Every January, three very different gatherings set the tone for the year ahead in health and life sciences: CES in Las Vegas, the J.P. Morgan Healthcare Conference in San Francisco, and the World Economic Forum in Davos.
Taken together, this year’s conversations say something important for anyone delivering or building care: AI is no longer just a headline; it is the plumbing. The real work now is about workflows, evidence and people.
CES: The patient and the platform
Health and wellness took over the CES floor in rings, bands, headsets, connected home devices and beyond, and there were three prevailing themes:
- The GLP-1 ecosystem and the tools wrapped around new weight-loss and metabolic drugs
- AI-powered precision health
- Remote care through increasingly sophisticated wearables
While these may not seem groundbreaking for those immersed in health innovation, seeing and hearing these conversations in the mainstay sent a clear message: Amid the futuristic glitz, glam and robotics, digital health is no longer the awkward sibling sitting in the shadow of big tech and consumer tech.
These discussions and showcases highlighted how AI is increasingly becoming an invisible layer that turns sensors into proactive, personalised coaches, scores cardiometabolic risk, analyses nutrition, detects early cognitive change and flags when someone might need clinical attention. Devices now demand less active input from the user, but promise more intelligence and active condition management.
With digital health now increasingly mainstream, CES reaffirmed that baseline expectations of health and care are shifting. Patients are increasingly arriving at consultations with months of sleep, heart rate, rhythm or activity data on their wrist or in their phone, and expect it to mean something. All huge promises, but the elephant in the room remains – when and where should the regulation kick in? Consumer-grade does not automatically mean clinic-ready, and clear policies are needed around how patient-generated data is interpreted and used.
J.P. Morgan: AI moves from theory to execution
At the J.P. Morgan Healthcare Conference, the mood was markedly different from the peak-hype years. Much of the conversation referenced a shift from “broad enthusiasm” to evidence, execution and emerging momentum. Investors want to see AI models that have moved beyond pilots into products with validated outcomes.
It was also clear that providers are now looking beyond just administrative use cases and more confidently towards AI that directly improves clinical care, whether in diagnostics, risk prediction or treatment planning. At the same time, deal activity and announcements showed the interest in AI agents has not and is not waning, with a real focus on automating complex workflow tasks across drug discovery, personalised medicine, clinical trials and healthcare administration.
For healthtech innovators, the take-home message from funders was impossible to ignore: “We use AI” is no longer interesting. The bar for evidence is rising fast, and real-world data, comparative studies and clear economic arguments are becoming hygiene factors rather than nice-to-haves.
There was an increasing call to providers to play a bigger role in shaping how innovation plays out. Whether that’s co-designing pilots to solve the problems that matter most clinically and commercially, or building internal capability to evaluate AI tools on technical performance, explainability, safety and how well they fit into existing workflows. Even as far as exploring new partnership models where the upside is linked to outcomes and value, not simply to the number of licenses sold.
Davos: Systems, standards and the human clinical workforce
While CES focused on devices and J.P. Morgan on deals, Davos zoomed out to ask bigger questions about systems and society.
World Economic Forum pieces on digital health this year repeated an AI-centred theme: It can only help reimagine healthcare if it is built on connected data, clear standards and smart regulation, and embedded into resilient health systems rather than bolted on as isolated pilots. Scaling digital solutions depends on empowering clinical entrepreneurs inside hospitals and aligning them with external partners and global networks.
Davos discussions also centred on the labour market impact of AI. Executives warned of an ‘AI tsunami’ that could reshape up to 60% of jobs in advanced economies, with younger workers and entry-level roles most exposed. Panels on “human-centred AI” pushed the idea that the future of work in sectors like healthcare will be less about replacing clinicians, and more about redesigning roles, workflows and training so humans can do the important human-to-human, hand-on-shoulder work, complemented and in many cases even emancipated by technology.
January’s conferences made one thing clear: AI in healthcare is no longer about whether it will arrive, but how we choose to use it. For Harley Street Health District, the opportunity and responsibility is to turn global headlines into local, evidence-based improvements in care for the people that it serves and supports.
