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The narrative around enterprise AI is shifting. After years of broad promises and experimental pilots, organizations are recalibrating. They're asking harder questions about ROI, abandoning tools that don't deliver, and doubling down on use cases that prove their value within weeks, not quarters.
Our recent Enterprise AI survey of 1,000+ professionals across the US, UK, and Canada revealed something striking: 70% of companies plan to invest over $10 million in AI over the next 12 months. Yet nearly half struggle to measure any return on those investments. The disconnect between AI spending and AI outcomes has never been clearer.
But there's a bright spot. Document AI achieved 95% adoption among executives and 75% among employees, with quantifiable productivity gains totaling $26 million annually for a 1,000-person organization. When AI solves a specific problem with measurable results, adoption isn't a challenge. It's inevitable.
We sat down with Nitro's leadership team to get their take on what 2026 holds for enterprise AI. Their predictions point to four defining shifts that will separate AI winners from AI skeptics.
From experimentation to consolidation
The era of unlimited AI pilots is over.
"I think over the past couple of years, there's been a big embrace of new technologies, new tools that people have been testing and trialling and allowed employees to spend money on in organizations to see what fits for them," says Dave Andreasson, Nitro's Chief Financial Officer.
Organizations are tired of managing fragmented tool stacks. They're moving past the "let's try everything" phase and into the "let's commit to what works" phase. Budget that once funded dozens of experimental AI projects will now fund enterprise-wide deployments of tools that have already proven their worth.
This consolidation reflects a broader maturity in how companies think about AI. Early adopters tested everything. Now they're picking winners.
"Eventually organizations are going to consolidate around their chosen one or two that actually add proper efficiency benefit to that organization," Andreasson continues. "And I think you'll see a consolidation of spend around a couple of key winners in the AI space."
The survey data backs this up. While 61% of companies have already invested over $10 million in AI, adoption rates vary wildly depending on the tool. Companies are starting to realize that more AI doesn't mean better outcomes. Focused AI does.
ROI over hype
For the past two years, AI has been sold on its potential. In 2026, enterprises will demand more.
"Our recent Enterprise AI survey revealed that 70% of companies plan to invest over $10 million in AI over the next 12 months," says Michele Jefferson, Nitro's Chief Marketing Officer. "However, nearly half of these enterprises struggle to measure ROI. The breakthrough use case from our survey document AI Tools shows 95% adoption, with millions in quantifiable productivity value. That gap reveals an opportunity."
The difference between document AI and other enterprise AI tools is stark. Document AI users save over 9 hours per week on document tasks. That translates to a 5-6 month payback period and a 2.5x ROI thereafter. Organizations can measure exactly what they're getting and when they'll break even.
Compare that to broad "AI transformation" initiatives that promise enterprise-wide change but deliver ambiguous results. Without clear metrics, these projects stall. Teams lose confidence. Budgets dry up.
The AI market is projected to exceed $1 trillion by 2031. Document processing with 95% adoption demonstrates that purpose-built AI integrated into platforms that users already trust drives value, high adoption, and measurable ROI at scale. That's the blueprint for enterprise AI success.
Integration over innovation
The most successful AI in 2026 will likely be the most invisible.
"In 2026, organizations will move past experimenting with AI and the cautious rollout to start treating it as a critical implementation detail of the tools that people are already using every day," says John Fitzpatrick, Nitro's Chief Technology Officer.
This shift matters because it changes how companies evaluate AI tools. Instead of asking "What can this AI do?", they're asking "Does this fit into our existing workflows?"
The survey revealed that 96% of executives and 82% of employees use AI for work at least weekly. But that usage is concentrated in tools that integrate naturally into their daily routines. When AI requires behavioral change or a separate login, adoption suffers. "Bigger is not always going to mean better," says Garret La Cava, Nitro's SVP of Global Sales.
Document AI succeeded where other enterprise tools failed because it solved a problem people were already trying to solve. Employees were already extracting data from PDFs, redacting sensitive information, and pulling tables into spreadsheets. AI just made those tasks faster. It didn't require them to adopt new software, change their workflows, or sit through hours of training.
The usability imperative
The survey found that 68% of executives feel pressure to deliver better AI tools, yet 57% of employees feel little or no pressure to use them. That gap doesn't exist because employees don't understand AI. It exists because the tools aren't worth the effort.
Meanwhile, 68% of executives and 50% of employees are using unapproved consumer AI tools to fill the gaps. One in three employees has processed confidential data through unvetted platforms. The security risks are real. But so is the message: if enterprise AI doesn't work, employees will find something that does.
"Nitro's going to step in by integrating these workflows into a very commonly used tool to help them maximize what they're looking to achieve," La Cava says.
This isn't about adding more features. It's about reducing complexity. The AI tools that win in 2026 will be the ones that require the least explanation. They'll solve problems immediately, without setup, without onboarding, and without disrupting existing workflows.
Document AI achieved near-universal adoption not because organizations trained employees on how to use it, but because employees could figure it out in minutes. The interface was intuitive. The value was immediate. The learning curve was nonexistent.
What this means for organizations
The AI market is at an inflection point: Companies have invested heavily. They've run pilots. They've tested dozens of tools. Now they're making decisions about which ones stay and which ones go.
The organizations that succeed will be the ones that stop chasing AI for its own sake and start investing in AI that delivers measurable outcomes within 90 days. They'll prioritize tools that fit into existing workflows rather than requiring employees to adopt new ones. And to avoid shadow AI concerns, they'll demand enterprise-grade security and governance from day one.
As Nitro's survey data shows that 96% of executives and 79% of employees believe AI will improve business performance. We can see the belief in AI's potential is nearly universal, but it’s real application and execution that will drive meaningful business results.
Want to see what the data reveals? Read our Enterprise AI Report to explore the full survey findings on adoption, ROI, and what separates successful AI implementations from the rest.
