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This article is part of our Opinions section, where we invite industry professionals to share their views on the most pressing technology questions of our time.
2026 is going to hurt. After years of pouring money into AI solutions that promised transformation and delivered disappointment, service-based businesses are facing a wake-up call. Mass layoffs are coming across sectors like customer service, finance operations, and outsourcing. While job losses are never something to celebrate, they will expose a broader, uncomfortable truth: The jobs that will be eliminated simply aren’t adding enough value.
Job cuts won’t hit work that actually moves the needle, only the roles that have existed to compensate for broken operations. The reality is that businesses are about to discover that the productivity gains they banked on aren’t coming, the staff cuts they made were premature, and the only way forward is the work they should have done first, fixing the broken operations underneath.
Over the last few years, businesses have convinced themselves that AI will quietly shoulder their operational workload. They’ve invested heavily, made bold productivity assumptions, and in some cases cut staff early in anticipation of efficiency gains that still haven’t arrived.
What they’re about to discover should have been obvious from the start. You can’t automate your way out of operational chaos. AI tools deployed onto broken, invisible workflows don’t fix anything. The AI hangover is coming.
The problem was never the technology. It was the shortcuts. Most organisations skipped the unglamorous work of understanding their own operations. They don’t know what work is actually being done, by whom, or why. They can’t answer basic questions like where bottlenecks form or what truly slows delivery. In that environment, automation was always doomed to underwhelm.
Service businesses will cut costs this year and eliminate roles, and we’re going to see a pattern emerge. Much of the work disappearing will turn out to have only existed to paper over operational dysfunction.
Teams are manually routing emails because there’s no triage. People re-keying data between systems that should already talk to each other. Layers of middle management coordinating work that could be automatically assigned.
This work has created the appearance of productivity while gobbling up time and budget. The question everyone will finally ask is: In 2026, why did this manual exist at all? Because no one ever fixed the underlying problems.
There’s a gap between what leaders think happens operationally and what actually happens. For years, process maps have documented neat workflows, clean handoffs, and end-to-end journeys. But those diagrams rarely match the messy reality. The real work lives in inboxes, spreadsheets, and constant human firefighting that never gets captured.
That gap is what I call process debt. Each workaround and manual fix adds to the disconnect between documented processes and real operations. Eventually, it becomes a serious liability.
It’s also why the next wave of automation is going to fail. Agentic AI needs structure and clarity to work. It can’t function where no one understands what work exists or why it exists. Businesses that haven’t addressed their process debt will watch their AI investments deliver zero ROI, over and over again.
Another big change coming is who controls technology decisions. The traditional model, where central IT teams gatekeep every tool and system, is breaking down. It’s too slow and too disconnected from operational reality.
The most resilient service businesses will put technology decisions in the hands of people who deal with operational challenges every day. The customer service leaders, finance operations specialists, and workflow heads. Modern platforms have lowered the barrier to entry. You don’t need technical expertise to deploy effective solutions anymore. Citizen development puts the technology into the hands of the people, often with no need for expensive coding or development.
CIOs who cling to the old ways will see their influence fade. Those who focus on governance, security, and standards while giving their teams license to improve operations will become invaluable.
“AI-powered” alone isn’t enough to sell licenses. After years of unmet promises, no one’s impressed by slick demos or vague claims anymore. AI is a piece of the puzzle, not the full picture. Any AI claims will need to be backed up with hard numbers and results.
Operational leaders are going to ask hard questions before buying anything new. How much manual work does this actually remove? What’s the real cost saving? Can you prove the value with actual customer data?
Technologies that deliver measurable impact and focus on solving real business problems will win.
Service businesses face a clear choice in 2026. Do the hard work, fix operational foundations and automate deliberately. Or keep doing what you’ve always done and get left behind. The service businesses that survive will be the ones that stop chasing shiny AI tools and finally get their operations in order. The race is on.
