The AI-first technology function
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1. Home 2. |What we think 3. |The AI-first technology function
Insight UK
2026 UK Tech Leaders Survey: The AI-first technology function
Published June 17, 2026
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Key takeaways
- For the third consecutive year, Wavestone surveyed 200 CIOs in the UK. Their insights confirmed that leaders are navigating unprecedented pressure: enabling AI‑led transformation across the organisation, while simultaneously adopting AI deeply within their own teams.
- **Cost reduction** goals dominate overall (64%), but larger organisations prioritise **automation (72%)** and productivity at scale.
- **AI‑ready skills are the top IT challenge** (40%) yet remain a low investment priority (14%), creating a widening execution gap.
- Data maturity is a leading challenge, but **only 23% prioritise investment in data management**, governance and compliance, revealing another execution gap.
- Despite rising AI demand, **70% have yet to fully embed AI into their Technology Operating Model,**slowing their ability to move fast and lead AI transformation.
AI is not a technology problem: Designing the operating model that wins the race
The technology function is now on the frontline of the AI race, expected to drive AI transformation for the business while also transforming itself. Most organisations have invested in the engine. Few have built the system to win.
Following on from last year’s**Global AI Survey**(opens in new tab)which presented the enterprise level ambition of AI and determined that 70% of organizations already place AI at the heart of their business strategy, yet challenged by market complexity, regulation, talent shortages and adoption. Wavestone’s new report deep dives into the technology function. The**2026 UK Technology Leader Survey** takes a closer look at the technology function and to determine what they are actually ready to deliver when it comes to AI and if they can do it at scale. We benchmarked 200 CIOs, to find the answer to these questions. The report will help CIOs understand how fast the market is moving, take the lead in AI and identify the gaps that determine whether IT accelerates transformation, or slows the business down.
Overall, the survey shows that AI is already reshaping how technology functions operate, delivering value beyond cost reduction. However, a gap persists between ambition and execution, which is driven by challenges in skills, data, governance, and ROI.
This report shows how to turn AI ambition into sustained business performance, by focusing on the operating model, not just technology.
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1. The technology function becomes the engine of AI transformation
Demand for AI is now widespread across the business and is accelerating rapidly. The technology function is now positioned as the primary engine for building, deploying and governing AI across the organisation so must be set up to respond faster, and at scale. Getting a handle on prioritising AI use cases is a capability all CIOs need.
- 79% of respondents report very strong or strong demand for AI from business teams 79% of respondents report very strong or strong demand for AI from business teams
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> Many organisations treat AI as a technology upgrade rather than the operating model transformation required to embed AI at scale and drive sustained value. > > Gonzalo Gonzalez, Associate Partner, Wavestone
2. AI is reshaping IT, but operating models aren’t keeping up
AI is already reshaping the technology function in most organisations. More than 70% of those surveyed report that AI is fully embedded or established to some degree across most IT functions, with the highest levels of adoption in IT Customer Support and Helpdesk, and Data and Analytics.
AI foundations are largely in place, but few organisations have fully embedded them. Only 40% have fully embedded human oversight, and just 24% have a dedicated AI Centre of Excellence. Inconsistent integration across technology services is limiting the ability to generate repeatable value at scale.
Today, AI’s impact is felt more in enhanced capabilities than immediate efficiency. with productivity gains expected to follow as AI matures.
- 56% of organisations report improved operational scalability
- 51% report better decision-making
- 51% report improved quality
Productivity before savings
AI is delivering productivity before cost savings, and priorities differ by organisation size. Smaller organisations tend to focus on cost reduction (64%), while larger organisations prioritise automation and productivity at scale to manage greater complexity. In practice, scaling AI requires upfront investment to unlock productivity, quality improvements, and long-term value.
However, investment continue to skew towards AI tools. By prioritising software delivery and IT operations tools (54%) over critical foundations such as data governance, workforce capability,organisations risk missing the deeper operating model change that AI demands. Find out how we helped our Life Sciences client unlock AI innovation with a scalable, compliant Data Operating Modelhere. (open in new tab)
The AI skills and delivery challenge
Technology team roles are being reshaped as AI increases demand on technology teams, but the biggest constraint is the lack of AI-ready skills. Despite this growing pressure, upskilling remains a low priority.
Rather than reducing headcount, AI is changing how work is delivered. Hiring continues to focus on technical roles, but demand is growing for hybrid profiles as organisations move towards AI‑augmented, value-focused delivery.
Third party partners are helping organisations move faster on AI, but they also introduce new risks. Delivery models are increasingly hybrid, with 46% combining internal teams and external partners to accelerate execution. This makes more disciplined sourcing critical: retaining control over core capabilities while using partners selectively to add scale and speed.
Risk and governance – constraints on AI scale
Investment in AI governance and risk management is increasing as organisations recognise governance as a critical enabler of scale. To be effective, it needs to be fully embedded and designed into AI-enabled processes from the outset, rather than added later. Cybersecurity is also emerging as a priority. Read more about this topic in our article **“Scaling AI safely: Are your guardrails ready?**“(open in new tab)
> Hybrid roles are rising, with 40% seeking profiles that can translate AI into operational outcomes, such as AI product ownership > > Alex Millard, Associate Partner
3. Operating model change will decide the winners
AI is already improving service quality, reliability and delivery speed across IT, but gaps in skills, data, governance and ROI are holding back scale.
As technology teams evolve from service delivery to leading AI transformation, only those that embed AI into their operating model, while building strong internal capabilities, will be able to lead AI transformation at pace.
> There’s no doubt that the acceleration of AI-enabled end-to-end transformation has become one of the most defining leadership challenges across industries. One critical success factor in AI adoption that deserves even greater emphasis: the human dimension. > > Bryn Barlow, AXA UK
What next?
AI is already reshaping the technology function today, not in the future.
**The differentiator is no longer ambition. It is execution.** The goal is not more use cases. It is repeatable, scalable impact across the enterprise. Those that embed AI into their operating model will be able to scale and realise sustained value.
Methodology
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A slide titled “About the survey” summarises respondent demographics. Wavestone surveyed 200 senior IT leaders in the UK in late 2025.
By job level, 77% of respondents are senior management (senior managers of units, functions or departments), and 23% are board members or C-level executives.
By company size, 41.5% of respondents work in organisations with 1,000–2,499 employees, 33% in organisations with 3,000–4,999 employees, and 25.5% in organisations with over 5,000 employees.
A donut chart labelled “Respondents sector” breaks down industries: Insurance represents 20% of respondents; Banking, Energy, Manufacturing, and Transport/Travel each represent 15%; Financial services excluding banking accounts for 10%; and Life Sciences accounts for 10%.
What to expect from the report:
- **Report Analysis:** Deep dive into how 200 CIO peers are embedding AI across technology delivery to find out where your technology function stands
- **Expert advice and real world examples:** AI experts advice on the building blocks of an AI‑first technology function and how its been delivered for our clients
- **AI maturity assessment**: Assess your AI maturity, expose gaps and act fast
- Data & AI
Wavestone’s 2026 UK Tech Leaders Survey
pdf · 1417KO
Explore how to move from experimentation to measurable AI impact
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