Monday Live | May 2026 | Getting Back to Basics, Part Two
There is a question the smart building industry has been avoiding for years. Not “what can AI do for buildings” but “what do buildings need to become before AI can do anything useful with them at all?”
That shift in framing is at the center of this month’s theme on Monday Live. The old basics, connecting systems and organizing data, are not going away. But a new set of fundamentals is rising alongside them, and ignoring them means hitting a wall the moment AI enters the picture.
The Old Basics Versus the New Basics
For thirty-plus years the industry has been focused on connecting systems and organizing data. That work is not done, but the goalposts have moved. The new basics are:
- Connected systems that are genuinely interoperable, not just technically open
- Data by default, structured and freed from proprietary architectures
- AI assistance is built into the workflow from the ground up
- Governance and security baked in, not bolted on afterward
- Outcome focus is broad enough to avoid solving for the wrong thing
The critical insight from this week’s discussion: the industry has spent years on connected systems and data without a clear destination. Now that AI assistance, governance, and real outcomes are visible on the other side, the value proposition for doing one and two correctly has completely changed.
The Five Pillars of the New Basic
1. Connected Systems
Being connected is no longer enough. What matters is the quality and architecture of the connection and how long it holds.
BACnet is the clearest example of this shift. The protocol is being looked at in a new light, not as a legacy standard that survived but as a critical bridge to what comes next. What BACnet carries in a points list is relationship data, topology, and context. That is the beginning of a knowledge graph. The Semantic Interoperability Working Group within the BACnet committee is actively developing exactly this capability.
The benchmark for any IoT solution entering a building today is whether it approaches what BACnet provides in depth, metadata, scalability, and longevity. Most do not come close.
2. Data by Default
Data must be the automatic output of every system, not something that requires additional licensing or custom extraction to access. This means moving away from walled gardens and proprietary formats toward knowledge graphs and standards like RDF.
When data is structured as a knowledge graph it becomes self-describing and interpretable, not just to humans but to AI agents. ASHRAE has endorsed knowledge graphs as a way to represent BACnet data, and ASHRAE 223P provides the semantic tagging standard that gives the data context. The path from a functioning building automation system to an AI-accessible data structure is a defined trajectory, not a research project.
The C4SB Semantic Buildings project is testing how different open-source semantic models can be integrated into genuinely useful knowledge.
3. AI Assistance
Technicians and engineers are already using AI daily, finding use cases no product manager would have predicted. The problem is that those efforts keep hitting walls: walled gardens, proprietary data architectures, systems designed to feed only themselves.
The killer app is not one app. It is the ability for every user to create their own solution using the data they need. Excel was not the killer app. What made it transformative was that it gave anyone access to their own data and let them do whatever they needed with it. The same logic applies now, scaled by AI. Once a building’s data is freely structured and accessible, a thousand applications become possible, built by the people who know what they need.
The Interoperable Building Box is being developed as an open environment where owners and developers run applications against live multi-system data without a proprietary platform in the middle.
4. Governed and Secure
As buildings become more connected and data-rich, governance and security move from IT concerns to core operational requirements. This means knowing who has access to what data, how it is being used, and ensuring automated decisions align with business rules and compliance standards.
BACnet SC, the cybersecurity extension introduced in 2019, is now moving into real deployment at large-scale sites. The adoption curve in this industry runs roughly a decade from introduction to mainstream. BACnet SC is on schedule. A governed and secure environment is not a future aspiration. It is arriving.
5. Outcome Focused
The industry focused on energy savings for decades because it was easy to measure: a meter, before and after numbers, and a legible ROI. Energy efficiency was never sufficient to justify the full investment in the infrastructure underneath it.
A building must do what it was designed to do, as efficiently as possible, whether that means occupant comfort, productivity, or keeping critical processes running. Energy savings is a byproduct of a well-run building, not its purpose.
Nobody demanded a hard payback calculation before deploying Salesforce. The value was intuitively legible because the operational problem being solved was visible. The first AI-native apps for buildings are beginning to produce that same response.
The Legacy Challenge and the Path Forward
The harder question is what happens to systems installed ten, fifteen, or twenty years ago. The PAE Living Building in Portland is working through exactly this. The building is five years old but was built to look like a century-old structure, and its systems were engineered two decades ago, making it an honest proxy for the installed base the industry needs to address.
The silos being integrated include BIM and design documents, lighting, battery storage, the building automation system, solar panels, water heating, electrical panels, and systems being modeled for future integration: indoor air quality, cameras, access control, fire and life safety, and operable windows tied to HVAC. Where direct integration is not available, submetering captures run times at a minimum.
The answer for legacy buildings is a semantic layer on top of existing infrastructure, not a wholesale replacement. Using the relationship data already embedded in a BACnet points list, combined with BIM documents and as-built drawings, a building’s data can be surfaced and structured without tearing anything out. The C4SB Managed BACnet project is working through these deployment challenges in cloud-native environments. The Asset Leadership Standard establishes what smart assets need to communicate and with whom.
Once data is in a knowledge graph and accessible via standard tools, the operating logic of a building can change in days rather than years. The owner of the PAE building, an engineering firm, is already writing its own applications against the exposed multi-system data. Legacy assets stop being a liability. The rip-and-replace cycle can finally be broken.
Open Does Not Mean Available
A system can be technically open, with its specification published and its API readable, yet still be practically unavailable. The data needed to make sense of it is thin. The relationships between points are not exposed. The metadata does not travel with the value.
BACnet has gone so far beyond the word “open” that the label is almost a disservice. What it provides is rich relationship data, depth of metadata, scalability across decades, and a direct path toward knowledge graphs. The Data Modeling Working Group is where that evolution is being shaped.
True openness in 2026 means autodiscoverable, context-rich, and accessible to anyone with the right permissions, not just the vendor who installed the system.
From the Janitorial Closet to the Enterprise Layer
Building operations have historically been parochial. No matter how wide you draw the circle, the conversation tends to stay small. Energy savings became the dominant value proposition not because it was the most compelling outcome but because it was the easiest to quantify.
Enterprise technology has been a trillion-dollar business in every other vertical without a hard payback calculation at the door. The value of accounting automation, CRM, and ERP was intuitively legible because the operational problem being solved was visible to everyone running a business.
Buildings are approaching that same inflection point. AI may be what finally makes the value of well-structured building data legible to the people who control capital allocation. The infrastructure work happening now, freeing data, building knowledge graphs, and connecting silos, is laying the fuse. AI is striking the match. The applications will follow.
C4SB Town Hall: First Rehearsal, Real Clarity
The first C4SB Thursday Town Hall took place last week. Twelve to thirteen working group leaders presented in sequence, each describing where their group stands and what is coming next. The recording and a written summary will be published on the C4SB website ahead of the next town hall on June 5th.
The Digital Building Profiles effort is also being announced: a growing catalog of every system type that could be connected in a building. Every time the list seems complete, another five or six systems surface. The goal is a shared reference inventory that grows as practitioners bring their real-world complexity to it.
What This Means in Practice
The buildings that will perform in the AI era are not the ones with the most sensors. They are the ones with the most accessible, well-structured, and secure data. That requires:
- Getting data out of existing systems, using submetering where direct integration is not possible
- Representing that data in knowledge graphs using ASHRAE 223P for semantic context
- Making the result accessible to developers, technicians, and owners writing their own applications
- Governing access and security from the ground up, not as an afterthought
The conversation is shifting from “what can technology do for my building?” to “what does my building need to become?” The answer is now clear: connected, data-rich, AI-ready, secure, and focused on real outcomes.
Those are the new basics. The work starts today.
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