How can wearables offer value beyond visualization?

The tech-enabled wearables market is expected to grow by 12 percent CAGR for the next six years (Grand View Research). Devices such as Oura rings and Fitbit wristbands, which monitor metrics such as heartrate, sleep, and fitness activity, seamlessly connect to smartphone apps, providing individuals with personal health and performance data. But wearables have been pulled into the limelight recently, and not for the right reasons.

Rising criticism against obsessive wellness tracking has led consumers to rethink their relationship with wearable tech. Is it really helping them to achieve their goals? While 78 percent of consumers are investing in wellness, only half feel that their health is ‘good’. Although this reflects wellness more broadly, it points to a clear unmet need. How can wearable brands ensure users achieve what they want to achieve?

From data to insight

According to our Brand Impact Index research, dependable delivery is the number one factor that drives consumers to engage with brands. Consumers reward brands that deliver dependable value and make life easier. In wearables, that means turning data into guidance that people can use. With 90 percent of consumers interested in personalized health or wellness products, the future of wearable technology lies in shifting from visualization to personalization. This is especially true as wearables become more integrated with healthcare systems. But daily reminders to take more steps or get more sleep can quickly become overwhelming. Without adequate guidance on how to interpret copious amounts of data from wearables, users can experience data anxiety and decision fatigue, leaving them uncertain about what actions to take.

Truly customer-centric wearables interpret data into personalized workout routines, sleep schedules, wellness plans, and even medical guidance. Oura, for example, offers an integrated care service in partnership with Council Health where users can access medical AI and licensed physicians directly via Oura’s app. This direct pathway helps users to make sense of their data through on-demand, personalized advice.

From chatbots to coaches

Fitness apps use machine learning to analyze large volumes of data from wearables – including pace, heart rate, and sleep – identifying trends and generating dashboards of an individuals’ fitness levels. But AI chatbots that offer one-size-fits-all solutions to individual needs will fail to garner trust with consumers, or provide meaningful guidance.

AI-powered fitness coaches go one step further, translating insights into real-time support. Strong AI companion apps interpret user data in a personalized context, creating tailored workout plans based on defined goals and ongoing performance data. Leading technology players are already demonstrating the potential. Zing Coach provides a ‘personal trainer in your pocket’, using AI to deliver personalized strength and conditioning programs which automatically respond to user behaviour, recovery levels, and energy patterns. Likewise, WHOOP Coach uses generative AI to offer personalized recommendations based on recovery, strain, sleep, and stress data, as well as users’ personal journal entries. The rise in AI-powered fitness companion apps has made professional level coaching more accessible, while demonstrating how data can deliver innovative services. No wonder the AI fitness sector is expected to reach $34.7 billion by 2031.

From artificial to augmented

Leading brands combine AI capabilities with human validation, delivering tailored insights that are grounded in professional expertise. For example, Oura’s Advisor feature is powered by a proprietary LLM which draws on established medical research. All knowledge is validated by Oura’s in-house team of board-certified clinicians and health experts. Similarly, Runna’s training plans are designed by elite runners and Olympians such as Steph Davis, Ben Parker, and Colleen Quigley, ensuring plans are grounded in expert coaching principles. AI monitors and analyzes performance data, delivering personalized recommendations that keep users on track.

Wellness apps such as Headspace also utilise this approach, using recordings by expert meditation teachers, mindfulness trainers, and even co-founder Andy Puddicombe, an ex-monk who traditionally led the ‘Basics’ series; a personal touch which helps users feel more connected to the ethos of the brand. To drive adoption and trust, brands must ensure users understand the scientific validity behind all advice, and clearly communicate their approach to data privacy so users know exactly which data fuels which recommendations and services.

From dashboard to delivery

Brands that layer on data analysis tools or AI features to ‘provide more information’ without the credibility of human oversight will overwhelm users and struggle to build trust. True personalized support relies on direct access to professional medical support through in-app experiences.

The real frontrunners will combine AI-powered advice with human expertise to build stronger trust and credibility with consumers. In doing so, they’ll get closer to consumers, spark behavioral change, and improve wellness and medical outcomes.