New yr, 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 not if organizations will spend money on AI, however how they’ll flip that funding into sturdy, long-term worth.
Over the previous yr, 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 completely different disciplines, a transparent set of themes retains rising.
Beneath are a number of insights from myself and our management group that mirror 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 satisfy 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 greater investments – it is going to 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.
Nevertheless, with the doorway of agentic AI, this problem is exponentially compounded. It’s 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 no technique for Agentic-Prepared Information, organizations danger amplifying incorrect data, information bias, and poor outcomes pushed by inconsistent or poorly ruled information. And at present, 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 corporations 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 methods develop extra succesful, the problem is not simply processing data – it’s understanding the world during which that data 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 information in shaping AI’s subsequent chapter. Context doesn’t simply enhance outputs; it helps AI methods make choices which can be extra correct, explainable, and related to real-world situations.
Right here’s what a few of our Exactly leaders should say.
Tendü Yoğurtçu, PhD
Chief Know-how Officer
“As we transfer into 2026, geospatial information will play an more and more crucial function in AI coaching, shaping how methods understand, interpret, and work together with the world round them. The present actuality is that giant language fashions are educated on publicly obtainable 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 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 data 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, comparable to buyer data, transaction patterns, or operational alerts, geospatial information creates a strong basis for differentiated insights and lasting aggressive benefit.”
Andy Bell
Senior Vice President, World Information Product Administration
“In 2026 we might see speedy development within the agentic AI workforce with adoption anticipated to develop 327% by 2027. Nevertheless, reaching the total advantages and efficiencies of those AI employees could possibly be hampered by a scarcity of knowledge readiness.
At present, solely 12% of organizations report that their information is of enough high quality and accessibility for AI. It will solely be heightened by agentic AI methods which function independently by planning, reasoning, and taking actions in the direction of objectives with minimal human intervention.
As these methods depend on advanced processes, agentic-ready information is essential to making sure correct outputs. Attaining true information integrity requires contextual information together with information integration, information governance, and information enrichment.
Contextual information presents an expanded perspective on information, offering insights into locations, individuals, and behaviors. With out understanding the context behind your information, it is going to be troublesome to find out a nuanced and wealthy understanding of how agentic AI methods are reaching their outputs. It’s crucial to have an understanding of this to make sure that agentic AI methods are making totally knowledgeable, assured choices on behalf of your small business.”
A complete vary of knowledge technique consulting choices delivered by seasoned information consultants, tailor-made to your particular necessities, and centered on delivering measurable outcomes and reaching your goals.
Information Integrity Turns into the Working System for AI Governance and Belief
As AI methods change into extra autonomous and extra embedded in crucial enterprise choices, 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 information 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 information, integrity will decide whether or not AI can scale safely and ship lasting worth.
As you concentrate on easy methods to govern AI responsibly within the yr forward, right here’s what our management group believes will matter most.
Dave Shuman
Chief Information 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 sensible and succesful, however like every agent – human or in any other case – they nonetheless require clear path, 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 a purpose to be certain that the enter information straight aligns with the specified, measurable outputs.”
Jean-Paul Otte
Information Technique Lead
“2026 is the yr 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.
Information maturity assessments and AI governance applications will more and more revolve round verifying the provision, 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 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 Information
What strikes me most about these views isn’t how completely different they’re — it’s how intently they align. Throughout roles, areas, and duties, 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 received’t simply be those that undertake AI quickest. They’ll be those that make investments thoughtfully within the information foundations that make AI – significantly agentic AI – dependable, explainable, and resilient over time.
That’s the place the subsequent chapter of AI worth can be written – and it’s a problem I imagine many organizations are prepared to satisfy.
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 succeed in out to our Information Technique Consulting group. They’ll present the professional steering you must responsibly scale and succeed together with your AI initiatives this yr and past.
