As enterprises move beyond experimentation with artificial intelligence, 2026 is expected to mark a decisive shift in how organisations embed AI into everyday operations. In an interview, M-Files founder and chief innovation officer Antti Nivala shared six predictions that outline how AI will mature from pilot projects into a foundational capability for knowledge work.
Prediction one: AI pilot projects finally grow up
According to Nivala, the coming year will bring an end to isolated AI pilots that fail to deliver lasting value. “Leadership teams will no longer tolerate AI initiatives that live outside core business processes,” he said. Instead, organisations will prioritise production-ready deployments that improve decision-making and generate measurable outcomes. While this shift may expose overhyped investments, Nivala noted, “Real innovation emerges when organizations accept that AI success is not driven by clever models alone, but by data quality, governance, change management, and scalable operating models.”
Prediction two: AI unlocks the value of unstructured knowledge
Nivala believes AI’s most transformative impact in 2026 will not be content creation, but comprehension. “Enterprises are sitting on decades of unstructured information, research, contracts, project documentation, customer interactions, and intellectual property. Much of it remains underused not because it lacks value, but because humans cannot process it at scale,” he said. AI’s ability to enrich context and synthesise insights will allow organisations to unlock this hidden knowledge, marking what he described as “a decisive shift from information accumulation to organizational understanding.”
Prediction three: workers become directors of work
The interaction between employees and information is also set to change fundamentally. Nivala explained that “knowledge workers will spend far less time searching and far more time directing work through intent.” AI copilots will retrieve relevant information and suggest next steps, while humans retain responsibility for verification and decision-making. “Work becomes less about operating tools and more about orchestrating outcomes,” he added.
Prediction four: compliance becomes easier, not harder
Despite persistent concerns around AI risk, Nivala argued that automation will strengthen compliance outcomes. “Most compliance failures today originate from humans performing manual tasks inconsistently,” he said. When deployed with enterprise-grade guardrails, AI can handle governance tasks more consistently. The key shift, he noted, is pragmatic design: “The operating model becomes pragmatic and resilient. Trust, but verify.”
Prediction five: data quality defines competitiveness
By 2026, Nivala expects organisations to accept a hard truth: “AI value scales only as far as information quality allows.” Having more data will matter less than having well-governed, context-rich information. As a result, information readiness is becoming a board-level concern. “In the AI era, data quality is not hygiene. It is competitive advantage,” he said.
Prediction six: knowledge management becomes reality
Finally, Nivala said AI will push organisations beyond traditional information management. “AI enables systems that do more than store and retrieve documents. They understand them,” he explained. Employees will increasingly ask questions of collective organisational knowledge rather than search for files, representing “the most significant transformation in information work since the shift from paper to digital.”
Together, these six predictions point to 2026 as the year AI becomes essential rather than impressive, driven not by technology alone but by organisational readiness.
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