Key Outcomes
- Product AI readiness scorecard — where can AI transform your value proposition, personalisation, and user experience?
- Roadmap opportunity mapping — identifying which product initiatives are amplified, unlocked, or fundamentally changed by AI
- SDLC assessment — evaluating AI-native development practices, tooling, velocity, and team readiness
- Business operations audit — surfacing AI opportunities across customer support, content, onboarding, analytics, and internal workflows
- Data readiness review — assessing data quality, accessibility, and architecture for AI/ML workloads
- Prioritised AI transformation roadmap with quick wins, strategic initiatives, and investment framework
Tools & Technology
Our Approach
AI readiness in health and fitness isn't a single question — it spans the entire organisation. A product might be ripe for AI-driven personalisation, but the data infrastructure can't support it. The SDLC might be ready for AI-assisted development, but the team doesn't have the practices in place. Business operations might benefit enormously from AI automation, but nobody has mapped the opportunities. This assessment covers all three.
We assess the product dimension first: where does AI change the value proposition? Can you move from static programmes to adaptive coaching? From generic content to hyper-personalised guidance? From manual insights to real-time intelligence? Then we look at the SDLC: are your development practices, tooling, and team capabilities ready for AI-native workflows? Finally, we audit business operations — customer support, content creation, user onboarding, analytics — identifying where AI can drive efficiency, quality, and scale.
The assessment follows a four-week cadence: stakeholder interviews and landscape mapping in week one, product and data readiness deep-dive in week two, SDLC and operations assessment in week three, and strategic transformation roadmap delivery in week four.
What's Included
- Stakeholder interviews across product, engineering, operations, and leadership
- Product AI opportunity mapping against existing roadmap and value proposition
- Data readiness assessment — quality, accessibility, and architecture for AI/ML
- SDLC evaluation — AI-native development practices, tooling, and team readiness
- Business operations audit — AI opportunities across support, content, onboarding, and analytics
- Competitive benchmarking against AI-forward health and fitness products
- Prioritised transformation roadmap with phased investment framework