How AI Can Turn Facilities Management from Reactive to Proactivess

Exclusive Interview with Sangeetha B, CEO of Amantra Facilities Management

1. AI and predictive maintenance are gaining traction in facilities management. Why should facilities managers consider transitioning from traditional maintenance models to AI-driven systems?

AI’s impact can be seen most clearly in its ability to preemptively address issues before they escalate. Instead of waiting for things to break, AI systems predict when equipment is likely to fail by analyzing real-time data from across the facility. This typically leads to significant improvements in operations, reductions in emergency repairs, and minimal downtime. It shifts the focus from managing isolated assets to improving the performance of the entire facility. It helps managers transition from an asset-centric approach to managing an interconnected ecosystem.

2. Where is the return on investment (ROI) most visible when adopting AI-driven predictive maintenance? Is the impact immediate or more long-term?

Energy savings and reduced maintenance costs become evident almost immediately, particularly when AI uncovers inefficiencies that were previously unnoticed. However, the true return on investment is more apparent over time. The long-term impact on the bottom line will be significant—lower repair costs, optimized energy use, and extended equipment lifespan. It’s a comprehensive savings solution at the facility level.

3. Does data quality come into the picture with AI-driven maintenance?

AI thrives on real-time data, and it’s not just any data—it needs to be high quality. This includes sensor data monitoring temperature, humidity, vibrations, air quality, and energy usage. However, in older buildings, outdated or inconsistent sensors can compromise data quality. To ensure accurate predictions, facilities must standardize their sensor systems and implement robust data governance practices, including regular calibration and sensor maintenance. Solid data management practices are essential for accurate monitoring and analysis. Reliable data is critical for AI to deliver optimal results.

4. Despite the advantages, what barriers are preventing more widespread adoption of AI in facilities management?

Many decision-makers don’t fully grasp how it can seamlessly integrate into their existing operations or, more importantly, how it can be customized to suit their needs. This is the primary roadblock at the moment. Switching to AI can feel like stepping into uncharted territory. It’s a big mental shift. Then there’s the cost factor – installing AI systems isn’t cheap, which can make it feel like a hefty commitment up front. Those who act early to integrate AI will have a significant advantage – we are barely past the early-adoption phase, and facilities that can be proactive about integrating AI will have a big advantage in the long run.  AI isn’t just another tool, it’s a long-term strategy that will holistically transform how facilities are run in the near future.

5. How does AI contribute to sustainability efforts in facilities management?

I think it will be a game-changer. AI plays a critical role in enhancing sustainability in facilities management. The immediate effect is reduced waste and lower carbon footprints. Facilities are huge energy consumers. By continuously monitoring and adjusting systems like HVAC, lighting, and water usage, AI ensures that energy isn’t being wasted. This leads to more efficient resource use and will be a boost to all sustainability goals. As sustainability regulations tighten, AI will play an even bigger role in helping facilities meet their environmental goals while staying compliant with new standards.

6. Is AI-driven predictive maintenance a viable solution for smaller facilities with limited budgets?

AI is becoming increasingly accessible. Facilities don’t need to implement it across the board from the start. Instead, they can focus on key areas like HVAC or lighting systems, where immediate benefits can be realized. Smaller facilities can tap into AI’s potential without straining their budgets, and the long-term cost savings generated will help fund further investments as they scale AI adoption.

7. How do you see AI evolving in facilities management over the next 5 to 10 years?

AI’s role in facilities management will expand significantly in the coming years. Currently, its primary applications are in predictive maintenance and operational optimization. In the future, AI will touch every aspect of facilities management – from security to energy grids to tenant comfort. We are moving towards autonomous facilities where AI not only predicts failures but actively manages entire systems to optimize performance in real-time. The full potential of AI in facilities management is still being realized, and it will continue to drive significant advancements in operational efficiency and sustainability.