Sessions

Most building owners know their portfolio could perform better. Far fewer can say, with confidence, which building to start with, which intervention delivers the most value, and what it will be worth.
Producing that answer has traditionally meant an energy audit: expensive, point-in-time, and out of date within months. This panel examines what changes when that analysis runs continuously and automatically across a portfolio.

The discussion covers how AI is used to identify and rank optimisation opportunities, how those findings translate into performance ratings including NABERS UK, and where human judgement remains essential. The panel considers what building owners should expect from automated analysis, and what they should be sceptical of.
Attendees will learn

● What an automated optimisation roadmap contains, and how it differs from a traditional energy audit
● How to prioritise interventions across a portfolio when capital is constrained
● Where automated analysis is reliable, and where engineering judgement is still required
● How continuous analysis supports performance ratings including NABERS UK

Modern buildings are increasingly equipped with Building Management Systems (BMS), smart technologies, analytics platforms and digital tools. Yet many continue to underperform long after handover, falling short of their energy, carbon, operational and occupant comfort objectives.

This presentation explores the gap between what is designed and installed, and what is ultimately achieved in operation. Drawing on real project experience and building performance reviews, it examines the common issues that prevent buildings from delivering their intended outcomes, including control strategy challenges, scheduling issues, poor data quality, sensor inaccuracies, underutilised analytics and operational practices that drift over time.

The session will demonstrate how Health Checks and performance-focused reviews can uncover hidden inefficiencies, improve building operation and help organisations realise greater value from their existing systems without major capital investment.

Attendees will gain practical insights into:

- Why many smart buildings still underperform after handover.
- Common issues identified through building performance and controls reviews.
- The role of controls, data and operational practices in achieving better outcomes.
- Practical approaches to improving energy performance, occupant comfort and decarbonisation.
- How building owners and operators can unlock more value from existing systems and technologies.

Whether you are a building owner, facilities manager, operator, asset manager, project manager, or building performance professional, this session will provide practical lessons and real-world examples that can be applied to both new and existing buildings.

Most energy reduction strategies start in the wrong place. They start with a target, a piece of equipment, or a retrofit, before anyone has actually established where the energy is going and why. The result is guesswork dressed up as strategy: cuts that look good on paper but don't survive contact with a real building.

This session makes the case for starting somewhere less exciting but far more effective: visibility. You cannot make meaningful cuts to consumption or cost that you cannot see, measure, and attribute. Submetering and granular energy monitoring aren't just a compliance checkbox or a nice to have dashboard, they are the foundation that everything else in an energy management strategy is built on.

Kuldeep will walk through why so many buildings are, in effect, flying blind: relying on a single monthly utility bill to understand a year's worth of complex, dynamic energy use across dozens or hundreds of circuits, tenants, and systems. He'll unpack the hidden costs that stay invisible without proper metering, from phantom loads and base load creep to equipment running needlessly outside occupied hours, and explain why these costs are often larger, and easier to fix, than most facilities teams assume.

The session will also cover how visibility changes behaviour, not just budgets. When tenants, occupiers, and facilities teams can actually see consumption in near real time, and when that consumption is tied to accountability through tools like tenant billing, energy use starts to fall without a single piece of new equipment being installed. Kuldeep will share practical examples of how submetering and tenant billing work together to shift incentives and encourage the kind of everyday behaviour change that top down efficiency mandates rarely achieve on their own.

Finally, the session looks ahead to what becomes possible once visibility is in place: connecting metering data into building and energy management systems (BMS and EMS) to automate responses, build a genuinely defensible business case for further investment, and give facilities and sustainability teams the confidence to make faster, better informed decisions.

Attendees will leave with a clear, practical framework for thinking about energy management in the right order: see it, understand it, then cut it. Whether you're responsible for a single site or a large portfolio, this session will change how you think about where an energy strategy should actually begin.

Energy data is the starting point for any meaningful optimisation work. The first question is: where does the data come from? It may be drawn from utility metering, Building Management Systems, or manual meter readings, and the source will vary depending on the building portfolio. Just as importantly, we need to understand the quality and reliability of that data. In my experience, this can be influenced by a range of factors, including the type and age of the meter, its location, and the frequency of readings. Even new buildings can experience metering issues, such as intermittent communication or connectivity problems.

