Google Makes AI Usage a Factor in Performance Reviews for Non-Technical Staff

Google is rolling out a broad "work style transformation" across the company. Recently, management has explicitly told certain non-technical employees that they need to integrate AI tools into their daily tasks, and AI usage will now be a formal part of the annual performance review.
This shift positions AI as a "core productivity tool" rather than an "optional extra." Before, Google mandated AI-assisted programming for software engineers, and now roughly 50% of the code inside the company is AI-generated and then reviewed by human developers.
How AI use is required for different roles:
Software Engineers are expected to use in-house AI coding tools like Goose (trained on Google's technical history) for writing code, troubleshooting, and maintaining codebases.
Non-Technical Roles need to leverage AI for drafting strategic documents, analyzing sales conversations, and extracting customer insights.
Sales Teams must use internal AI tools to log call notes, with some members needing to hit weekly AI usage targets, and even employing AI avatar tools like Yoodli for practicing customer interactions.
For data security, Google workers primarily rely on custom-built internal AI tools. One example is Duckie, an internal version of Gemini that can respond to queries using the company's sensitive documents without risk of leakage.
Google CEO Sundar Pichai has said that given competitors' heavy internal AI adoption, Google needs to keep pace. Now, AI usage is tied to performance via the GRAD (Googler Reviews and Development) system, meaning an employee's proficiency with AI directly influences their career trajectory at Google.
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Google is rolling out a broad "work style transformation" across the company. Recently, management has explicitly told certain non-technical employees that they need to integrate AI tools into their daily tasks, and AI usage will now be a formal part of the annual performance review.
This shift positions AI as a "core productivity tool" rather than an "optional extra." Before, Google mandated AI-assisted programming for software engineers, and now roughly 50% of the code inside the company is AI-generated and then reviewed by human developers.
How AI use is required for different roles:
Software Engineers are expected to use in-house AI coding tools like Goose (trained on Google's technical history) for writing code, troubleshooting, and maintaining codebases.
Non-Technical Roles need to leverage AI for drafting strategic documents, analyzing sales conversations, and extracting customer insights.
Sales Teams must use internal AI tools to log call notes, with some members needing to hit weekly AI usage targets, and even employing AI avatar tools like Yoodli for practicing customer interactions.
For data security, Google workers primarily rely on custom-built internal AI tools. One example is Duckie, an internal version of Gemini that can respond to queries using the company's sensitive documents without risk of leakage.
Google CEO Sundar Pichai has said that given competitors' heavy internal AI adoption, Google needs to keep pace. Now, AI usage is tied to performance via the GRAD (Googler Reviews and Development) system, meaning an employee's proficiency with AI directly influences their career trajectory at Google.
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