From ‘are we using AI?’ to ‘where is the value?’

29th October 2026

Across our portfolio, the conversation around AI is changing. It's no longer simply about whether businesses are using it, but where it's making a difference and who's responsible for turning that into real value.

We recently brought together people leaders from across the FPE portfolio for our latest People Leaders Forum, exploring how businesses are adapting to AI. Facilitated by Gary Mitchell of Hanleo People, with insights from Sunil Rajan, FPE's Senior Adviser (AI), the session was an opportunity to share experiences, discuss common challenges and explore what's working in practice.

Widespread use, uneven integration

AI is now in widespread use across the portfolio. Access to the leading AI tools, prompting and content generation are now commonplace. Despite this, few businesses would describe AI as fully embedded in how they operate.

Cross-departmental adoption is uneven. Whilst engineering and technical teams are well established in their use of AI, attention is turning to the wider business functions as they begin to integrate AI into their own processes. Examples include:

• Operations: AI assistants embedded in everyday collaboration tools now answer frontline queries around the clock, reducing overnight delays, with personal agents in development to extend managers' capacity.
• Finance and back office: core business systems, from CRM and accounting to project management, are being moved towards a single AI layer, giving leadership near real-time visibility of performance.
• People: performance review and engagement survey data can now be analysed in minutes rather than worked through submission by submission.
• Sales and delivery: AI is being used to strengthen the handover from presales to implementation, so customer context carries through to delivery.

Ultimately, the opportunity lies beyond doing existing tasks more efficiently. As AI becomes part of the underlying operating model, some processes will not simply run faster but will be redesigned altogether, particularly at the hand-offs between teams and systems, where much of the friction sits today.

If everyone owns AI, no one does

Ownership is one of the most important factors in making AI adoption stick. Good ideas and use cases are emerging across businesses, but they can remain siloed within individual teams, or even with specific employees. Without clear responsibility for connecting these initiatives, businesses risk duplicating effort, missing opportunities and relying too heavily on a small number of enthusiastic individuals.

Wider research points to some of the organisational challenges. In WRITER's 2026 survey of 1,200 executives, 78% say AI has created tension between IT and other lines of business and 55% report that AI use is a chaotic free-for-all at their company.

One approach is to establish a cross-functional AI group, with senior leadership support and representation from across the business. The aim is straightforward: define responsibilities, agree priorities and make sure successful ideas don't remain isolated within individual teams.

Where the value is

The focus is shifting from measuring AI activity to understanding the value it creates.

Time savings are often the easiest benefit to identify. But an efficiency gain only becomes meaningful when a business decides how to use that additional capacity, whether that is serving more customers, developing products faster or strengthening operational control.

For many businesses, quantifying the impact remains a challenge. Connecting AI initiatives to improvements in revenue, margin, capacity and EBITDA will be important in demonstrating how AI contributes to wider growth ambitions.

In the meantime, early measures are emerging across the portfolio. Capability development is being assessed, and AI expectations are beginning to feature in competency frameworks and performance processes. Usage and model costs are being monitored and the strongest use cases are being designed around a specific operational outcome, such as reducing response delays, increasing management capacity or cutting manual effort in implementation, rather than general time savings.

Adoption starts with people

Enthusiasm for AI varies across every workforce, from early adopters building their own tools to colleagues who are unsure where to start. In many cases, the barrier is confidence or familiarity rather than willingness.

A useful first step is understanding where people actually sit. Mapping capability across the workforce gives leaders a clearer picture of where to focus support. Sunil shared an AI competency framework to help leaders assess skills, confidence and judgement, target development and track progress

Once that picture is clear, the priority is building confidence, and that starts at the top. When senior leaders actively use AI and share their experiences, it signals that AI is a strategic priority and gives others permission to experiment.

Structured training turns that permission into capability. Programmes completed by the whole workforce and then applied directly in each role give everyone a common foundation, while peer learning, with colleagues showing one another what works in practice, often wins over hesitant users more effectively than top-down instruction. Sustaining that momentum depends on clear ownership so that progress in individual teams is connected, prioritised and shared across the business.

Two lessons stand out.

First, move from individual adoption to team adoption. Once people understand how to use AI themselves, the next challenge is working out how teams can use it consistently and measure the impact.

Second, learning needs to be continuous. With AI developing so quickly, one-off training programmes can soon become outdated. Regular knowledge sharing, practical demonstrations and peer learning are increasingly valuable.

Looking further ahead, as AI takes on more routine execution, the focus for people leaders will expand from building capability to redesigning roles and workflows, with workforce planning increasingly shaped by how work should be structured and which skills will be needed to make the most of agentic tools.

Good governance need not slow progress

Governance is a key consideration, with data security, privacy, regulation, platform dependency and future cost exposure the primary risks. A proportionate approach, built on an approved tool list, a straightforward risk assessment process and clear responsibility for AI within the business, can help manage these risks without discouraging experimentation.

A less obvious challenge is what happens when employee-built tools succeed. As they become part of everyday operations, businesses need to decide who maintains them, make sure they are properly documented and avoid becoming dependent on the original creator. AI leadership should also keep technology architecture, usage and costs under regular review, so the business retains the flexibility to adapt as AI models and pricing structures evolve.

Turning shared learning into action

The discussion also highlighted several areas where FPE, working alongside Sunil and our portfolio leadership teams, can continue to support businesses as their use of AI develops.

• Understanding AI maturity: assessing capability consistently across the portfolio, so businesses understand where they stand, where the gaps are and how quickly to move.
• Supporting leadership teams: working with CEOs and senior leaders to align AI priorities with business strategy, establish clear ownership and translate ambition into practical roadmaps for each function, including how roles and skills need to evolve.
• Developing AI capabilities: helping teams move beyond prompting towards agents and connected workflows, with an emphasis on practical demonstration and peer learning over generic training.
• Connecting AI to value: helping businesses link AI initiatives to tangible measures of financial performance, so they form part of the wider value-creation plan.
• Sharing what works: making sure successful use cases are adopted and embedded across teams within each business, and creating opportunities for companies across the portfolio to exchange proven use cases.

Thank you to everyone who joined us, to Gary for facilitating, and to Sunil for sharing his insights.