Digital by default: a cornerstone for sustainable assets

The importance of sustainability for the future of our built environment has never been more critical. The same could be said for harnessing digitally enabled intelligence. Two parallel imperatives: we must decarbonise, we must digitise. Almost inevitably, it is the union of the two that may prove key to unlocking success.  

Our recent report the State of Sustainable Assets uncovered many of the trends shaping building asset managers’ response to the climate crisis. Most notably, we asked over 4,000 asset and portfolio managers across the globe what they believed is the most significant area of investment to create greener portfolios. The favourite, alongside the likes of green skills, carbon capture technology and unified reporting standards, was data and AI. 

Given AI’s explosive prominence in the last two years, this could seem like a desperate search for a silver bullet. So how can AI genuinely advance sustainability, and why might almost half of built asset managers place such confidence in its effectiveness?  

Our Net Zero Carbon Service Lead, Andy Bolitho shares his thoughts on the scale of opportunity for data and artificial intelligence to advance decarbonisation, as well as outlining the need for a net zero data strategy.       

Smarter buildings equal smarter decisions 

Many organisations are now adopting data and AI technologies into their operations, leveraging tools to inform strategic decisions, manage risk and streamline processes. Within the built environment, we are producing raw data and information all the time, ranging from material specification to operational energy, to productivity metrics. However, such information is often siloed within single projects or platforms and is not converted into actionable insight.  

To see how data insights can be harnessed, we can look at smart manufacturing as an example of processes and equipment which rely heavily on data to drive decisions. In the last year alone, the AI manufacturing market has grown by 44% to almost $8.6 billion. Unlike traditional machinery, outputs are based on real-time insights, analysis, and performance and crucially provide replicative learnings and patterns that can be applied across devices and facilities. The difference is striking, and one which we can learn from to achieve smarter and more resilient buildings and infrastructure. Decisions can be made proactively, rather than reactively, leading to optimised operations and better performance outcomes throughout the building lifecycle.  

Relating to sustainability specifically, AI presents solutions to some of the most stubborn challenges with built assets. Among them, understanding energy usage patterns, tracking and reducing carbon and predictive maintenance to minimise inefficiencies and downtime. These applications can help combat ageing assets and demystify opaque emissions data. Tracking where and when improvements are needed could be the difference between a retrofit being viable or not, action being taken sooner rather than later, or the risk of holding stranded assets as new regulations come into play. 

Reporting reinvented: smarter, sharper, simpler  

Our report highlighted a surprising 57% of respondents globally felt ‘very able’ to keep pace with environmental regulations and reporting requirements. Whilst this is a positive outlook on how many asset and portfolio managers have a firm grasp on the environmental reporting frameworks, there is still a substantial gap where managers are finding disclosing sustainable performance challenging.  

We see this especially in sectors such as Education, which was over 10% behind the global average in comfort with reporting requirements. With a diverse range of assets from physical infrastructure to educational materials and technology, managing these assets whilst also tracking sustainability metrics holistically can be complex and time consuming. If information on different asset types becomes siloed or lost, this will inevitably lead to blind spots in sustainable performance and complicate reporting indefinitely.  

 A strategic integration of data can revolutionise reporting and disclosure. Primarily, AI can reduce the effort and fatigue which comes with repetitive, administrative reporting. With data and AI informing sustainability reports, not only are the insights more accurate, but teams can focus their expertise on other priorities. With 80% of asset managers struggling to implement sustainable solutions, automation can focus efforts to actually drive carbon down, steering people to more impactful outcomes. 

The power of predictions  

The performance and longevity of built assets is deeply reliant upon how well they are maintained and monitored over their lifecycle. With support from data and AI, asset managers can be proactive. By anticipating problems, predicting failures and defects before they happen, and tracking real-time environmental factors, managers can intervene appropriately. In turn, reducing the need for carbon and resource-intensive repairs or rebuilds unlocks more climate resilient operations. 

Looking ahead, the use of AI and modelling technology in tandem can allow managers to forecast assets energy usage, environmental exposure and other climate related risks. Augmenting sensor technology with AI can transform raw data into modelled insights and actionable intelligence, allowing better risk identification, management, and planning. Through continuous monitoring of assets, prediction and maintenance can be achieved, ensuring assets are regulatory compliant and sustainably resilient.  

Digital by design, sustainable by strategy  

To provide asset managers with digitally enabled tools that can assess the condition, usage, and environmental impacts of assets will support decision-making for current portfolios, extending lifespans and aligning to sustainability targets through the likes of renovation, repurposing, and retrofit.  

Integrating real-time data into planning, construction and operation has the potential to redefine the industry’s path towards risk resilient assets and future-proof infrastructure.