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 workforce 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 workforce that replicate the place AI is headed, and what organizations like yours might want to prioritize as ambition provides approach to execution.
AI Infrastructure is Accelerating – However Knowledge 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. However it’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 info it’s given. From my perspective, that shift raises the bar considerably. With out a technique for Agentic-Prepared Knowledge, organizations danger amplifying incorrect data, information bias, and poor outcomes pushed by inconsistent or poorly ruled information. And right this moment, 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, count on 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 data – it’s understanding the world wherein that data exists. Knowledge with out context limits how successfully AI can motive, interpret, and act.
Throughout our management workforce, there’s sturdy 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 are extra correct, explainable, and related to real-world circumstances.
Right here’s what a few of our Exactly leaders should say.
Tendü Yoğurtçu, PhD
Chief Expertise Officer
“As we transfer into 2026, geospatial information will play an more and more crucial function in AI coaching, shaping how techniques understand, interpret, and work together with the world round them. The present actuality is that giant language fashions are skilled on publicly accessible information, data 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 way 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 data gaps the place information is incomplete, providing a extra goal, full, and verifiable view of real-world circumstances. When mixed with a company’s personal proprietary information, equivalent to buyer data, transaction patterns, or operational indicators, geospatial information creates a robust basis for differentiated insights and lasting aggressive benefit.”
Andy Bell
Senior Vice President, World Knowledge Product Administration
“In 2026 we may see speedy development within the agentic AI workforce with adoption anticipated to develop 327% by 2027. Nonetheless, attaining the total advantages and efficiencies of those AI staff might be hampered by a scarcity of knowledge readiness.
At the moment, solely 12% of organizations report that their information is of enough high quality and accessibility for AI. This can solely be heightened by agentic AI techniques which function independently by planning, reasoning, and taking actions in the direction of objectives with minimal human intervention.
As these techniques depend on complicated 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 affords an expanded perspective on information, offering insights into locations, folks, and behaviors. With out understanding the context behind your information, it will likely be tough to find out a nuanced and wealthy understanding of how agentic AI techniques are reaching their outputs. It’s crucial to have an understanding of this to make sure that agentic AI techniques are making absolutely knowledgeable, assured choices on behalf of your online business.”
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Knowledge Integrity Turns into the Working System for AI Governance and Belief
As AI techniques change into extra autonomous and extra embedded in crucial 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 consider the way to govern AI responsibly within the 12 months forward, right here’s what our management workforce believes will matter most.
Dave Shuman
Chief Knowledge Officer
“In 2026, semantics shall be a very powerful AI governance guardrail. Coaching AI is akin to managing well-intentioned interns. AI fashions could also be sensible and succesful, however like every agent – human or in any other case – they nonetheless require clear course, oversight, and constant analysis.
Including a semantic layer transforms complicated 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 folks and assets wanted to construct the semantic layer, with a purpose to make sure that the enter information instantly aligns with the specified, measurable outputs.”
Jean-Paul Otte
Knowledge Technique Lead
“2026 is the 12 months when AI readiness frameworks shall be reframed round information 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.
Knowledge 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 information and metadata accountability.
The organizations that achieve 2026 shall 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 obligations, the message is constant: the way forward for AI shall 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 shall 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 workforce. They’ll present the skilled steerage you might want to responsibly scale and succeed along with your AI initiatives this 12 months and past.
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