New 12 months, new conversations about AI. As 2026 begins, AI has moved from experimentation to execution, and expectations are rising simply as quick. Boards are investing, and clients are pushing for actual outcomes. The query is now not if organizations will spend money on AI, however how they’ll flip that funding into sturdy, long-term worth.
Over the previous 12 months, I’ve had numerous discussions with our Exactly management group about what they’re seeing throughout industries, areas, and buyer environments. Whereas their views come from totally different disciplines, a transparent set of themes retains rising.
Under are a number of insights from myself and our management group that replicate the place AI is headed, and what organizations like yours might want to prioritize as ambition offers strategy to execution.
AI Infrastructure is Accelerating – However Knowledge is The place AI Worth Compounds
The tempo of AI funding has been extraordinary. Firms are pouring billions into AI infrastructure to fulfill the capability calls for of the AI second. But it surely’s clear that the following chapter of AI gained’t be outlined by sooner fashions or greater investments – it will likely be outlined by information readiness. Accuracy, consistency, and context will decide whether or not AI delivers actual outcomes, and governance will decide whether or not organizations can belief what AI produces at scale.
Nonetheless, with the doorway of agentic AI, this problem is exponentially compounded. It’s now not about decision-making, alone. Agentic AI plans, causes, and acts primarily based on the information it’s given. From my perspective, that shift raises the bar considerably. With out a technique for Agentic-Prepared Knowledge, organizations threat amplifying incorrect info, information bias, and poor outcomes pushed by inconsistent or poorly ruled information. And immediately, many enterprises merely aren’t prepared.
As additional proof of this shift, in 2025 we started to see a number of high-profile acquisitions of knowledge firms signaling a rising focus past infrastructure alone. In 2026, anticipate to see that consolidation speed up.
Contextual Knowledge Will Outline How Intelligently AI Operates at Scale
As AI techniques develop extra succesful, the problem is now not simply processing info – it’s understanding the world by which that info exists. Knowledge with out context limits how successfully AI can motive, interpret, and act.
Throughout our management group, there’s robust alignment across the function of contextual information in shaping AI’s subsequent chapter. Context doesn’t simply enhance outputs; it helps AI techniques make choices which might be extra correct, explainable, and related to real-world situations.
Right here’s what a few of our Exactly leaders must say.
Tendü Yoğurtçu, PhD
Chief Expertise Officer
“As we transfer into 2026, geospatial information will play an more and more important function in AI coaching, shaping how techniques understand, interpret, and work together with the world round them. The present actuality is that enormous language fashions are educated on publicly obtainable information, info that’s finite in quantity and infrequently restricted in accuracy and illustration. This rising “information drought” dangers slowing innovation but additionally presents a strategic alternative to unlock worth by means of proprietary and curated information.
Geospatial intelligence, together with satellite tv for pc imagery, GPS coordinates, and different location-based insights, introduces a brand new dimension of context. It helps fill info gaps the place information is incomplete, providing a extra goal, full, and verifiable view of real-world situations. When mixed with a corporation’s personal proprietary information, akin to buyer info, transaction patterns, or operational alerts, geospatial information creates a strong basis for differentiated insights and lasting aggressive benefit.”
Andy Bell
Senior Vice President, International Knowledge Product Administration
“In 2026 we may see fast development within the agentic AI workforce with adoption anticipated to develop 327% by 2027. Nonetheless, attaining the complete advantages and efficiencies of those AI staff might be hampered by an absence of knowledge readiness.
At the moment, solely 12% of organizations report that their information is of enough high quality and accessibility for AI. This may solely be heightened by agentic AI techniques which function independently by planning, reasoning, and taking actions in the direction of targets with minimal human intervention.
As these techniques depend on advanced processes, agentic-ready information is vital to making sure correct outputs. Attaining true information integrity requires contextual information together with information integration, information governance, and information enrichment.
Contextual information gives an expanded perspective on information, offering insights into locations, individuals, and behaviors. With out understanding the context behind your information, it will likely be troublesome to find out a nuanced and wealthy understanding of how agentic AI techniques are reaching their outputs. It’s important to have an understanding of this to make sure that agentic AI techniques are making absolutely knowledgeable, assured choices on behalf of what you are promoting.”
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Knowledge Integrity Turns into the Working System for AI Governance and Belief
As AI techniques develop into extra autonomous and extra embedded in important enterprise choices, the query of belief strikes entrance and middle. In 2026, governance gained’t be one thing organizations layer on after deployment – it will likely be constructed into how information is structured, interpreted, and monitored from the beginning.
Knowledge integrity will function the working system for accountable AI. From semantic readability and explainability to compliance, auditability, and management over AI-generated information, integrity will decide whether or not AI can scale safely and ship lasting worth.
As you concentrate on how one can govern AI responsibly within the 12 months forward, right here’s what our management group believes will matter most.
Dave Shuman
Chief Knowledge Officer
“In 2026, semantics can be an important AI governance guardrail. Coaching AI is akin to managing well-intentioned interns. AI fashions could also be good and succesful, however like several agent – human or in any other case – they nonetheless require clear course, oversight, and constant analysis.
Including a semantic layer transforms advanced information right into a business-friendly format that’s extra digestible, serving to AI interpret and translate information into dependable output.
As AI conversations shift from implementation to purposeful motion in 2026, leaders will prioritize the individuals and assets wanted to construct the semantic layer, with the intention to be sure that the enter information immediately aligns with the specified, measurable outputs.”
Jean-Paul Otte
Knowledge Technique Lead
“2026 is the 12 months when AI readiness frameworks can be reframed round information integrity-first rules. Organizations will transfer away from remoted AI pilots and in the direction of repeatable, data-driven frameworks that guarantee AI is deployed responsibly and at scale.
Knowledge maturity assessments and AI governance applications will more and more revolve round verifying the supply, high quality, and trustworthiness of knowledge belongings earlier than any AI mannequin is developed or deployed. AI readiness would require a decentralized working mannequin regarding information and metadata accountability.
The organizations that reach 2026 can be people who embed integrity into each layer of their working mannequin, from function definitions and management frameworks to coaching and steady monitoring. In doing so, they won’t solely meet regulatory expectations however unlock AI that’s dependable, explainable, and able to delivering long-term worth.“
Turning AI’s Potential into Outcomes – With Trusted Knowledge
What strikes me most about these views isn’t how totally different they’re — it’s how intently they align. Throughout roles, areas, and tasks, the message is constant: the way forward for AI can be constructed on trusted information, grounded in context, and ruled with intention.
As we transfer into 2026, the organizations that succeed gained’t simply be those that undertake AI quickest. They’ll be those that make investments thoughtfully within the information foundations that make AI – notably agentic AI – dependable, explainable, and resilient over time.
That’s the place the following chapter of AI worth can be written – and it’s a problem I imagine many organizations are prepared to fulfill.
How will you strengthen your information basis for AI in 2026? For help in constructing a sensible, tailor-made roadmap to your group, I encourage you to achieve out to our Knowledge Technique Consulting group. They’ll present the knowledgeable steering you might want to responsibly scale and succeed together with your AI initiatives this 12 months and past.
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