Data consultant warns that AI hype is masking real business problems—most projects don't need machine learning at all.

What happened: Nikhil Suresh, a data consultant in Melbourne, published a blog post criticizing the overuse of AI in corporate environments. He argues that most projects billed as AI work are actually 98% web development, DevOps, or stakeholder management—and that executives promote AI solutions because they are perceived as career-advancing, not because they solve business problems effectively.

Why it matters: For 30 years, automation tools have existed but remained underutilized in non-technical companies. The current wave of AI enthusiasm is selling the idea of magic solutions to complex problems, but Suresh observes that actual delivered value remains elusive. Clients are being promised untold efficiencies, yet layoffs attributed to AI automation have not resulted in workers reporting permanent job loss—instead, they expect to be rehired once executives reconsider.

What to watch: Suresh's consultancy deliberately avoids AI work despite half the team holding postgraduate degrees in data science–related fields, choosing instead to focus on concrete infrastructure and process problems. His experience suggests that the gap between AI promises and real business delivery will likely persist as long as executives view AI as a career-advancement tool rather than a means to solve specific, measurable problems.