AI is Easy. Impact is Hard.
Despite record investment and widespread deployment, the gap between AI adoption and real business value is widening and the leaders running these programs are struggling to keep up with it.
The AI Impact Imperatives, 2026 is our enterprise AI market report, built on insights from 467 senior leaders across G2K organizations in 10 countries.
The research maps exactly why AI impact is proving harder than AI adoption, where programs are failing and what the organizations closing that gap are doing differently.
Key Highlights
AI has moved beyond experimentation and is now embedded across IT operations, software development and physical environments, with Agentic AI becoming a foundational layer within enterprise technology stacks.
Market growth continues to outpace almost every other enterprise category, reinforcing AI’s central role in future competitiveness.
The question has shifted. It is no longer whether to adopt AI. It is why, at this scale of investment, impact is not keeping pace and what it will take to close that gap.
Business leaders are increasingly frustrated by the pace at which IT delivers high-impact AI initiatives. In contrast, IT leaders remain concerned about the risks of unsupervised or fragmented adoption by business teams.
The tension runs deeper than IT and business misalignment. At board level, AI failure is being systematically underestimated, in frequency, in risk and in the financial consequences of getting it wrong. That blind spot is costing organizations the window to lead.
Perspectives from Our Clients
We’ve just scratched the surface of AI’s potential. The sky’s the limit. The blocker in the pipeline of innovation is going to be how humans can imagine”
Kanda Natarajan
Vice President of IT
GSK
At the end of the day, only three metrics matter in business: revenue, cost and risk. If a provider cannot clearly articulate how a solution impacts at least one of those, then everything else is just noise.”
Corrado Azzarita
Global CIO
The Kraft Heinz Company
Automating the wrong applications or processes destroys value; application services must focus on pragmatic modernization tied to real business impact, not technology led automation."
Michael Löchle
Executive Advisor to the Chief Digital and Chief Security Officer
Hitachi, Ltd.
AI adoption is accelerating rapidly, with ASML aiming to embed AI across IT this year, but security and export control risks must be managed carefully."
Sven van Lieshout
Vice President of IT
ASML
AI will drive major business transformation, not just IT change, but success depends on close, integrated teams between internal staff and partners."
Dimitri Van Dyck
Director
Strategy and IT Governance
Achmea
The Impact Imperatives: Bridging the Ambition vs. Impact Gap
The Right Foundation
The Right AI Governance
The Right Partners
The Impact Imperatives
Organizations generating real AI impact don't treat these as separate workstreams. They treat them as a single program. Those that don't, consistently underperform those that do.
The Right Foundation. The Right Governance. The Right Partners. Miss one and the other two won't save you.
The Right Foundation
Over half of enterprise applications still run on architecture that was never designed for AI. That's not a technical footnote, it's a structural ceiling that limits what any AI initiative can achieve before it even reaches scale.
At the same time, only a small proportion of organizations have achieved a fully modernized data estate, despite broad recognition that data maturity is the primary determinant of model accuracy, scalability and Responsible AI compliance. Modernization isn't a future priority. It is the prerequisite for meaningful impact.
The Right AI Governance
Responsible AI has emerged as both a challenge and a differentiator, with security vulnerabilities and governance concerns now ranking among the top barriers to enterprise AI adoption. A majority of organizations have already delayed deployments due to these concerns, reflecting the complexity of balancing innovation with risk at scale.
But the research tells a more important story. The organizations that have embedded governance from the start aren't moving slower, they're moving faster, with greater stakeholder trust and less exposure. Responsible AI, designed into the architecture from day one, is not a constraint. It is the foundation of sustainable scale.
The Right Partners
Nine in ten organizations say external partners like system integrators are accelerating their time to value. But the research reveals something more specific - the right partner brings pre-validated use cases, cross-industry pattern recognition and accountability that doesn't stop at go-live.
Their influence is particularly evident in advanced domains such as Agentic AI and Physical AI, where organizations with experienced partners are more likely to move from experimentation to production. In these environments, the right partner isn't an advantage. It's the difference between piloting and scaling.
Perspectives from Our Leaders
AI has moved from being a technology initiative to becoming an enterprise operating reality. What leaders are grappling with now is not whether AI can deliver value, but how organizations adapt their structures, decision rights and risk tolerance to keep pace with it. The pressure to move fast is real, but without the right investment in people, in helping them understand, trust and work effectively alongside AI, speed can just as easily amplify failure as success."
Vijay Guntur
CTO & Head of Ecosystems
HCLTech
Every AI initiative is, at its core, a change management initiative. The technology is rarely what fails. What fails is the human architecture around it- the behaviors, the trust, the willingness to work differently."
Jill Kouri
Global Chief Marketing Officer
HCLTech
When half your application estate was built before the modern AI demands existed, you’re not just carrying technical debt - you’re operating under an AI performance ceiling. The shift comes when you realize the same AI that requires modern infrastructure is also the fastest way to build it. What once took four years can now take 12 months or less."
Pawan Vadapalli
Corporate Vice President and Global Head
Digital Business Services
HCLTech
AI is now deeply embedded across engineering, product development and manufacturing operations. However, as the data demonstrates, organizations achieving the greatest impact are those that treat AI as an engineering discipline, not a technology experiment. That rigor is what transforms proof of concepts into scalable, enterprise-grade systems."
Hari Sadarahalli
Corporate Vice President and Global Head
Engineering and R&D Services
HCLTech
We’re moving into a phase where enterprises will be defined by how autonomously they can operate and scale. That future will not be powered by AI in isolation, but by a digital foundation that brings together apps, data, cloud and security to create systems that are always thinking, always adapting and always on."
Jagadeshwar Gattu
President
Digital Foundation Services
HCLTech
Physical AI: The Next Frontier
The three imperatives don't stop at the edge of the virtual environment. The fastest-emerging frontier in enterprise AI is physical and the same rules apply.
While AI has already revolutionized virtual environments, enabling intelligent systems to analyze data, generate code, deploy and scale IT assets and interact directly with application users: Physical AI represents a leap into the real world.
- 90% of enterprise leaders say Physical AI will be critical within three years, yet most organizations are still running pilots.
- Where it is in production, the outcomes are measurable and significant: Reductions in R&D costs, improvements in safety posture, better resource utilization and greater production uptime.
- Organizations with experienced partners are more than twice as likely to have Physical AI in production and consistently outperform on every outcome measure. The partner imperative doesn't change. It accelerates.
What does it take to move from AI deployment to AI impact?
The competitive window is real and narrowing. Boards are already measuring. A significant proportion of AI programs are already expected to fail, according to the people running them. The organizations that will lead are not those who adopted AI first. They are those who built it right. The foundation. The AI governance. The partners. All three. Together.
The AI Impact Imperatives, 2026 shows you what that looks like.