TECH & AI

How RPA systems help RPA systems contain software robots that automate specific tasks that are often repetitive and rule-based. These tasks include data entry, reporting and system monitoring, which can slow down production times within a company.

In mining specifically, RPA can be applied to procure-to-pay cycles, accounts processing and financial reporting. Businesses can tackle these back-office functions through automated systems and upskill current staff as opposed to a complete replacement.

Infosys, a global leader in nextgeneration digital services and consulting, works with businesses to implement RPA systems in everyday operations. The company reports that RPA has delivered a 30-80 % reduction in manual effort, resulting in fewer errors, improved productivity and reduced cycle times.

According to an Infosys case study, a large gold mining company improved productivity in its back-office procurement and finance functions by 35 % through RPA technology. By speeding up administrative and procurement processes, RPA allows mining companies to adjust to changes in demand and pricing.

Key benefits

• Reduces manual work in back-office tasks like invoicing, payroll and procurement

• Speeds up compliance reporting for safety and environmental regulations

• Cuts equipment downtime by triggering maintenance checks through sensor data

• Unifies fragmented data across legacy and modern systems

Future innovations RPA is being combined with AI to handle more complex tasks, including intelligent document processing and computer vision.

Infosys has recently developed AI-driven tools such as BlastAID, which automates blast design within mining operations. Although this is not a typical RPA system, the implementation within the mining industry signifies a shift towards AI platforms.

The wider RPA market is projected to reach US $ 247bn by 2035, as automation technology is set to scale across multiple industries.

For mining companies, combining RPA with AI agents can enable further automation of complete tasks rather than isolated assignments. This expansion from back office operations to more specialised applications can support exploration and production planning to meet mineral demand.

of mining companies are already realising a positive return on investment from AI agents, or expect to within the next year

110 October 2026