AI 2026: a maturity test?
Practical implementation, tighter cost tracking and better quality. We’re heading into a year where what matters isn’t AI’s technological promises, but whether it makes sense to use it and whether organizations can actually transform.
After a period of intense experimentation, organizations are cutting back their AI projects to the ones that actually make money or save time. McKinsey data shows that the biggest hurdle isn’t access to models anymore, but weaving AI into how companies’ real operations: its processes, decisions and day-to-day life.
So that means the era of scattered “because everyone’s doing AI” initiatives is over. Only use cases you can run day to day and that make financial sense will stick. That shakeout will drive AI’s growth in 2026.
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