AI ambitions clash with weak data practices in mining

Geoprofessionals in mining and civil infrastructure spend more than a quarter of their working week on data management, even as organisations expand their use of artificial intelligence, according to new research from Seequent.

The findings come from the seventh Geoprofessionals Data Management Report, based on a survey of more than 1,000 professionals worldwide. It highlights a gap between growing interest in AI and the state of data practices inside many organisations.

Across sectors, respondents reported complex datasets drawn from multiple sources and stored across different software platforms. Many also cited unmanaged historical data and the time required for routine administration, alongside rising expectations around data quality, integration, and access to older information.

Angela Harvey, Seequent's Chief Customer Officer, said geoprofessionals spend more than a quarter of their time on data management and want to use that information for competitive advantage. She added that limited data frameworks mean too much time is spent managing data rather than interpreting results.

AI interest

AI use and consideration have risen sharply over the past two years, the report found. It said 51% of organisations are now using, or considering using, AI, up from 30% two years ago.

The research describes data as a prerequisite for applying AI and advanced analytics in day-to-day work, but suggests many teams still lack the structured approaches needed to support wider adoption.

Harvey said the rise in AI consideration shows an appetite for innovation, and that the next step is building stronger data foundations so these technologies can deliver a more efficient and sustainable future.

Mining focus

In mining, 80% of respondents rated data management as highly or critically important. Mining geoprofessionals reported spending almost a third of their time on data management tasks.

Despite that focus, formalised practices remain limited in many organisations. The report found that 39% have a defined data management framework in place.

Common obstacles include integrating diverse data sources, assessing data quality, and obtaining reliable historical records. Many organisations also lack a centralised "single source of truth", which can lead to duplication and inconsistency.

"Data is central to decision-making across the mining lifecycle," said Dr Janina Elliott, Seequent's segment director for mining. "The next challenge is unlocking more value from current and historical data as AI and automation become increasingly important."

Civil gaps

In civil infrastructure, 69% of respondents rated data management as highly or critically important. Civil geoprofessionals said they spend more than a fifth of their time on data management.

The report found that 41% of civil respondents have an established data management framework. Only 30% maintain a formal data chain of custody to track data from collection through storage and use.

These gaps can affect governance and accountability, particularly on long-running projects involving multiple contractors and handovers. They can also limit how confidently teams combine datasets across different project stages.

Pat McLarin, Seequent's segment director for civil, said geoprofessionals spend about a day a week on data management but still face challenges that affect project outcomes. He added that while there is a desire to be data-driven, the foundational frameworks are often missing.

Seequent, a Bentley Subsurface business headquartered in New Zealand, said the report provides a snapshot of data management practices across mining and civil infrastructure as organisations consider wider use of AI and automation in technical workflows.