Tech Workers Invest Nights Learning New AI Tools

Business Insider reports that many tech workers are spending nights and weekends learning and experimenting with AI tools to avoid falling behind. Business Insider profiles Maahir Sharma, a 24-year-old software engineer at a Big Tech company, who says AI has dramatically sped some work and that he spends about 20 hours a week outside work experimenting with tools such as Cursor, which he pays for out of pocket. The article cites the EY Agentic AI in the Workplace Survey (Oct 2025), which polled 1,148 US desk workers across six industries at companies with $1B+ in annual revenue. Key EY finding: 85% of desk workers were learning how to work alongside AI agents outside of work, and 83% said most of what they know about agentic AI is self-taught -- amid a reported lack of adequate employer training. Business Insider also cites LinkedIn data showing AI-related skills now top the fastest-growing skills list for 2026, with sustained demand for AI engineers across industries.

The story documents a widespread pattern of unpaid upskilling driven by worker anxiety about being left behind. The EY survey found 54% of desk workers feel they are falling behind peers in agentic AI use at work, and 56% worry about their own job security working alongside AI agents. This tension -- enthusiasm paired with anxiety and a perceived lack of employer support -- is shaping how practitioners actually acquire AI skills: through after-hours hands-on projects, self-funded tools like coding assistants, and self-directed experimentation rather than formal employer programs. EY found only 52% of senior leaders say their organization has a fully deployed agentic AI training initiative.

LinkedIn's Skills on the Rise 2026 report (Feb 2026) identifies AI engineering, prompt engineering, and model development as among the fastest-growing skills across 12 global markets. Industry-pattern observations suggest that when employer-provided training lags adoption demand, workers absorb the cost in unpaid hours -- raising questions about access equity and burnout, particularly for those without employer-sponsored tool access or learning budgets.

Indicators to follow include employer-provided AI training adoption rates, out-of-pocket vs. employer-funded tooling costs, and AI-role hiring composition on major platforms. Whether large employers begin funding structured agentic AI upskilling will materially affect which workers can participate in rapid skill transitions.