Miners turn to AI and dealmaking as extraction costs rise

Mining executives are putting data at the center of exploration strategy as tougher deposits raise costs and artificial intelligence gives buyers new ways to judge assets, Deloitte adviser David Hill told Nikkei Asia.

Hill, an mergers and acquisitions adviser and former Deloitte Asia Pacific CEO, said resource companies now treat geological records, drilling histories, satellite data, and operating models as assets that can shape deal value. He compared data and AI analysis to “the new oil” for mining, according to Nikkei Asia.

The shift gives large miners a sharper deal lens. A company that can process years of exploration records can test an acquisition target’s claims before it commits capital. Executives can compare ore grades, transport constraints, water access, permitting risk, and production costs across projects with more speed than older review teams could manage.

That matters in a sector where easy deposits have drawn capital for decades. Mining companies now spend more to find, extract, and process ore in harder locations. Lower-grade deposits require more drilling, more energy, more water, and longer project timelines. Each factor raises the value of better analysis before a company buys a project or expands a mine.

AI does not remove the need for geologists, engineers, and local operators. It gives those teams a broader view of the evidence. A model can scan survey results, production logs, maintenance records, and commodity price scenarios. Then specialists decide which signals deserve capital.

M&A follows from that pressure. Large resource companies can buy smaller exploration firms that hold data-rich assets but lack capital for development. Buyers can also pursue technology teams that know how to turn raw exploration data into investment decisions. Hill’s comments point to a mining market where executives value information quality along with reserves.

The business case depends on discipline. A company that owns better data can still make a poor acquisition if managers ignore geology, community relations, or infrastructure limits. Buyers need clean records, source checks, and engineers who can challenge model outputs. In mining, a wrong assumption can lock capital inside a project for years.

Deloitte has tracked the mining sector’s push toward digital operations through its mining and metals practice. Resource companies also use AI across exploration, maintenance, supply chains, and safety programs as they try to offset higher operating costs.

The strategic implication is clear for miners: companies with better data pipelines can move faster on deals and spend less time chasing weak targets. Companies that treat exploration records as back-office material risk losing ground to rivals that can price assets with more confidence.