges, and we're working on them.

Security is a major concern, and that adds another layer on top of everything.

Once we solve these issues, we’ll bring the technology out in a more robust way, and people will be able to do much more.

Google reforecasts its business a few times each year.

A forecast is a snapshot in time, combining data from people's knowledge and what’s written down.

AI could potentially do a fully automated, no-human-in-the-loop forecast.

One advantage for startups is that they tend to have more AI-native teams, and might be able to integrate these tools more quickly.

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