Geospatial demand outpaces team capacity in Britain

Landmark Geodata has published research showing that demand for geospatial insight is rising faster than many teams can support. The findings are based on a survey of 77 geospatial and GIS professionals in Great Britain.

The study found that 83% of respondents had seen increased organisational demand for geospatial data, analysis or outputs over the past 12 months. At the same time, 78% said demand for geospatial outputs was rising faster than team capacity, pointing to growing pressure on staff and systems.

Geospatial data is used across infrastructure, utilities, land and property, environmental services and finance, where organisations rely on location-based information for planning, asset management and risk assessment. The research suggests that broader use of these tools in decision-making is increasing the strain on specialist teams.

Almost all respondents, 95%, expected geospatial insight to play a greater role in business decisions over the next two to three years. Nearly half, 48%, said geospatial work was already embedded through specialist teams or strategic platforms.

Skills gap

The survey also highlighted staffing concerns. Four in five respondents said demand for GIS and geospatial data skills would outpace supply over the next two to three years, suggesting recruitment and retention could become bigger issues as workloads expand.

That pressure comes alongside persistent operational constraints. Only 19% of those surveyed described their systems and data sources as highly interoperable, while integration problems were identified as the biggest obstacle to using geospatial data effectively.

Respondents said teams spend an average of 33% of their time preparing data before analysis can begin. That suggests a significant share of working hours is spent formatting, organising and connecting information rather than analysing it.

AI uptake

Many organisations are also turning to artificial intelligence to manage that burden. The research found that 68% already use AI in geospatial workflows, while another 25% plan to adopt it within the next year.

Among those already using AI, 83% said it was applied to analysis and insight generation. A larger share, 88%, expected AI to automate more geospatial workflows over the next two to three years.

The figures suggest AI is moving from experimental use to routine application in geospatial work, particularly where teams are handling growing volumes of data and repeated manual tasks. Even so, automation alone may not resolve deeper issues around data integration and workforce capacity.

The research was carried out between April and May and covered both senior decision-makers and practitioners responsible for technology adoption, spatial data use and environmental strategy. Participants came from sectors including infrastructure, utilities, environmental services, land development and finance.

Josh Rains, Managing Director, Landmark Geodata, outlined the challenge facing organisations that use geospatial information.

"The market research found that the challenge for many organisations is not a lack of data. Most now have access to more information than ever before. The challenge is turning that information into decisions quickly enough to keep pace with growing demands on teams and increasing complexity across infrastructure, property and environmental management.

"As geospatial insight becomes more embedded in day-to-day decision-making, the focus needs to shift from simply producing outputs to enabling better business outcomes. When skilled professionals spend significant time preparing and organising data, that limits their ability to test assumptions, interrogate risks and apply their expertise to the questions that matter most.

"As location-based insight becomes more central to planning, asset management and risk assessment, the opportunity for many organisations lies in making geospatial data easier to access, structure and use. Those best at adopting this approach will enable their teams to spend less time managing information and more time applying insight to real-world decisions," said Rains.