Bueno Analytics London Event May 7, 2026 - How AI is Transforming Building Operations
Session 2: How Data-Driven Maintenance UK Is Shifting Building Analytics Beyond Energy Dashboards
At Bueno Analytics’ London event, How AI is Transforming Building Operations, a panel of industry leaders explored one of the most important transitions currently happening across commercial real estate: the shift from energy monitoring and dashboards toward operational analytics, Fault Detection & Diagnostics (FDD), and Data-Driven Maintenance UK.
Modéré par Claire Callan, Smart Places Technical Director at WSP, the panel brought together operational, sustainability, and engineering perspectives from:
- Allan Fourie, JLL
- Nadine Lawless, Avison Young
- Suki Gilliland, CBRE GWS
The discussion focused on why whole-building energy management often only delivers incremental improvements, and why the next stage of building optimisation increasingly relies on equipment-level analytics, operational workflows, and AI-assisted maintenance strategies.
Why Data-Driven Maintenance UK Is Moving Beyond Dashboards
One of the clearest themes from the panel was that the industry is steadily moving beyond static energy dashboards toward more operationally focused building analytics.
While metering and reporting remain important, the discussion highlighted that many organisations are now asking a more practical question:
what operational actions are actually being taken from the data?
The panel explored how Data-Driven Maintenance UK is increasingly being used to:
- prioritise operational issues
- identify hidden HVAC inefficiencies
- improve maintenance workflows
- reduce reactive fault-finding
- support continuous optimisation
This operational shift is also changing the role analytics platforms play inside buildings.
Rather than simply reporting performance, modern analytics platforms are increasingly expected to help engineering and facilities teams:
- identify faults faster
- prioritise actions
- validate remediation
- improve tenant comfort
- maintain optimisation over time
The Reality of Operational Optimisation
A particularly strong theme throughout the discussion was the operational reality behind building optimisation.
The panel reinforced that analytics tools alone do not automatically create performance improvements. Successful outcomes still depend heavily on engineering engagement, governance, operational processes, and behavioural adoption.
“It’s not the magic wand. If the engineers are not on board, you’re going to pay licence fees every year and not get anything from it.”
— Allan Fourie, JLL
Allan spoke candidly about the challenge of introducing new technology into operational teams, particularly where engineers may initially see analytics as additional workload or a threat to existing processes. He stressed that successful deployment depends on making tools genuinely useful for day-to-day operations.
The panel also discussed how operational optimisation can degrade over time if buildings are not continuously monitored.
Nadine Lawless highlighted an example where reverting systems back to their original commissioned settings resulted in significant energy savings after operational drift had occurred post-handover.
“Making changes to inefficiencies in your BMS are low cost but high reward. It’s about educating and communicating that to the right people.”
— Nadine Lawless, Avison Young
This reinforced one of the major themes of the evening – many buildings already contain operational savings opportunities, but the challenge is often identifying, communicating, and acting on them consistently.
AI, FDD & Equipment-Level Analytics
The panel also explored the growing role of AI within building analytics and Data-Driven Maintenance UK.
Claire Callan noted that while AI capabilities are evolving rapidly, successful AI deployment still relies heavily on:
- data quality
- governance
- operational integration
- trusted workflows
She also highlighted the growing tension between rapid technology innovation and operational trust inside large organisations.
AI is very helpful now on finding signals in noise. Sometimes it also finds noise in noise.”
— Claire Callan, WSP
The discussion reinforced that the most valuable use cases for AI currently involve:
- identifying hidden inefficiencies
- surfacing operational anomalies
- improving prioritisation
- reducing manual analysis time
- helping broader operational teams interpret complex building data
Suki Gilliland shared practical examples of how equipment-level analytics and FDD rules can identify issues that would otherwise remain hidden inside normal building operations.
“You want to be constantly hitting the mark in terms of optimisation.”
— Suki Gilliland, CBRE GWS
The panel discussed examples including:
- chauffage et refroidissement simultanés
- valves leaking through
- performance degradation over time
- boilers operating unnecessarily
- hidden energy wastage inside control systems
Importantly, the discussion reinforced that the real value of Data-Driven Maintenance UK comes not simply from identifying faults, but from embedding analytics into day-to-day operational workflows.
The Human Side of Data-Driven Maintenance UK
One of the strongest insights from the session was that successful analytics adoption remains as much about people and operational culture as technology itself.
The panel repeatedly returned to themes around:
- behavioural change
- operational readiness
- collaboration
- communication
- user adoption
Claire Callan described how many organisations are now investing in structured technology adoption programs to help operational teams integrate analytics into their daily workflows.
The conversation also reinforced that Data-Driven Maintenance UK is not simply about adding more data into buildings. Instead, it is about creating operational frameworks that help teams:
- interpret information faster
- reduce investigation time
- prioritise high-value actions
- maintain optimisation continuously
- improve operational consistency
This shift is becoming increasingly important as labour constraints, engineering shortages, and growing building complexity continue affecting the UK market.
From Monitoring to Operational Intelligence
As the panel concluded, a clear message emerged:
the future of building analytics is operational.
Commercial real estate is steadily moving beyond static dashboards and annual reporting toward continuous operational performance management supported by:
- FDD
- Analyse pilotée par l'IA
- Data-Driven Maintenance UK
- equipment-level optimisation
- operational workflows
- continuous commissioning
The session provided attendees with a practical look at how building analytics is evolving from a monitoring tool into an operational intelligence layer supporting engineering teams, ESG objectives, and long-term building performance.
The discussion also reinforced that while AI and analytics are becoming increasingly powerful, long-term success still depends on combining technology with operational engagement, governance, and continuous optimisation practices.
The Risk of Immature AI Platforms
One of the most candid moments of the session came during the closing discussion around the rapid growth of AI startups entering the building analytics market.
The panel acknowledged that while AI and operational analytics are now delivering genuine value across commercial real estate, the market is also becoming crowded with newer platforms making broad optimisation claims without the operational maturity or historical data foundations required to support them reliably.
Allan Fourie highlighted concerns around the number of emerging AI optimisation companies currently entering the European market, warning that immature platforms with limited operational history can create significant risks for clients if solutions fail to deliver expected outcomes at scale.
The discussion reinforced that successful AI-driven optimisation relies heavily on:
- long-term operational datasets
- mature machine learning models
- domain expertise
- scalability
- operational validation
rather than simply layering AI interfaces over limited historical building data.
“First question always is, how old is your data?”
— Allan Fourie, JLL
Allan also stressed the importance of understanding whether platforms have been proven at scale inside real operational environments, particularly across large and complex portfolios.
The panel discussed how poorly implemented analytics projects can create long-term hesitation within organisations, slowing broader adoption of operational analytics and reducing trust in future technology deployments.
Key Takeaways
“This stuff requires domain expertise.”
— Hugh Amoyal, Bueno Analytics
The session concluded with a broader industry message:
as AI adoption accelerates across commercial real estate, building owners and operational teams are increasingly looking beyond marketing claims and focusing more heavily on:
- operational credibility
- engineering capability
- data maturity
- measurable outcomes
- long-term scalability
This closing discussion became one of the strongest themes of the evening, reinforcing that the future of operational AI in buildings will depend not only on innovation, but on proven operational performance and trusted delivery.
If you would like to discuss how Data-Driven Maintenance UK, FDD, and operational analytics can help improve building performance and reduce maintenance workload across your portfolio, contact Bueno Analytics for more information.
Intervenants :
Claire Callan
WSP - Smart Places Technical Director
Nadine Lawless
Avison Young - Associate Director - Sustainability Manager
Allan Fourie
JLL - Technology Lead – Property Management
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