The geospatial sector is undergoing rapid change as new technologies, new requirements and new opportunities continue to challenge the status quo.

In the following Q&A, Ordnance Survey’s (OS) CTO, Manish Jethwa, gives his views on turning location data into actionable insights — from AI to protecting critical infrastructure, from democratising access to working collaboratively.

The OS is Britain’s 230-year-old national mapping agency, supporting improved public services, economic growth, and national resilience.

What do you think will happen in 2026?

We often refer to geospatial data as the invisible backbone of modern policy – supporting climate resilience, smart city planning, improving connectivity and traffic optimisation, and national defence.

Valued at hundreds of billions globally, the geospatial industry is a critical asset due to its deep integration across sectors and the way location data and technologies drive growth.

At OS, we’re leading the development of next-generation geospatial technologies. The average person in the UK already interacts with OS data 42 times a day — a number set to rise as services become increasingly location-aware.

AI is set to democratise geospatial data, unlocking new ways for people to interact with location intelligence. I think we’re going to see the focus shift from interoperable data to actionable insight.

Customers don’t want lightbulbs, they want light. At OS, we often say customers don’t want data, they want insights. We’re exploring how people will interact with maps over the next decade. The future is conversational: users will ask questions and receive answers from maps and the data behind them; maps will then ask questions back.

Emerging technologies, especially agentic AI, are key to enabling this shift, but they also expand the threat surface we’ll need to manage.

In 2026, responsible AI frameworks will become standard — not just for compliance, but to build trust. Geospatial data is now one layer in complex decision-making systems. With agentic AI, verifying legitimacy and bias becomes harder, and because agents need broad access to be useful, the threat surface grows.

For OS, whose datasets support emergency services and critical infrastructure, safeguarding against disruption is vital which is why industry standards for validation, auditability, and ethical use will be essential.

What do you think is going to be new (or take off) in 2026?

Generative AI is already transforming how we interact with maps. In 2026, expect assistants that can interpret complex datasets and guide users in plain language. We’re already experimenting with AI agents that sit between developers and our APIs. This kind of automation will accelerate — but it must be secure.

Conversational and agentic AI will become mainstream, enabling natural-language queries that democratise access to geospatial insights. Imagine a planner asking, “Where’s the best site for a new school?” and receiving an answer that combines catchment analysis, transport access, and land availability — without needing specialist GIS skills.

Adopting AI isn’t just a technical shift — it’s a cultural one. To be effective, AI tools must be responsibly embedded into workflows, with a strong focus on quality, risk management, and IP protection.

This means more than new technology; it requires upskilling and, in some cases, retraining. That’s why OS is building an AI Community and AI Champions across the business, alongside curated learning pathways and an AI Accelerator to drive experimentation.

Machine learning for feature extraction, like calculating solar potential from roof imagery, is just the beginning. We’ll see more use cases like this emerge. The concept of a ‘human-in-the-loop’ will evolve into hybrid systems where AI handles the heavy lifting, but humans validate and guide outcomes.

Efficiency matters, but we must not lose the human qualities that bring depth, creativity, and value to our work and relationships with customers and partner organisations. At the same time, expect a rise in geospatial startups using AI to solve real-world problems — from environmental monitoring to urban planning.

We’re already seeing this through Geovation’s accelerator programme with GeoTech start-ups Verna, which provides a software platform to unlock investment for nature recovery, and Land App, a land management mapping tool supporting Biodiversity Net Gain, agri-scheme applications, and landscape recovery projects.

Innovation must be built on trust and provenance, because reliable data underpins everything – from future-proofing infrastructure against climate change to creating a more connected and sustainable nation.

What would you personally like to see change in 2026?

Everything happens somewhere, and geospatial data underpins it all — from emergency response to financial services and risk management — yet its importance often goes unnoticed. Skills in geodesy and cartography are becoming scarce, even as they remain critical to national infrastructure.

We need renewed investment in these foundational disciplines and a stronger effort to embed geographical thinking into mainstream curricula and technical courses.

At OS, we’re investing in curriculum partnerships and an AI academy model to future-proof our workforce because flexible, future-ready skills are essential across the sector. But this needs to go further: geospatial thinking should be part of every technical discipline, not a niche.

Security is another priority. With agentic AI, it’s harder to tell if an automated request is legitimate or malicious. Agents need broad access to be useful, which expands the threat surface.

For organisations whose datasets support emergency services and critical infrastructure, protecting against disruption is non-negotiable. Responsible AI cannot be an afterthought; it must be embedded from the start.

Trust and provenance in geospatial data are becoming critical in AI-driven systems, especially for autonomous vehicles and national infrastructure. AI can join the dots — but it can also join them wrongly. That’s why we need provenance that tracks origin, transformation, and interaction history. Smart cities and climate models depend on spatial accuracy rather than relying on AI guesswork.

The sector needs to establish clear standards for validation, auditability, and ethical AI use and it must do so collaboratively. We don’t need different versions of reality; we need a consistent source of truth. There must be a mindset shift toward an ecosystem, not competition – working with partners to extend impact and relevance, even in a competitive environment.

2026 should be the year collaboration becomes the norm, creating a unified geospatial ecosystem built on trust and shared responsible and ethical standards.