Silicon Valley is entering a new era of worker surveillance and accountability in 2026, as major tech companies implement sophisticated tracking systems to monitor employee productivity amid massive AI investments and widespread job cuts. Amazon and Meta are leading this shift with new performance monitoring tools that reflect growing pressure on workers to justify their value in an AI-driven economy.
Amazon has deployed dashboard systems that allow managers to track employee badge swipes and office attendance, reinforcing its return-to-office mandate. The company has also revised its performance review process, requiring corporate workers to provide three to five specific accomplishments that demonstrate their contributions. This represents a significant shift toward quantifiable, individual-based performance metrics.
Meta has taken a different but equally intensive approach, implementing dashboards specifically designed to track how employees are using AI tools in their daily work. The company is also simplifying its review structure with a “winner-take-more” philosophy that disproportionately rewards top performers. Additionally, Meta announced cuts of approximately 10% of workers in its metaverse division, signaling a strategic reallocation of resources.
These moves come as Big Tech companies pour billions into AI infrastructure while waiting for returns on those investments to materialize. According to Nitin Seth, cofounder and CEO of enterprise AI firm Incedo, AI coding assistants have boosted worker productivity by 25% to 40% at his company. However, Seth notes that many business leaders experienced a “sobering realization” by late 2025 that while early AI gains were impressive, achieving further productivity improvements has proven challenging.
The trend extends beyond Amazon and Meta. Microsoft has worked to shed its “country club” reputation, while Google has modified its employee rating system to incentivize exceptional performance. Even outside tech, Citi CEO Jane Fraser sent a memo titled “The bar is raised” to the bank’s 200,000+ employees, stating bluntly: “We are not graded on effort. We are judged on our results.”
Matthew Bidwell, a management professor at Wharton, suggests there’s “a mood of panic” among tech executives fearful of falling behind in the AI race, leading to the question: “How do we make sure we’re squeezing the most out of people?” The answer appears to be comprehensive metrics tracking through productivity dashboards, tool-usage monitoring, and increasingly granular performance evaluations.
Key Quotes
I suspect in a lot of tech firms, there is kind of a mood of panic
Matthew Bidwell, a management professor at the University of Pennsylvania’s Wharton School, describes the current mindset among tech executives who fear falling behind in the AI race, leading to increased pressure on workers to demonstrate productivity.
We are not graded on effort. We are judged on our results
Citi CEO Jane Fraser wrote this in a memo titled “The bar is raised” to the bank’s 200,000+ employees, exemplifying how the demand for measurable productivity extends beyond tech into traditional industries.
As that is happening, there is a squeeze on jobs
Nitin Seth, cofounder and CEO of Incedo, explains how AI-driven productivity gains of 25-40% are creating pressure to either produce more or cut jobs—often both simultaneously—as companies seek to justify their AI investments.
He came in. He fired everybody. It didn’t fall over
Wharton’s Bidwell describes the “Elon effect” following Musk’s takeover of Twitter, where massive staff cuts without operational collapse convinced investors that tech companies had pandemic-era bloat that could be eliminated, fundamentally shifting cultural attitudes about workforce size.
Our Take
This development reveals a troubling paradox at the heart of the AI revolution: the same technology promised to liberate workers is now being used to surveil them. While AI tools demonstrably boost productivity, companies are responding not by reducing workloads but by raising expectations and intensifying monitoring. The dashboard-driven approach to management represents a fundamental philosophical shift—from trusting professionals to do their jobs to requiring constant proof of value. What’s particularly striking is the gap between AI infrastructure spending and actual returns, which Seth likens to “building roads without cars.” This suggests companies may be using worker surveillance partly to deflect from questions about their own massive, potentially premature AI investments. The real test will be whether this surveillance culture actually drives innovation or simply accelerates burnout and talent flight to companies with healthier cultures. As AI capabilities mature, the question isn’t just whether workers can adapt to AI, but whether management can resist the temptation to use AI as a tool for oppressive oversight rather than genuine empowerment.
Why This Matters
This shift toward intensive worker monitoring represents a critical inflection point in how AI is reshaping workplace dynamics across the tech industry and beyond. As companies invest hundreds of billions in AI infrastructure, they’re facing mounting pressure from investors and boards to demonstrate tangible returns on those investments. The result is a fundamental change in the employer-employee relationship, where productivity is no longer assumed but must be continuously proven through data.
The implications extend far beyond Big Tech. As AI tools become more sophisticated and widespread, workers across industries will likely face similar scrutiny and performance expectations. The “Elon effect”—referencing Musk’s dramatic staff cuts at Twitter without operational collapse—has emboldened executives to question workforce size and productivity levels. This creates a challenging environment where workers must not only adopt AI tools but demonstrate measurable productivity gains to justify their positions. The trend also raises important questions about workplace surveillance, employee autonomy, and whether constant monitoring actually drives innovation or simply creates anxiety. As one expert noted, this pressure creates “a snowball effect” of anxiety cascading from executives to managers to rank-and-file workers.