Once the data has been collected and consolidated, it needs to be stored, reviewed, and analysed in a way that supports informed decision-making. Energy data platforms, including those linked to Building Management Systems, can help identify trends, highlight anomalies, and provide insight into how energy is being used across a building or portfolio. However, the technology alone is not enough. As energy managers, we need to be able to interpret the analysis, challenge what the data is telling us, and determine the right corrective or preventative actions. That means considering wider variables such as weather, occupancy, building performance, HVAC systems, controls, mechanical and electrical infrastructure, and maintenance activity. I can bring to life some examples of this.

Having practical knowledge of these variables is what enables us to move from data analysis to real optimisation opportunities. It helps us identify where action is needed, prioritise interventions, and develop a credible plan. Successful delivery depends not only on the quality of the energy data, but also on reliable information about the building services and on delivery partners who can manage and implement optimisation projects effectively.
After implementation, it is essential to capture the results. This supports continuous improvement and helps demonstrate the value of the work to stakeholders. At project level, outcomes should be clearly linked to wider corporate energy and sustainability targets, as well as to portfolio priorities and investment frameworks.

Too often, this is where the energy management story ends. But we should also think about engagement and storytelling as part of the process. By explaining the impact of an optimisation project in a way that is relevant and accessible, we can help building users, the public, and other stakeholders understand the benefits and feel part of the journey. Ultimately, effective energy management is not just about data and systems; it is about helping people understand the role they can play in delivering better outcomes.

As energy costs rise and net-zero targets tighten, optimising building performance has become a critical priority. However, many organisations still rely on reactive approaches and disconnected systems that limit their ability to act effectively.

This session explores how AI-driven energy optimisation is transforming the way buildings are managed — shifting from passive monitoring to continuous, intelligent optimisation. By combining structured data and advanced analytics, organisations can identify inefficiencies, predict issues, and automatically improve performance in real time.

We will also explore how open, intelligent control frameworks are enabling a new generation of smart controllers — creating more adaptive, scalable, and future-ready building systems that support long-term sustainability goals. 

What will you learn from this session?
• How AI can be applied to optimise energy performance in real time
• The limitations of traditional, reactive energy management approaches
• How structured data enables more effective energy optimisation
• The role of open frameworks in next-generation building controls
• How intelligent controllers can adapt, learn, and improve building performance
• Practical strategies to reduce energy consumption, costs, and carbon emissions

Who should attend this session?
• Building owners and operators
• Facilities and estate managers
• Energy and sustainability managers
• Smart building and digital transformation leaders
• Consultants and system integrators
• Anyone responsible for reducing operational costs or achieving net-zero targets

As buildings evolve beyond “smart”, this session explores the shift to truly human centric autonomous infrastructure using Industrial AI. Drawing on insights from Siemens’ Autonomous Buildings whitepaper, the discussion will examine how AI driven systems can learn, anticipate and act and how the UK built environment can use these systems to optimise energy use, comfort, safety and performance. Referencing Siemens’ 2025 Infrastructure Transition Monitor and its Human-Centric Autonomous Buildings Whitepaper, the session will highlight why autonomy is emerging as a critical enabler of decarbonisation, resilience and long-term value in the built environment.

The industry now holds a great deal: continuous operational data from sensors, meters and control systems; mature machine readable ways of describing building systems; and a full body of specification and asset information created through design, construction and handover. This session looks at what becomes possible when all of it is held in one connected model that a machine can read. It covers four areas of opportunity: simulation grounded in the real components of a real building; capital planning that can be interrogated and evidenced; requirements that a model can verify itself against, including the ability to test a proposed requirement before it is made; and in use performance reaching the manufacturers who can act on it.

Technology lives in the land of 1s and 0s: on or off, perfect or imperfect. Buildings aren't like that. Walls aren't straight, and every fitout carries a thousand small compromises that add up. Ours has a two-pipe HVAC system dropped into an open space on the basis that it was probably enough BTUs, resulting in five years of unwinnable aircon wars.

