Rio Tinto Brings Automation, Copilot to Its Finance Function

Why It Matters

The initiative shows how AI‑enhanced low‑code platforms can streamline complex, high‑volume finance processes, delivering cost savings, speed and employee morale gains that are critical for large, data‑intensive enterprises.

Key Takeaways

• Rio Tinto automated month‑end close using Power Platform.
• Automation cut effort and delivered fastest close for largest product group.
• Power BI and Copilot reduced spreadsheet reliance and sped data analysis.
• Staff reported higher satisfaction and fewer late‑night work sessions.
• AI agents expected to expand across finance and shared services.

Pulse Analysis

Rio Tinto’s finance transformation underscores a broader shift in corporate accounting toward low‑code automation. The miner’s month‑end close once relied on a labyrinth of spreadsheets that extracted data from SAP, required manual calculations, and demanded extensive cross‑team reviews. By channeling SAP data into Power BI for journal computation and then looping results back into SAP, the company eliminated redundant steps, tightened data integrity, and accelerated reporting. This approach not only slashed the labor hours needed for close but also set a new benchmark for speed, earning commendation from the group CFO.

The Power Platform’s suite—Power BI, Power Apps, Power Automate, and Copilot Studio—proved pivotal in reshaping Rio Tinto’s finance workflow. Power BI visualized and calculated journal entries in real time, while Power Automate orchestrated data movement between systems, ensuring compliance and audit trails. Embedding Microsoft Copilot within Power BI enabled analysts to pose natural‑language queries, turning hours of spreadsheet manipulation into instant insights. The result was a more accurate, governed process that freed finance professionals to focus on strategic analysis rather than repetitive data entry.

For the wider industry, Rio Tinto’s success signals that AI‑driven, low‑code tools can deliver tangible ROI in even the most data‑heavy sectors. As finance teams witness the productivity boost and morale uplift from reduced overtime, adoption of AI agents and automation platforms is likely to accelerate across shared services functions. The next frontier will involve extending these capabilities beyond month‑end close to budgeting, forecasting, and risk management, cementing a digital‑first mindset that aligns with the “stronger, sharper, simpler” agenda championed by global enterprises.