How LeisureLabs turned AI ambition into a working system for growth
LeisureLabs is a digital transformation, delivery and product partner to the fitness and wellness sector, combining industry knowledge with technical capability to improve the digital services leisure brands depend on. Its 2030 vision set a clear commercial goal: treble revenue without trebling the workforce, with AI doing the work the extra headcount would otherwise have to. The leadership team joined the Spark AI Accelerator to build the way of getting there.
The challenge
The ambition was written down, but the team was not yet ready to deliver it across the business. Parts of the group were using ChatGPT and a mixture of other tools, meanwhile the team behind LeisureWise, the group's member engagement product, had already moved its development to an AI-led model. They still hadn't agreed on their tech stack, and no one was accountable for a set of AI initiatives. Internal surveys asked the team whether AI was making them more efficient and got an overwhelming yes, but nobody could say what that yes was actually worth. And the founders kept getting pulled into delivery rather than direction, with little time to do the work that would have moved the vision forward.
How Spark AI helped
The company embarked on Sparkās three-month AI Accelerator programme, starting with a company-wide AI Foundations workshop followed by dedicated streams for leadership, client services and strategy. With the team spread across several countries and time zones, the streams ran as a mix of in-person days in London and online sessions working through the agency's own briefs, statements of work and strategy documents, so the training landed on the work people actually do.
The leadership stream worked through Sparkās automation, augmentation and innovation framework to produce a prioritised roadmap, an operating playbook and a company AI policy. They also stood up an AI Task Force with a fortnightly rhythm, led by an AI Lead and supported by āKimā, an AI agent built in-house to act as AI Enablement Lead for the group's initiatives. Twice-monthly AI School Days give the wider team a regular place to share what they're building.
The client side got the same treatment. LeisureLabs mapped its clients across four levels of AI readiness, from those who want no AI involvement to those who want to build alongside them, which gave the team a clear basis for what to say to whom.
What changed
A month after completing the programme, 86% of the team use AI every day, and 71% report recovering more than three hours a week, and over 20% are building tools their colleagues use. The business scored 2.5 on the Spark AI Maturity Model Ā®, moving from individual experimentation to solid adoption, with AI embedded in many ways of working.
The change shows up across all three parts of Sparkās AI Strategy framework:
Automation:
Client meetings moved onto a single AI meeting assistant with central ownership and a cross-team project and account dashboard. A new joiner who started in September was onboarded by an agent acting as a digital buddy, answering his questions and walking him through tasks that used to take several colleagues hours of repeated explanation. In finance, an agent now cross-checks the intercompany ledgers and posts draft journals for a human to approve. A legal agent has turned round DPIA, DPA and cyber security documentation that would otherwise have taken weeks. On the group's product side, a grant application process that ran to six months now takes about two.
Augmentation:
Gemini Gems are built around real work across the business, supported by a shared prompt library with review, version control, tagging and a dashboard showing what people are actually using. Client call insights are now captured in HubSpot, so recurring needs across the sector surface rather than sitting in individual heads.
Innovation:
Within a month of finishing the programme, a new AI-enabled product had been pitched to an existing client, priced on the outcome rather than on time and materials, and the consulting team is packaging a set of services the agency has never been able to offer before.
"We came out of it with more than a roadmap. We came out with the operating playbook and the tools to execute on it, and a team to support it. It's been a catalyst in the organisation."
ā Charles Njoku, Co-founder, LeisureLabs
The return on investment
Fragmented experimentation to Stage 2 Adoption in three months, with a prioritised roadmap, an operating playbook, a company AI policy and a standing taskforce where three months earlier there were none.
Agents live in the business: onboarding, finance reconciliation and legal documentation, plus a grant cycle cut from six months to about two. A member of the finance team who started the programme unsure AI was relevant to her role, and finished it running two assistants of her own.
A new AI-enabled product pitched to an existing client on outcome-based pricing, and a client base mapped by AI readiness so the agency knows which conversation to have with whom.
