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 put money into 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 provides solution to execution.
AI Infrastructure is Accelerating – However Information is The place AI Worth Compounds
The tempo of AI funding has been extraordinary. Corporations are pouring billions into AI infrastructure to fulfill the capability calls for of the AI second. Nevertheless it’s clear that the subsequent chapter of AI received’t be outlined by sooner fashions or larger investments – it is going to be outlined by knowledge 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 based mostly on the info it’s given. From my perspective, that shift raises the bar considerably. With no technique for Agentic-Prepared Information, organizations danger amplifying incorrect info, knowledge bias, and poor outcomes pushed by inconsistent or poorly ruled knowledge. And as we speak, 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 Information Will Outline How Intelligently AI Operates at Scale
As AI programs develop extra succesful, the problem is now not simply processing info – it’s understanding the world during which that info exists. Information with out context limits how successfully AI can motive, interpret, and act.
Throughout our management group, there’s sturdy alignment across the function of contextual knowledge in shaping AI’s subsequent chapter. Context doesn’t simply enhance outputs; it helps AI programs make selections which might be extra correct, explainable, and related to real-world situations.
Right here’s what a few of our Exactly leaders need to say.
Tendü Yoğurtçu, PhD
Chief Expertise Officer
“As we transfer into 2026, geospatial knowledge will play an more and more essential function in AI coaching, shaping how programs understand, interpret, and work together with the world round them. The present actuality is that enormous language fashions are skilled on publicly out there knowledge, info that’s finite in quantity and infrequently restricted in accuracy and illustration. This rising “knowledge drought” dangers slowing innovation but additionally presents a strategic alternative to unlock worth by way of proprietary and curated knowledge.
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 knowledge is incomplete, providing a extra goal, full, and verifiable view of real-world situations. When mixed with a company’s personal proprietary knowledge, corresponding to buyer info, transaction patterns, or operational alerts, geospatial knowledge creates a robust basis for differentiated insights and lasting aggressive benefit.”
Andy Bell
Senior Vice President, International Information Product Administration
“In 2026 we may see speedy progress within the agentic AI workforce with adoption anticipated to develop 327% by 2027. Nonetheless, reaching the complete advantages and efficiencies of those AI staff may very well be hampered by a scarcity of knowledge readiness.
At the moment, solely 12% of organizations report that their knowledge is of enough high quality and accessibility for AI. This may solely be heightened by agentic AI programs which function independently by planning, reasoning, and taking actions in the direction of targets with minimal human intervention.
As these programs depend on advanced processes, agentic-ready knowledge is vital to making sure correct outputs. Reaching true knowledge integrity requires contextual knowledge together with knowledge integration, knowledge governance, and knowledge enrichment.
Contextual knowledge presents an expanded perspective on knowledge, offering insights into locations, individuals, and behaviors. With out understanding the context behind your knowledge, it is going to be troublesome to find out a nuanced and wealthy understanding of how agentic AI programs are reaching their outputs. It’s essential to have an understanding of this to make sure that agentic AI programs are making totally knowledgeable, assured selections on behalf of your online business.”
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Information Integrity Turns into the Working System for AI Governance and Belief
As AI programs grow to be extra autonomous and extra embedded in essential enterprise selections, the query of belief strikes entrance and middle. In 2026, governance received’t be one thing organizations layer on after deployment – it is going to be constructed into how knowledge is structured, interpreted, and monitored from the beginning.
Information integrity will function the working system for accountable AI. From semantic readability and explainability to compliance, auditability, and management over AI-generated knowledge, integrity will decide whether or not AI can scale safely and ship lasting worth.
As you concentrate on methods to govern AI responsibly within the 12 months forward, right here’s what our management group believes will matter most.
Dave Shuman
Chief Information Officer
“In 2026, semantics shall be crucial AI governance guardrail. Coaching AI is akin to managing well-intentioned interns. AI fashions could also be sensible and succesful, however like all agent – human or in any other case – they nonetheless require clear route, oversight, and constant analysis.
Including a semantic layer transforms advanced knowledge right into a business-friendly format that’s extra digestible, serving to AI interpret and translate knowledge 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, as a way to be certain that the enter knowledge instantly aligns with the specified, measurable outputs.”
Jean-Paul Otte
Information Technique Lead
“2026 is the 12 months when AI readiness frameworks shall be reframed round knowledge integrity-first ideas. 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.
Information maturity assessments and AI governance packages 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 knowledge and metadata accountability.
The organizations that reach 2026 shall be those 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 Information
What strikes me most about these views isn’t how totally different they’re — it’s how intently they align. Throughout roles, areas, and duties, the message is constant: the way forward for AI shall be constructed on trusted knowledge, grounded in context, and ruled with intention.
As we transfer into 2026, the organizations that succeed received’t simply be those that undertake AI quickest. They’ll be those that make investments thoughtfully within the knowledge foundations that make AI – notably agentic AI – dependable, explainable, and resilient over time.
That’s the place the subsequent chapter of AI worth shall be written – and it’s a problem I imagine many organizations are prepared to fulfill.
How will you strengthen your knowledge basis for AI in 2026? For help in constructing a sensible, tailor-made roadmap in your group, I encourage you to achieve out to our Information 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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