This article is adapted from “Most Companies Have AI Tools, But Many Don’t Rewire Themselves for AI,” originally published in Forbes by Gaurav Singal, Chief Technology Officer at ConstructConnect®.
In short:
- AI speed alone isn't enough. AI must support accurate, confident decisions.
- Trustworthy AI is grounded in construction context, project data, and industry knowledge.
- AI in preconstruction should fit real workflows, reduce repetitive work, and keep professionals in control.
- ConstructConnect is building AI to create more capacity for higher-value work.
Before a commercial building can handle new equipment or more demand, its electrical system may need more than an extra outlet. A proper rewire starts with understanding the existing system. It requires planning around how the building is used and making sure everything works together.
AI in preconstruction needs the same approach. Adding a feature is not the same as rewiring the work. AI is often sold on speed, but a fast wrong answer is worse than a slower right one. The best AI helps preconstruction teams move faster without sacrificing the context and judgement needed to understand scope, review changes, and make confident decisions before bid day.
That is the idea behind a recent Forbes article by ConstructConnect Chief Technology Officer Gaurav Singal. He describes rewiring for AI as changing the data, knowledge, and work processes underneath the tool, so AI becomes part of how work gets done. In preconstruction, that means building AI around project context, construction expertise, and the way professionals make decisions. The goal is not simply to add AI, but to make AI useful in the work.
Rewiring starts with construction context
A rewire begins with understanding the existing system. AI begins with the same foundation: reliable information and the context to interpret it.
Gaurav puts it plainly:
“An agent on an undocumented data model will fabricate. An agent on a semantic layer will reason.”
A “semantic layer” is simply a clear map of what information means and how it connects to the rest of the project.
In preconstruction, that means more than recognizing lines, symbols, or objects in a plan set. AI also needs to account for the drawings, notes, details, revisions, and scope around them.
The data layer tells AI what is in the project. The knowledge layer helps it interpret what that information means in a construction setting. A revision can change a quantity. A note can change the meaning of a detail. An addendum can change the scope. Without that context, AI can miss changes or misread details, leading to rework, underbids, and lost margin.
That is why construction-focused AI must be grounded in project information and construction knowledge, not just trained to process documents.
Rewiring means fitting AI into the workflow
A building rewire has to be planned around the people and work that depend on it. The work may need to be phased and coordinated so the building can keep operating. AI should fit into preconstruction in the same way.
That is the risk Gaurav describes:
“Most organizations are running AI on top of their existing operating model. They installed a tool, but they didn’t ‘rewire’ for it first.”
An AI feature will not improve the preconstruction process if it creates another disconnected step. If teams must export information, reformat it, re-enter it, and reconcile what changed, the AI technology has shifted work instead of eliminating it. That misses the point, entirely.
Gaurav makes the broader point directly:
“The operating model is the bottleneck, not the tool.”
Making AI fit your workflow does not mean keeping everything exactly the same. It means using AI to cut repetitive work, make review easier, and help your team get from project information to the next decision with fewer steps.
We saw this internally. More than 90% of ConstructConnect engineers were already using AI tools, but that did not automatically help teams deliver work faster. The real improvement came when teams changed how they worked together around AI instead of simply adding it to the old process.
Construction companies face the same challenge. Making one task faster is helpful, but the bigger benefit comes when the entire team can use project information to make better decisions, estimates, and bids.
Rewiring creates capacity for professional judgement
When the data, knowledge, and work processes are built together, AI can take on more repetitive work while professionals spend more time on decisions that require experience.
Gaurav explains the difference this way:
“A productivity tool makes you faster at what you were already doing. An AI agent can completely change what you’re doing.”
For preconstruction teams, that does not mean handing decisions over to software. It means creating more capacity to analyze scope, protect margins, coordinate information, and grow the business.
Sheri Winslow, lead estimator at AKS Interior Systems, describes that shift in practice. Takeoffs that once took days can now take about 20 minutes. But the greater value is what her team does with the time: analyzing scope, protecting margins, growing the business, and teaching new estimators strategy and construction business goals instead of basic tracing.
The technology is not perfect. Her team still skips drawings that are too cluttered for AI to interpret reliably. That is professional control: use AI where it helps, review the output, and rely on experience when judgement is required.
Read the AKS Interior Systems customer story or Sheri’s full interview for the details.
What rewiring looks like in practice
We are applying this approach across the ConstructConnect preconstruction portfolio. The focus is not on adding an AI label to every feature, but rather building tools around three customer needs:
- Construction context: AI should be grounded in the project information and industry knowledge professionals use to make decisions.
- Workflow fit: AI should reduce repetitive work without creating another system or extra steps for preconstruction teams to manage.
- Professional judgement: AI should support the people responsible for understanding scope, evaluating risk, and deciding what happens next.
These principles guide how we build AI-powered tools for construction professionals. Our team considers the information construction professionals work with, the processes they rely on, and the judgement they bring to every decision, so AI supports their work instead of adding complexity.
The AI bar should be high
Construction professionals should expect more from AI than speed. They should expect technology that fits the work, acknowledges its limitations, and improves the capacity of the people using it.
Gaurav’s conclusion about how companies should approach AI applies to the tools construction professionals choose:
“The agentic era doesn’t reward early adopters of tools. It rewards the ones who rebuilt for it.”
In preconstruction, rewiring means looking beyond whether a tool has AI. The better question is whether the company behind it has done the harder work: grounding AI in construction data and knowledge, fitting it into real workflows, and keeping professionals in control of decisions that affect scope, risk, and margin.
That is the standard guiding us at ConstructConnect. We are building AI-powered tools around the work construction professionals do, while acknowledging where human review and experience still matter. The goal is not to replace expertise or add another system to manage. It is to reduce repetitive work and give teams more capacity for analysis, collaboration, and better decisions.
Speed matters, but it is only half the equation. The right AI should help teams move faster without sacrificing confidence or control.
Read Gaurav Singal’s full Forbes article to learn more about how ConstructConnect is building for the next era of AI.
