Kathy Gibson reports – We are at a critical moment in the race for enterprise artificial intelligence (AI) – winning is no longer about who adopts AI, but who scales safely, efficiently and with business impact.
This is the headline finding from IDC’s CIO Playbook, a study conducted in partnership with Lenovo.
Ewa Zborowska, research director: AI Europe at IDC, points out that AI is becoming a key business enabler as organisations seek faster growth and better outcomes.
The key here is in business enablement, she says, with organisation enhancing, innovating or reinventing their businesses with AI.
“Customers are well past testing and trying things; they are in a place where they want to make technology work for business outcomes.”
This ties into the second priority, which is increasing revenues and profits.
Ai is also being used to improve customer service and satisfaction; improve employee productivity; and reduce business risk and cyberthreats.
“Importantly, AI has moved beyond the infrastructure, as more business units take ownership of use cases and budgets,” Zborowska adds.
There are some interesting use cases, she says. “For a long time, AI was mostly used in IT related areas, where processes are in place and there is a lot of data. We are increasingly seeing it used to help in operations, customer service, marketing and back office functions.”
And it’s not going to slow down: IDC believes AI investments will double over the next year.
This could be because organisations have seen results IT, cybersecurity and data/analytics – and 94% expect to see additional value across various key performance indicators (KPIs) ranging from revenue to experience to decision-making.
“Customers are increasingly look for non-financial benefits,” Zborowska says. “They are looking for things like employee engagement/satisfaction, improved customer experience; or improved decision-making speed or effectiveness.
“I think we will see more non-financial benefits over the years.”
Of course, these benefits don’t come without challenges, with skills, infrastructure, data and integration still the major issues that organisations need to address.
“And we need to think about how we introduce AI to ensure people are happy working with it,” Zborowska adds.
When it comes to infrastructure, hybrid cloud is the platform of choice for CIOs.
“Organisations are choosing hybrid deployments to balance control, performance and compliance,” Zborowska says. “The public cloud is not necessarily the first choice. It’s often the choice for testing and development, but when they go into production, organisations are running their workloads where it make the most sense.
“For instance, customers who need inference often want an infrastructure they are in control of, where they have data management, and the workloads run closer to the employee.
“I think we will see increasingly that cloud only is not the way organisations go.”
In 2026, organisations are preparing for agentic AI as they seek deeper automation.
“Agentic AI will be used in cybersecurity, quality control and maintenance, customer service and support, product development and innovation, financial analysis and reporting,” Zborowska says.
The research shows that 65% of organisations are focused on scaling agentic AI across their operations within 12 months, but only 16% report significant usage today, with the majority still piloting or actively exploring use cases.
More advanced markets such as Scandinavia, Italy, and the UK are moving beyond pilots, with a majority of organisations already systematically adopting AI and increasing focus on hybrid and edge deployments to support scale. In contrast, parts of Southern and Eastern Europe remain earlier in their AI journeys, with a higher proportion of organisations still in planning or early development stages.
Meanwhile, the Middle East is emerging as a fast-moving growth market, showing strong adoption momentum and a sharp year-on-year increase in interest in advanced and agentic AI.
Across the region, hybrid deployment models dominate as organisations balance innovation with data sovereignty and operational control, while interest in agentic AI is accelerating. This signals a broader shift from experimentation toward more autonomous, production-ready AI use cases, even as readiness levels continue to vary by market.
“We’re now seeing clear returns from the AI pilots and proof-of-concept organisations have invested in, with AI delivering measurable impact across the region,” says Matt Dobrodziej, president: Europe at Lenovo. “But many are not fully equipped with the skills, governance and readiness needed to scale AI to its full potential. As priorities shift toward agentic AI, and compliance with regulations such as the EU AI Act becomes imperative, trust and scale must be built in from the start. Those who don’t, risk leaving tangible returns on the table.”
Again, there are challenges to deploying agentic AI, such as ensuring agents are managed in the right way.
Responsible AI is the order of the day, Zborowska says, with trust, alignment, accountability and control not negotiable.
The top AI trust concerns are lack or responsible AI, poor data security, poor knowledge/application of responsible AI, shadow AI risk and IP risk, she adds.
Half of the companies surveyed are in the process or developing AI governance, risk and compliance (GRC) policies. Many have realised that what they have now is not enough, with just 30% currently having comprehensive policies.
Zborowska concludes with the key CIO considerations in 2026:
- AI will become a core engineer of business performance, turning business priorities into clear AI user cases with business owners, KPIs and timelines. CIOs should simplify and modernise workflows so AI can scale.
- There will be an increase in budgets, and an increasing partnership between IT and business. AI projects need to be co-owned, with business and IT working together, with KPIs in place.
- A hybrid, secure and integrated environment will become an essential standard for enterprise AI.
- Agentic AI is emerging as the next step in workflow automation – however, it requires control.
- Governance maturity may become the gatekeeper for AI scale
“One of the most important CIO roles will be help business determine where agentic AI makes sense; and looking at agents from the perspective of management,” Zborowska says.
“The need to ensure the adoption of AI governance goes hand in hand with deployment, ensuring rules, policies and processes are in place, and ensuring people are well prepared.”