Back in 1999, I walked into my first job at Wales Environmental Centre. Fresh out of university, I was armed with a clipboard, a measuring tape, and boundless enthusiasm for making buildings more efficient.

Day after day, I’d visit businesses across Wales, conducting energy and waste audits. I’d survey buildings, measure systems, take notes, and then spend hours back at the office writing reports about how these buildings were performing and what measures could improve them.

Change for the Better

Then one day it hit me—and this still bothers me 26 years later: consultants are still doing virtually the same thing. The fundamental process hasn’t changed. We’re still stuck in that same methodology I used in 1999, just with slightly more data.

Since then, I’ve watched building management systems promise intelligent control, only to bury teams in interfaces so opaque that most people felt overwhelmed. I’ve watched the Internet of Things explosion put sensors everywhere and leave us drowning in fragmented information that rarely turns into action. And I’ve seen smart meters pump out data streams that largely go unused.

We can (and should) do better. The opportunity is huge. 1.2 million buildings need to get to an EPC of B in the next 5 years. To achieve this we need to be more efficient. The shift is not from humans to machines, it's to a complementary intelligence. It's to move from single point‑in‑time annual energy audits to continuous, live optimisation of client estates through a roadmap you run.

From Artificial Intelligence to Complementary Intelligence

Now we have the opportunity to change this completely. Instead of Artificial Intelligence, I prefer to think of it as Complementary Intelligence (CI). CI is not here to replace consultants—it’s here to be your co‑pilot, freeing you from repetitive data processing so you can focus on what you do best: expert analysis, strategic guidance, and client relationships.

That framing matters because trust matters. In our interviews with leading consultants, I heard the same themes again and again. As a consultant at Cushman & Wakefield put it, tools like these can be invaluable “as the initial step… to figure out which buildings they need to address first,” with the caveat that the results must be revisited and recalibrated as reality unfolds.

From Savills, we heard the most sensible adoption path:

“The first thing we would want to do is check the accuracy… we start a pilot project where we can compare with projects we already have.”

A sensible start point for any consultant. They liked that the platform is “triple validated”—by actual meter data, a physics surrogate, and learned patterns (LLM), because it builds confidence.

And the Elmhurst team captured where the industry is headed operationally:

“You need that feedback loop… baseline, implement, then recalibrate up or down.”

They talked about the need to shift from static EPC labels to live performance and trajectory, underpinned by measurement & verification (M&V). That’s the heart of Complementary Intelligence: prove the saving, don’t just predict it.

What CI Looks Like in Practice

When we built OptimiseAI, we made two deliberate choices:

1. Keep the consultant in the driver’s seat. Many clients don’t want another portal; they want outcomes. As one consultant told us, their preference is often to

   “present the results… we’re not giving [clients] access to the dashboard,”

   because consultants interpret, contextualise and de‑risk the decisions. We designed views so your team can keep dashboards internal and publish client‑ready packs with your commentary.

2. Prove it, don’t just predict it. Accuracy bands, data lineage and M&V are essential. We clearly heard a call to “check the accuracy” and validate against known projects, with this being built into our early‑adopter workflow; Optimise tracks actual vs expected and attributes the delta so you can show what worked, what didn’t, and why.

That’s the idea behind our two products:

• Predict is the rapid triage tool: you feed in meter + EPC + a handful of building details; we triangulate against a physics surrogate and learned patterns to identify “problem children,” EPC trajectory, and opportunities across an estate, in minutes. The tools cover the “find” so you can spend your time on the “fix”.

• Optimise is the live layer: a full digital‑twin view that tracks actual vs expected, and uses a machine learning layer to propose a specific implementation plan. Over time the digital twin recalibrates after interventions, and blends static measures (fabric/plant) with dynamic ones (set‑points, schedules). Where BMS actuation isn’t available, we provide what to set & when playbooks, even OEM‑specific “how‑tos”, so action doesn’t stall.

What Consultants Told Us We Had to Get Right

• Start at portfolio scale, move to depth. As one Cushman & Wakefield lead put it: “We would use Predict for rapid portfolio analysis… to look at where the problem buildings might be.” Predict exists precisely for this—find the outliers, give an initial (low cost) baseline to clients, then go deep where it matters.

• Make outputs defendable. Boards and capital committees need confidence. One consultant described a world where teams compile massive spreadsheets to justify TM54‑style cases and then struggle to keep them current; he emphasised the importance of an M&V loop that proves outcomes after the fact. We’ve encoded that into the workflow.

• Target the right users. We were reminded that many end clients “will probably struggle with software,” and that equipping consultants, not bypassing them, is the scalable route. That aligns perfectly with our co‑pilot stance.

• Acknowledge the human layer. Cushman & Wakefield’s team highlighted that accuracy is never 100%, and that revisiting and recalibrating is part of the craft. AI should drive initial efficiency but it is a complementary intelligence, with the consultant using their experience to prove the analysis and recommendations.

From “Energy Audit Then Goodbye” to a “Live Client Roadmap”

I believe the next few years is about turning static audits into continuous optimisation. One consultant we spoke with noted the ongoing policy intent behind MEES/EPC targets; the market is clearly moving from labels to live performance and trajectory.

Boards are increasingly asking for real‑time decision data; consultants want instant business cases they can stand behind. CI lets you offer a programme—a living plan with clear interventions, ranked by ROI and impact, verified over time. It’s stickier for clients, better for outcomes, and frankly, more rewarding for consultants.

Our job is to make that shift painless: rapid triage to prioritise, dynamic playbooks to act, and verifiable M&V to prove.

A Broader Canvas: Energy, Air Quality, and Water

Since launching OptimiseAI, every consultant I speak with gets excited when they realise they could analyse 50 buildings in the time it used to take to analyse one.

Teams realise they can widen their business models beyond kilowatt‑hours to include air quality and water usage (more on this very soon); they can chase tariff wins while CapEx projects move through design; they can walk into an investment committee with confidence in the accuracy of the triple validate data, exportable assumptions, and a plan to prove savings, not just model them.

What This Means for Your Practice

Picture this: a consultant who spends their time on high‑value strategy and implementation rather than manual data crunching. That’s not a consultant being replaced, that’s a consultant with a rocket ship.

Start Simply

1. Run a side‑by‑side pilot on a handful of buildings you already know well; we’ll compare predictions to actuals and publish accuracy bands.

2. Use Predict to triage a building portfolios in minutes,

3. Once confident use Optimise to execute, measure and refine, turn the annual audit into a live roadmap with your team in the lead.

If you want to explore this approach with your clients, let’s talk. Complementary Intelligence is here to help you do what you’ve always done best—only faster, smarter and continuously.

Nick Tune

nicktune@optimise-AI.com