For many organisations, the AI journey is well underway. Pilots have been launched, internal capabilities have been built, and use cases are being explored. But the next step is where the true business value lies, transitioning from experimentation to meaningful, embedded AI adoption that drives measurable returns.

The latest Nash Squared/Harvey Nash Digital Leadership Report 2025 reveals this shift is firmly in progress. The number of organisations running large-scale AI implementations has nearly doubled since our 2024 report, rising from 10% to 19%, a 90% increase. More importantly, 33% of digital leaders now report demonstrable ROI from their AI investments.

So, where are the early adopters seeing results, and what separates pilot projects from scalable success?

Where AI is already delivering ROI

The data from the Nash Squared/Harvey Nash Digital Leadership Report 2025 shows that AI is no longer confined to isolated use cases or experimental environments. It’s being deployed where it can make a tangible difference to operational efficiency and productivity. Across the survey responses from digital leaders, several high-impact areas emerged:

  • Software development: Leads the way in AI adoption, with the highest levels of implementation driving efficiency and accelerating code creation and testing. As one digital leader from the Digital Leadership Report explained, AI is already being used for “code documentation, refactoring and development”, delivering “around a 20% efficiency improvement”.
  • Helpdesk and internal support: AI-powered virtual agents are reducing response times, improving issue resolution rates, and freeing up human capacity for more complex queries. As one digital leader shared in the Digital Leadership Report, “We implemented an AI-powered customer service chatbot…it reduced support costs by 30%, improved customer satisfaction, and increased sales conversions, with the system continuously improving to deliver significant ROI”.
  • Management of information/insights: Organisations are using AI to analyse data and support faster, more confident decisions. In the Digital Leadership Report, one leader noted, “We have used it to automate processing of incoming documents…success rates are significantly higher, reducing the number of incidents needing a person to review”.
  • Marketing and sales: From lead scoring to content generation and customer insights, AI is reshaping marketing and sales operations and sharpening targeting effectiveness. As one digital leader mentioned in the Digital Leadership Report, this has delivered “multi-million revenue uplifts through recommended outreach lists for client advisors rather than the previously human-led approach”.

These examples illustrate that when AI is targeted at well-defined problems, with structured data and clear objectives, it moves quickly from concept to impact.

What separates success stories from stalled projects?

One standout finding from the report is that the biggest barrier to scaling AI isn’t technology, it’s the business case. Almost half (49%) of digital leaders cite “demonstrating the business case” as their top hurdle.

But what if business cases are being built on weak foundations? In a recent episode of our industry-leading podcast, ‘Tech Talks,’ Kyle Hauptfleisch (Chief Growth Officer at Daemon) shared that his view was that too many organisations had a broad, vague AI strategy rather than focusing on specific friction points.

"What is the business trying to achieve? And then where are the friction points?... It's all about unlocking value, whether that's internally or for your customers, in a meaningful manner. It's got to move the needle; you can have multiple AI pilots that sit on the sideline, which have drained some resources but might offer good talking points, and maybe some decent lessons. But unless it's moving the business needle, it could become sunk cost".

This sentiment was certainly backed up by our wider conversations with digital leaders. We know the difference comes down to a few critical factors:

  • Clear alignment with operational priorities: Boards are sharpening their focus on operational efficiency, with 53% citing it as their top technology objective. AI projects that tie directly to cost savings, productivity gains, or customer improvements are far more likely to gain traction.
  • Cross-functional ownership: The most successful AI adopters embed AI into core business processes, not just within IT functions. Teams from operations, HR, customer service, and product development are involved in shaping AI initiatives, ensuring they address business needs.
  • Scalable infrastructure: From data platforms to governance frameworks, building the right technical foundations enables AI to be scaled across departments rather than remaining a niche experiment.
  • Targeted skills development: Despite AI’s growing prevalence, more than half of organisations are not yet upskilling teams on generative AI. Those investing in internal capability building, particularly in AI literacy for non-technical teams, report smoother adoption and faster ROI.

From pilot to productivity: Building your AI business case

For senior technology leaders, the question is no longer whether AI delivers value, but how to turn that value into real, scalable results.

Based on insights from the Digital Leadership Report, successful organisations approach AI with three guiding principles:

  1. Business-first, tech-enabled: Start with operational challenges and growth opportunities, then explore how AI can accelerate or enhance outcomes.
  2. Embed, don’t bolt on: Avoid treating AI as a side project. Integrate it into everyday workflows and decision-making processes.
  3. Prove early, scale fast: Focus pilots on areas where quick wins are possible, quantify success, and use those wins to secure broader buy-in and investment.

The road ahead

AI is rapidly moving from experimentation to enterprise-wide productivity. Organisations that act now to build strong business cases, foster alignment across teams, and invest in scalable AI strategies will be best placed to unlock sustainable competitive advantages.

Central to this shift is the evolving role of the CIO. Oracle’s Country Leader, Siobhan Wilson, spoke to ‘Tech Talks’ to emphasise that the CIO's role itself is "becoming much more aligned to the business as opposed to the business telling them what they want", leading to a "much more collaborative conversation now".

AI success requires a unified effort across departments, not just within IT, impacting the digital leaders' outlook and remit.

For more insights into AI and digital leadership, download the 2025 Nash Squared / Harvey Nash Digital Leadership Report

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