Pressure on productivity is reshaping how the world’s largest technology companies manage their workforces, with employee monitoring expanding in scope and sophistication through 2026 as firms pour billions into artificial intelligence. Tracking software, data-driven performance scoring and stricter return-to-office policies are becoming central tools for executives seeking to justify rising AI capital expenditure while navigating uneven growth and heightened competition.Workplace surveillance in the technology sector is not new, but the intensity and granularity have shifted. Large employers have broadened digital monitoring from basic security logging to continuous analysis of keystrokes, application usage, internal messaging patterns and even physical movement within offices. AI systems are increasingly used to flag “anomalous” behaviour, predict attrition risk and rank productivity at an individual level, often with limited transparency for staff.
Amazon has continued to refine systems that track warehouse and corporate employees alike, using automated metrics to assess task completion, collaboration time and compliance with internal processes. In its logistics operations, such monitoring has long been embedded, but similar principles are now influencing white-collar roles as the company pushes to extract efficiencies from cloud and AI investments. Managers say the aim is consistency and accountability; critics argue it blurs the line between performance management and constant surveillance.
Meta has also tightened oversight as it channels resources into AI infrastructure, including data centres and proprietary models. Internal policies increasingly link performance evaluations to in-office presence and quantified outputs, a shift that follows broader mandates requiring employees to spend more days on site. Executives have framed these measures as necessary to improve coordination and speed in product development, particularly as competition in generative AI intensifies.
Across the sector, return-to-office rules have become intertwined with monitoring. Office attendance is tracked through badge data and network logins, feeding into dashboards that managers use to assess engagement. Hybrid work, once promoted as a benefit, is being recalibrated with clearer expectations and consequences for non-compliance. For employees, this has altered the psychological contract formed during the pandemic years, when flexibility was widely presented as permanent.
The expansion of surveillance has prompted growing concern among labour advocates and privacy experts. Continuous data collection can create detailed behavioural profiles, raising questions about consent, proportionality and data security. While companies argue that monitoring focuses on work activity rather than personal life, the boundary can be thin when tools analyse communication patterns or time spent online. Employees in multiple firms report heightened stress and a sense of mistrust, factors that can undermine morale and retention in an industry reliant on scarce talent.
Ethical debates are sharpening as AI systems play a larger role in decision-making. Automated performance scoring can embed bias if training data reflect existing inequalities, potentially disadvantaging certain groups. There is also concern about over-reliance on quantitative metrics that fail to capture creative or collaborative contributions, leading to narrow definitions of productivity. Scholars studying organisational behaviour warn that excessive monitoring may deliver short-term gains while eroding intrinsic motivation over time.
Regulators are beginning to scrutinise these practices more closely. Data protection authorities in Europe have signalled that workplace monitoring must meet strict necessity and transparency standards under existing privacy law. In the United States, although federal rules are less prescriptive, state-level proposals and union-backed initiatives are pushing for clearer disclosure and limits on digital surveillance. The regulatory landscape remains fragmented, creating uncertainty for multinational employers operating across jurisdictions.
From a corporate perspective, the drive to monitor is closely tied to financial pressure. Massive AI investments demand measurable returns, and executives face shareholder expectations to demonstrate efficiency gains. Monitoring tools offer a way to quantify output and identify redundancies, particularly after waves of layoffs that have left leaner teams under pressure to deliver more. Yet analysts caution that productivity improvements attributed to surveillance are difficult to isolate from broader organisational changes.