Advanced algorithms will enable predictive maintenance, dynamic inventory management, and intelligent supply chain orchestration. Writes De Wet Joubert, Operations and Strategic Projects Director, RS South Africa
Artificial Intelligence (AI) is reshaping industrial operations at every level. Nowhere is this transformation more visible than in the maintenance, repair, and operations (MRO) supply chain, where AI is driving efficiency, predictive insight, and smarter decision-making.
Industrial organisations have long relied on data to guide decisions, but today’s AI goes far beyond traditional analytics. Advanced machine learning and generative AI can synthesise vast volumes of information, uncover patterns across previously siloed datasets, and generate insights that fundamentally change how businesses operate. The real value of AI lies in its ability to turn fragmented data into actionable intelligence that enhances operational performance and supports strategic decision-making.
Organisations with mature processes can leverage AI to anticipate demand, reduce stock errors, and ensure critical parts are available when needed.
At the heart of AI’s impact is data. Capturing, structuring, and standardising information across processes and systems forms the foundation of effective AI deployment. When data is complete, accurate, and contextualised, AI can augment predictive maintenance where asset behaviour changes gradually and predictably, supported by reliable sensing, adequate signal quality and repeatable failure modes. Under these conditions, it can also optimise inventory and improve overall supply chain reliability. Organisations with mature processes can leverage AI to anticipate demand, reduce stock errors, and ensure critical parts are available when needed. Those still building operational foundations may struggle to realise the full potential.
RS South Africa has been at the forefront of bringing these capabilities to life. By integrating AI into MRO operations, RS enables clients to identify patterns in part usage, standardise inventory across multiple sites, and unlock efficiencies that were previously hidden in complex supply chains. The application of AI allows for more accurate stock planning, faster part identification, and optimised working capital — ensuring organisations operate with maximum uptime and minimal waste.
The benefits of AI extend beyond inventory. Predictive analytics allow organisations to anticipate equipment failures and schedule maintenance proactively, reducing unplanned downtime and extending asset lifecycles. By using AI to simplify part naming, classify spare components, and optimise procurement processes, organisations achieve cost reductions and improve operational reliability. This is particularly valuable in Sub-Saharan Africa, where industries such as mining, manufacturing, and defence may operate with ageing assets, have complex supply chains, and limited access to highly skilled technicians.
Tools to support this transformation are already in use at RS South Africa. AI-enabled applications can rapidly help to identify parts in storerooms, reduce manual input, and improve data accuracy. Cloud-based platforms provide real-time visibility, streamline procurement, and enhance operational efficiency. Together, these technologies enable RS to deliver faster, safer, and more reliable MRO services, allowing organisations to focus on strategic operational improvements rather than transactional tasks.
Collaboration and integration are key to realising AI’s full potential. By working with RS, organisations gain access to end-to-end services, from data standardisation and process optimisation to supplier coordination and inventory management. Combining technological capability with industry expertise accelerates AI adoption and ensures tangible improvements across the supply chain.
The South African context highlights the transformative potential of AI. Research by PwC South Africa shows that 81% of operations executives expect AI to boost operating profits by at least 3 percentage points by 2030, with over 50% anticipating gains of 5 percentage points or more. Yet only 13% report achieving a significant return on investments made so far, highlighting the opportunity as local adoption evolves.
Looking ahead, AI will move from optimisation to transformation. Advanced algorithms will enable predictive maintenance, dynamic inventory management, and intelligent supply chain orchestration. Organisations that embrace AI strategically, align it with core processes, and invest in data quality will not only improve efficiency but unlock entirely new ways of operating.
