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ZDNET's key takeaways
- CIOs want to move from AI pilots to enterprise-wide deployment.
- AI must scale safely, responsibly, and with clear, measurable impact.
- Digital leaders should prioritize infrastructure, skills, governance, and value.
The next 12 months will be when the enterprise gets serious about its AI deployments, with tests and explorations being replaced by production-level services that drive lasting business transformations.
That's the conclusion of Lenovo's CIO Playbook for 2026, produced with tech analyst IDC. The playbook is a research-led guidebook for digital leaders who want to move from AI experimentation to enterprise-scale deployment.
Also: 8 urgent updates your IT playbook needs to survive the AI era
Lenovo's European CMO Alberto Spinelli explained to ZDNET during a media briefing that the research, which surveyed 800 executives from Europe and the Middle East, demonstrates how organizations are moving from scattered adoption to enterprise-wide strategies supported by stronger foundations in data, skills, infrastructure, and governance.
"AI is no longer just a future ambition, and it's now more of a defining force in how enterprises operate, compete, and grow," said Spinelli, suggesting that businesses face a critical moment.
"The race is on, but it's not just about who adopts AI fastest, but who scales it safely, responsibly, and with clear, measurable business impact."
Also: 10 ways AI can inflict unprecedented damage in 2026
During the event, Ewa Zborowska, research director at IDC, summarized the research findings and discussed five ways CIOs can scale their AI initiatives effectively.
1. Put AI at the core of business
Zborowska said the research shows that AI is crucial for organizations seeking faster growth and better outcomes.
"AI is becoming not just one of the technologies that customers are trying to use and something that they learn about, but an important enabler that helps them change business, transform how they operate, drive growth, and build competitive advantage."
That's an approach that Art Hu, global CIO at Lenovo, has adopted at his organization, as he explained to me recently in a one-to-one interview for ZDNET.
Also: Nervous about the job market? 5 ways to stand out in the age of AI
Zborowska encouraged other CIOs to work with their peers across the organization to turn their business priorities into clear AI use cases with owners, KPIs, and timelines.
"Yes, you are a CIO, but you are a partner for business. You need to realize that AI is not just to be considered from a technology perspective; you need to look at it from the perspective of what it brings to business," she said.
"Making sure that you look at processes and workflows internally to help adopt AI, and being a strong partner for your business stakeholders, is going to be of the utmost importance."
2. Identify proof of value
Rather than just using AI to improve tech-based activities, as organizations had predominantly in earlier years of the report, Zborowska said more organizations are now using AI to enhance, innovate, and reinvent their businesses.
"The majority of customers are way past this time of testing and trying things, and much more in a moment where they think, 'OK, how do we make this new technology work for us in the context of business outcomes?'"
The research suggested that almost 60% of companies are piloting or systematically adopting AI.
Also: Weaponized AI risk is 'high,' warns OpenAI -- here's the plan to stop it
Zborowska said key business priorities for deploying AI include increasing revenue and growing profit, improving customer experience and satisfaction, and boosting employee productivity.
"AI implementations are now focused on things like being more efficient in operations and looking for new ways of generating business," she said.
"This change doesn't mean the things that CIOs talked about last year are no longer important. It simply shows that other elements are of utmost interest to the business at this point."
3. Scale your infrastructure
However, Zborowska recognized that delivering value from AI comes with challenges. She said the research highlighted common issues, such as training and upskilling in IT teams and business functions.
However, she suggested the most significant challenge is IT infrastructure, stating that AI will not run effectively without efficient foundations.
"We need to think about how we introduce AI into our organizations to ensure that people are really happy when working with the technology," she said.
Also: 4 new roles will lead the agentic AI revolution -- here's what they require
Zborowska said conversations with CIOs suggest that scaling AI is only possible if the business ensures strong foundations for security, skills, and IT infrastructure are in place.
The research reported that 82% of organizations will leverage on-premises or edge deployments for AI workloads and applications as part of a hybrid environment.
"You must ensure AI is integrated within a wider IT estate on your end in the most secure way and also put in place all the mechanisms that allow you to make sure that you are operating and managing this infrastructure smartly, both from a technology perspective, but also from a money perspective."
4. Manage agentic concerns
Zborowska said interest in agentic AI is rising quickly, with the research reporting a 65% increase in organizations preparing for adoption as they seek to automate complex processes.
The research suggested that early focus areas for agentic AI deployments include security operations, financial workflows, and customer service, domains where structured tasks make agents effective.
However, organizations still face major agentic challenges, such as ensuring data quality, perfecting workflow redesign, establishing control mechanisms, and managing autonomy.
Also: 96% of IT pros say AI agents are a security risk, but it is deploying them anyway
Zborowska said the rise of agentic AI places new demands on digital leaders.
"One of the most important roles on the CIO side will be to make sure that you are helping the business identify where introducing agents and agentic AI makes sense, and where more traditional approaches will still be good enough," she said.
"Another key consideration for CIOs is looking at agents from the perspective of how they will be managed to keep control, maintain security, and prevent agents from sprawling."
5. Govern responsible AI
The research reported that just 30% of CIOs have established AI governance policies, rules, guidelines, and practices that rigorously address security, data protection, privacy, and AI sovereignty.
Worse still, more than half (54%) have not established or are in the process of developing an organization-wide approach to AI governance.
Also: How these state AI safety laws change the face of regulation in the US
Zborowska said successful enterprises agree on clear, shared rules for responsible, transparent AI use.
"Introducing AI into your organization or how you work with your customers or your business partners needs to be based on trust," she said.
Zborowska said CIOs achieve this confidence by ensuring that AI governance and adoption take place hand in hand.
"That means ensuring your organization is not just focusing on one element, like data or processes, but making sure that all elements are in place. So, you have rules, policies, and processes, and ensure that people are also well-prepped, so they're upskilled continually."
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