James Tuttiett, Global Transformation Director At FDM Group, On Why AI Transformation Must Move Beyond Pilots

This journey made me realise that meaningful transformation is always socio-technical, never just technical. In the past I’ve found a lot of transformations fail not because the strategy is wrong, but because the culture of the business never really shifts. Meaningful digital transformation needs to be sponsored from the top and modelled consistently by senior leaders; otherwise, it risks being seen as “another initiative” rather than a new way of operating.

I base meaningful digital transformation on practical outcomes and whether it made the business perform better, such as looking at profit and loss and client satisfaction. If there are no tangible results in revenue, delivery and engagement within 12-14 months, we are probably running a project, not a transformation.

Working in a service business right now, you find that AI is no longer a standalone speciality, but becoming embedded into how we build, how we deliver, and how we support. Across the industry, we are shifting from selling “smart people and hours” to selling outcomes, platforms and repeatable solutions that are increasingly AI-enabled.

Services firms are being pushed to behave more like product companies in how they invest, while still maintaining the client relationships that made them successful in the first place. This is also reshaping the talent that goes with it, particularly confident and curious individuals to work alongside AI, instead of seeing it as a threat.

Equally, as entry-level tasks are increasingly becoming automated, we need to find new ways for entry-level employees to learn and grow in their careers, rather than relying on the traditional career structure.

Successful AI projects don’t start with the technology, but with a clear business problem and someone accountable for delivering results. The organisations that focus on measurable outcomes from the outset and bring together teams from across the business to ensure all solutions are practical and secure, are the ones seeing the biggest impact. Where companies go wrong is by leaving AI pilots stuck in the experimentation stage, without a clear plan on how to roll it out across the business, leading them to failure.

The biggest opportunities for efficiency are in work that is high volume and document-heavy; this includes things like case triage, research, and first draft analysis, where AI can reduce time and manual effort dramatically.

However, the more we automate, the more valuable human judgement becomes. People are still needed for complicated client requests and for maintaining relationships or needed to look into a business decision to make sure it’s the right way to go. This is where the critical skills are essential, such as creative and critical thinking, and the ability to answer questions that really matter. AI will not work alone; human input is needed to make the most out of these tools.

A big part of our role is to deliberately strengthen those human skills alongside AI tools, so people can work confidently with AI while still bringing human judgement and perspective to business challenges.

Clients are particularly looking for speed and proof of value, so for service-led businesses, which means shifting from one-off projects to AI-powered solutions that can be rolled out quickly and improved over time.

Innovation in AI should be a daily priority in everyday work across all teams. As careers evolve with technology, people who use AI well can quickly outperform more experienced colleagues who don’t. The colleagues who stand out are the ones who are curious, willing to experiment, and able to adapt how they work around it, instead of just using it occasionally. The challenge is to build the right training and tools so people can use AI to improve their performance, while giving clients the clarity and consistency they expect.

The most important shift is from knowing the answer to knowing how to work with AI systems that help you find better answers. This demands strong problem-framing, data literacy, and the ability to design workflows where AI and humans each play to their strengths.

We are already seeing that individuals who work alongside these tools can outperform people mid-career who are still working in a pre-AI mode. The individuals who will thrive in the workplace will be the ones who are equipped with job-ready skills and AI fluency, and who receive continuous upskilling and reskilling opportunities, in order to keep pace with the needs of employers.

In this day and age, we see all over the media how AI should be feared, a weapon which is taking people’s jobs and ripping away opportunities for young people. However, AI must be seen as something which employees and young people entering the workforce can use to their advantage. It’s no secret that AI is reshaping the workplace, but AI knowledge combined with human skills, such as problem-solving, can bring true future career success.