AI in 2026: The data drought, healthcare opportunities, and space tech

In the last year, we’ve seen huge strides in AI development and adoption. Whilst staggering valuations take the headlines, I’m interested in the coming data drought, opportunities in healthcare, and space tech. These are the industries where we expect the most impact to be achieved.

New AI data sources: a huge market opportunity

Gaining access to differentiated data will become both a bottleneck and an opportunity in AI, as we begin to reach the limits of readily available data sources. Against the backdrop of the impending data drought, startups will need to test their creativity in sourcing, generating, and owning both training and feedback data, including synthetic data, proprietary operational data, and data created through new user interactions.

This is where a new market will spring up around providing data for AI solutions. The biggest LLMs have historically scraped the internet for their data, but as we learn more about how LLMs work and as we develop specialist forms of AI, we must have access to high-quality data for it to generate high-quality output. There are plentiful opportunities for new startups with access to good data to thrive, monetising previously siloed data to become data marketplaces or indeed data brokers.

This may also go some way towards tackling the problem of synthetic data. We’re starting to face the risk of model collapse, where synthetic data reinforces its own hallucinations, and this can be mitigated in part through more accurate data sources.

The internet is only a tiny fraction of all the information and data available in the world, with much of it set behind walls, for example, proprietary IP and unstructured offline data. This raises the question of how we access that data, the structures around it, and the protection of that data, particularly in high data-security-need markets like healthcare.

I predict strong market expansion over the next 12 to 18 months as demand for defensible data moats accelerates, and I am interested to see the ways these challenges are tackled by new players in the market.

New healthcare pathways

The rapid maturation of wearables, remote monitoring, and AI-driven decision support is fundamentally reshaping healthcare delivery. These technologies are no longer just peripheral tools; they are the architects of new, decentralised healthcare pathways that prioritise at-home diagnostics and longitudinal support.

As we move through 2026, several high-level shifts are becoming clear. Firstly, clinical decentralisation has led to a move away from resource-intensive, facility-bound diagnostics. By transitioning monitoring to the patient’s natural environment, providers can eliminate the logistical and financial burdens of inpatient observation without sacrificing data quality. We are also witnessing greater operational efficiency, as digital integration allows for a more streamlined flow from initial consultation to treatment. This shift reduces patient disruption, lowers overhead costs for clinics, and perhaps most importantly, reclaims clinical hours, allowing medical professionals to focus on high-complexity care.

In addition, AI-enhanced personalisation has moved beyond simple data collection, now providing real-time guidance and corrective feedback. This creates a continuous care loop that does not rely on constant human intervention, effectively scaling the reach of existing staff and improving patient adherence. Finally, I predict a pathway revolution, which is not just about adding new gadgets; it is about a fundamental reimagining of the patient journey. By optimising physical hardware and the algorithms behind it, we are building a system that is more resilient, accessible, and scalable.

The trajectory is clear: as these technologies continue to converge, the hospital-at-home model will evolve from an alternative option into the standard of care.

Space tech

As constraints around energy, materials, and sustainability intensify on Earth, select technologies will increasingly move into space. We’re already seeing more interesting companies appear in this area as we learn more about how the specific environment of space, including extreme cold and microgravity, is well-suited to certain types of research, such as protein crystallisation and high-purity semiconductor manufacturing.

Many companies are already leveraging on-orbit processing, but as the technology develops, so too will the bounds of what is possible to achieve. Historically, satellites have gathered and compressed data before sending it back to Earth. However, they collect so much data that it suffers from downlink latency and bandwidth constraints. New technologies are beginning to show signs of enabling more computational work to be done in space, with finer accuracy and therefore less work lost. More data from satellites also equals a greater understanding of Earth.

With a greater understanding of our wider environment, we can decrease pressure here on Earth. For example, our portfolio company Karman+ is a pioneer in extra-terrestrial resource prospecting. There are vast resources in space, and we have now reached a tipping point where we are able to access them.

Streamlining through AI

Back on Earth, I see AI having a more tangible impact on everyday lives. For example, I forecast that new AI applications will lower switching costs and increase interoperability between different types of AI solutions. With APIs that can be easily integrated into workflow systems, it will become simpler to switch to the latest solution for the context you’re operating in.

As a result, I imagine we will see the consumerisation of enterprise AI, an environment that will likely make users less loyal to a single solution, creating competitive conditions that push all solutions forward. For VCs, this may make it more difficult to determine where sustained growth lies or which products are truly sustainable. The startups with the most funding could end up being the winners, as they hold the greatest resources to develop further. Only time will tell.

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