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by Phoenix Energy Technologies on Jan 7, 2025
As we step into 2025, the hype surrounding Artificial Intelligence (AI) that defined 2024 is starting to settle into a more pragmatic understanding of what AI actually 'is' and how it can be applied to the most common use cases, the 'low hanging fruit.' In the wake of last year’s excitement, businesses are now faced with the question: What does AI really mean for their businesses, and how can it deliver tangible value beyond the buzz?
In 2024, AI promised revolutionary advancements across various sectors, particularly in asset, facilities, and energy. Yet, as the dust begins to settle, organizations are grappling with the practical realities of adopting yet a new technology. AI’s potential was never in question but realizing that potential often requires overcoming significant hurdles like fragmented systems, complex integrations, and high expectations.
So, what does AI truly look like in 2025, now that the initial excitement has faded? Let's explore how AI is evolving from a conceptual tool to a cornerstone of operational efficiency, sustainability, and long-term growth.
The Shift from Excitement to Practicality
AI’s role in asset, facilities, and energy management was once seen as the ultimate solution to a wide range of challenges. In 2024, it was the centerpiece of discussions about the future of smart buildings, cost reductions, and sustainability. But with that excitement came a rush to implement AI without fully understanding its limitations or the necessary infrastructure. Now, as we enter 2025, businesses are looking beyond the initial promises and starting to see AI for what it truly is: a powerful tool that requires thoughtful implementation and ongoing optimization, including coaching and continuous training.
The key to unlocking AI’s potential lies not just in deploying it, but in integrating it seamlessly with existing systems. For AI to deliver on its promise, it needs to be embedded within a unified framework that connects data, processes, and people. This is where the rubber meets the road for organizations. The excitement of AI’s potential must now give way to more methodical planning and execution.
AI’s Role in Refining Operations
One area where AI is already having a tangible impact is in refining operations to enhance both efficiency and sustainability. In the past, organizations in asset, facilities, and energy management have relied on basic, reactive systems like simple alarms with limited logic. Energy management, for example, often involves manual adjustments based on time schedules or emergency responses to equipment breakdowns. AI is moving this process beyond reaction to prediction. By analyzing vast amounts of data from energy meters, IoT devices, and even external factors like weather forecasts, AI can proactively adjust systems to optimize energy consumption and extend asset lifecycles.
However, the reality of integrating AI into day-to-day operations often involves complex data management challenges, including data gaps and a lack of consistency, especially when dealing with a large building portfolio. With AI’s ability to process and analyze large volumes of data almost instantaneously and fill data gaps by learning data patterns, businesses are beginning to see the true benefits of predictive maintenance. Rather than waiting for equipment failures to occur, the common 'break-fix' pattern common in multi-site commercial, AI can predict when equipment failure or underperformance is likely to happen and enable preemptive actions. This shift from reactive to proactive operations not only reduces downtime and maintenance costs but also enhances the long-term efficiency (i.e. lower energy cost) of energy-intensive assets.
Turning Data into Actionable Insights
While AI’s ability to process data is often the centerpiece of discussions, the real value comes in how that data is turned into actionable insights. Historically, businesses have struggled with silos of data, where information from energy systems, maintenance logs or CMMS systems, and occupancy levels existed in separate platforms. AI has the power to connect these disparate data streams into a unified solution, creating a comprehensive view of building performance and finding meaningful correlations among these disparate data sets.
In 2025, organizations that successfully integrate AI will no longer just collect data—using the 'let’s get all our data into a data lake' approach; they will leverage it to inform decisions in real-time. AI can identify trends and inefficiencies that would have been difficult, if not impossible, to see with traditional systems. For example, AI-powered energy management systems can dynamically adjust HVAC, lighting, and refrigeration to optimize electricity consumption based on current conditions, thereby reducing costs and improving occupant comfort. Similarly, by analyzing data on carbon emissions and energy usage, AI can guide organizations in meeting sustainability targets and minimizing their environmental impact.
Navigating Change with AI Adaptability
The business landscape is never static, and in 2025, one of AI’s key advantages is its ability to adapt to change. Whether it's fluctuating energy prices, supply chain disruptions, or new regulatory requirements, AI-driven systems can continuously learn from real-time data and adjust operations accordingly. This dynamic adaptability is a vital tool for businesses striving to remain agile in a rapidly changing world.
Consider asset management: AI can monitor equipment health and performance, predicting maintenance needs to prevent costly breakdowns. In facilities management, AI can trigger automatic setpoint and subsystem setting adjustments in heating, cooling, HVAC, refrigeration, or lighting systems based on changes in occupancy or environmental conditions, equipment health (and its predicted ability to perform under strain) ensuring optimal comfort and efficiency without wasting energy. Similarly, in energy management, AI can automatically adjust consumption patterns or recommend switching to more cost-effective energy sources during periods of high demand.
AI’s ability to provide such flexibility is invaluable as businesses strive for efficiency, sustainability, and resilience in the face of ongoing challenges. The reality is that AI isn’t just about optimizing operations—it’s about creating systems that can evolve with ever changing conditions and degrees of asset health.
Long-Term Growth: The AI Framework for Success
For businesses looking to truly harness the power of AI, success in 2025 won’t come from isolated AI applications or quick fixes. Instead, the focus is shifting to the development of comprehensive, AI-driven frameworks that connect various aspects of asset management, energy optimization, and facilities operations into a cohesive whole.
These frameworks should go beyond simply integrating AI; they must prioritize continuous learning, adaptability, and scalability. By continuously collecting and analyzing data, AI systems can drive long-term improvements in operations, reducing costs, extending asset lifecycles, and minimizing energy consumption. At the heart of these frameworks is a commitment to sustainability and profitability, ensuring that AI doesn’t just solve immediate problems but also sets the stage for future growth. Ensure that your AI vendor provides a product roadmap that is underpinned by sensible and achievable functionality to ensure that it will continue to offer value as AI technology matures and your organization evolves to use these tools.
Security and Privacy: A Growing Concern
As AI becomes more ingrained in business operations, concerns around data privacy and security are becoming more pressing. With AI systems processing vast amounts of sensitive data, businesses must prioritize robust security measures to protect against breaches and ensure compliance with regulations. But AI can also play a role in enhancing security. By monitoring real-time data for anomalies—such as unusual energy consumption patterns—AI can help detect potential security threats early and enable rapid responses.
In 2025, AI-driven security measures will become a crucial component of broader operational strategies, helping businesses safeguard not just their assets, but their data integrity as well.
Moving Forward: A Smarter, More Sustainable Future
Looking ahead, AI is no longer just a buzzword in asset, facilities, and energy management—it's becoming a central driver of operational success. In 2025, businesses will shift from the initial excitement around AI’s potential to a more focused approach on strategically integrating it into their operations to achieve long-term goals and address specific use cases. AI’s role in reducing costs, enhancing comfort, improving sustainability, and adapting to ever-changing conditions is transforming how organizations optimize their operations in ways that were once unimaginable.
For businesses, the question is no longer whether AI can deliver—but how to best harness its full potential for the future. By adopting a data-driven, adaptive approach, organizations can position themselves to not only keep pace with emerging trends but to lead the way in the evolution of asset, facilities, and energy management. The future of these industries is closely tied to AI, and embracing these technologies will improve operational efficiency while also creating smarter, more sustainable, and more resilient built environments for years to come.
