Recapping an Illuminating Active Uprising Conference

I recently had the pleasure of attending the insightful Active Uprising conference. It was fantastic catching up with so many inspiring people pushing the fitness industry forward. Discussions ranged from relieving NHS pressure through exercise, to the buzz worthy topic of artificial intelligence (AI).

In particular, Keepme's Founder & CEO, Ian Mullane, delivered an invigorating talk demystifying AI. I wanted to recap his simplified AI explanation for those unable to attend the event.

Breaking Down AI Concepts

Essentially, AI refers to computer systems exhibiting human-like intelligence for tasks like visual perception, decision-making, and problem-solving. The approaches include:

• Rules-Based AI

  The simplest form follows rigid rules defined by programmers, akin to "if this, then do that". For example, digital assistants use predefined rules and keywords to respond to basic commands and queries. Limitations arise when users ask something outside predefined rules.

• Machine Learning AI

  This advanced AI develops the ability to learn and improve independently without explicit programming. Algorithms examine data to detect patterns and then apply those patterns to make judgments and predictions. The more quality data they train on, the better they become at tasks like making personalised recommendations.

• Deep Learning AI

  This highly advanced technique uses artificial neural networks modelled after the human brain's intricately interconnected web of neurons. Analysing vast amounts of data, deep learning powers cutting-edge innovations from self-driving cars to predictive healthcare. However, due to their complexity, their inner logic is harder for humans to interpret.

We already encounter AI in apps providing customised recommendations and predictions. In gyms, AI has proven to be game-changing for improving member retention and reducing churn.

AI algorithms can analyse usage data - attendance frequency, activities, spending, and web browsing. By detecting patterns predictive of members at high risk of cancelling, gyms could proactively engage those members to change their behaviour.

For example, machine learning models might identify members rapidly losing attendance, allowing staff to reach out with motivational messaging or special offers to re-engage them. Or, AI could pinpoint members using limited gym features ripe for upsells on new services like personal training.

When applied across an entire member base, minor tweaks to improve retention can yield tremendous revenue returns over time. AI's continual learning allows ever-improving precision in preventing churn.

Some fitness operators understandably hesitate to leverage AI due to uncertainty around data privacy regulations like GDPR. Specifically, there may be questions about whether AI algorithms can analyse member data without violating sensitive data handling policies.

However, this should not need to stand in the way of AI adoption. With proper data governance protocols and access controls, AI systems can be implemented in full compliance with GDPR and other policies. Sensitive, personally identifiable information can be removed or obfuscated so AI models can still derive valuable insights from broader usage patterns without compromising member privacy. There are also techniques to allow AI analysis of encrypted data. Responsible and ethical usage of AI for member benefit should align with even the most stringent regulatory standards. With an informed approach, the fitness industry can tap into the tremendous potential of AI while also earning members' trust.

As Ian emphasised at the ukactive event, by feeding smart algorithms quality member data, we gain new problem-solving capabilities to reshape the member experience and business performance. And that is just a snippet of the capabilities! The AI revolution promises unprecedented personalised engagement between gyms and their customers and you shouldn’t be scared of it!