The thing that makes AI frustrating for many applications, non-deterministic output, is exactly what makes it good at this. Imperfect buildings don't need certainty, they need compromise, and compromise requires reasoning. Traditional if-statement logic you'll find in a BMS has never been good at that.

I'll walk through what we built: temperature, CO2, presence, solar output and room calendars feeding a model that re-plans every 15 minutes and writes its own rules from the results. What worked, what it cost, and where this approach earns its keep in a real building.

Planned preventive maintenance schedules are built on assumptions about how equipment behaves. Condition-based maintenance (or Data Driven Maintenance) replaces those assumptions with evidence, servicing equipment when the data says it needs attention rather than when the calendar says so.

Getting there requires analysis that runs continuously across every connected system, identifies genuine faults rather than noise, quantifies each one, and puts a clear instruction in front of the person who can act on it.

This session examines what condition-based maintenance looks like when it works, using real examples from commercial property and retail portfolios. It covers the practical barriers, what site teams actually need from these tools, and why the goal is to remove tedious analysis rather than to remove people.

This session will show how building operators can move from energy auditing to actionable analytics to reduce energy use, carbon emissions and operational cost. Drawing on real project experience, AIS BMS will outline a practical three-step approach: audit building performance, investigate control and HVAC issues, and manage ongoing improvement through data, rules-based analytics and FM workflow integration. Attendees will learn where to start, how to identify savings opportunities, and how smarter controls and performance monitoring can improve comfort, resilience and long-term building efficiency.

As energy costs rise and sustainability targets become more ambitious, organizations are seeking smarter ways to manage energy consumption across their buildings and facilities. This presentation explores how Infosys Energy-as-a-Service (EaaS), combines AI, digital technologies, and integrated energy management to help enterprises monitor, manage, optimize, and monetize their energy usage. 
The session will demonstrate how organizations can move beyond traditional energy dashboards to achieve measurable outcomes through AI-driven optimization, renewable energy integration, and real-time performance monitoring. Attendees will learn how EaaS provides visibility across campuses, offices, and industrial facilities, enabling reduced energy costs, lower carbon emissions, improved operational efficiency, and verified sustainability outcomes. 
The presentation will also highlight how data, AI, and outcome-based energy management are transforming smart buildings into intelligent, self-optimizing environments that deliver both financial and environmental value.

Between the building you designed and the building you operate, a gap opens. Sensors drift. Setpoints wander. Overrides are applied for good reasons and never removed. Within a few years most commercial buildings are running materially below the intent they were commissioned against, not because anything has broken, but because everything has drifted.

The operational stack built to close that gap has not closed it. BMS analytics, fault detection, smart building operating systems and digital twin were each architected around the same primary job: to describe what the building is doing. Describing is not the job. The job is to judge whether what the building is doing is right, and to say so in terms someone can act on the same day.

This session makes the case for a different category. Not another analytics layer, but a continuous performance audit, defined by five principles: continuous in time, causal in reasoning, conclusion-first in communication, ranked by recoverable value, and verified against baseline. All five, or it is a rebrand of the tools we already have.

The argument is worked through on a single real fault on a real commercial building. One valve, quietly failing. The session traces its impact upstream to the plant driving it and downstream to the zones absorbing it, with cost attributed at every node in the chain, and follows it through to verified closure.

It closes with five questions to put to any building performance platform, and what a good answer to each one sounds like. One of the five concerns architecture rather than capability: where AI sits in the diagnostic chain, and what happens to the conclusion when it is wrong.

The intention is that you leave able to answer the question in the title about your own buildings, on your own evidence.

Many buildings have sophisticated BMS controls, but still have unhappy occupants who are uncomfortable; high emissions; and out-of-control energy bills. Through turning every-day comfort complaints into usable data, we demonstrate how you can reduce energy demand while making occupants more comfortable.

In this session expect to learn about how to collect feedback from users; and how it can be used to fine-tune temperatures for each space in the building.

We’ll share some examples from Klimatica’s projects, including energy savings; integration methods; and issues we have had along the way. Also expect to hear about communicating with users and facilities teams, to make the change needed.

This session is for Facilities managers, BMS and controls engineers, energy managers, and building operators who want to get more out of the systems they already have - at low cost and without a hardware overhaul.