The growing divide over who pays for AI upskilling

Larry Gadea, founder of software firm Envoy, encourages his staff to experiment with AI during company meetings, yet he remains firm that personal initiative is mandatory. For Gadea, the rapid evolution of technology means that learning must happen regardless of the clock. This perspective mirrors a broader struggle: as AI reshapes software development and other sectors, the traditional boundaries of professional development are blurring.

RJ Bannister, COO at Farient Advisors, notes that historically, 60% of workplace learning has been self-directed. He suggests that AI could accelerate this, provided employees treat the tech as a tool for growth rather than a threat. However, Kathy Gersch of the consultancy Kotter warns that formal, periodic training is becoming obsolete. With AI capabilities shifting monthly, companies that rely on static, quarterly sessions are failing to keep pace. Instead, she advocates for peer-to-peer knowledge sharing systems that prioritize adaptability over rigid coursework.

At firms like GoDark, the approach is more informal; employees are often thrown into the deep end, learning by doing rather than through structured modules. While some CEOs, like Denis Dariotis, avoid mandating after-hours study to prevent burnout, the underlying pressure remains. Mark Ma, a professor at the University of Pittsburgh, argues that the current disconnect stems from generic corporate training that fails to translate to specific job roles. Ultimately, the burden of relevance is shifting: workers increasingly view AI proficiency as a portable asset, while bosses view it as a necessary condition for staying competitive in a volatile market.