That shift is what the current wave of AI in construction is building toward, and it is worth understanding plainly before the marketing gets loud. 61% of construction firms now use AI or plan to invest more, and “agentic” is the term that will be attached to most of what they are sold next. This guide explains what an agent actually is, what one looks like in a planning workflow, and why the good versions keep you firmly in charge. The reason to get familiar now is simple: the first agents aimed at construction are arriving inside the tools your team already uses, and the gap between a useful one and a risky one comes down to a few things you can learn to check for.

Chatbot, assistant, agent: a plain spectrum

It helps to see these as three points on a line rather than three separate things. A chatbot answers questions from what it already knows, like a well-read stranger who has never seen your projects. An assistant does the same but works on material you give it, drafting the email or summarizing the spec you hand over. An agent goes one step further: given a goal, it can take several actions in sequence to reach it, deciding which steps to run and calling on tools or data along the way. In construction terms, the chatbot can explain what a rookie ratio is, the assistant can turn your notes into a clean owner update, and the agent can keep an eye on your staffing and offer to rebalance it before a gap turns into a scramble.

The practical difference is who does the connecting work. With an assistant, you are the one moving information between steps, copying the availability list into the email, then into the schedule. An agent can carry the thread itself: check availability, find the conflicts, draft the reassignment, and stop to ask you before anything is committed. None of that makes it smarter than the assistant in the next tab. It is wired to act, where the assistant only talks. Picture the difference on a Monday. With an assistant you ask for everyone rolling off in the next month, read the list, then open the scheduler and start slotting people yourself. With an agent you ask the same question and it comes back with the list already cross-checked against upcoming work and a proposed set of moves waiting for you to approve, adjust, or throw out.

What an agent looks like in construction planning

Strip away the abstraction and an agent in workforce planning is something that watches for the situations you would want flagged and offers to handle the first move. Instead of you remembering to ask who is rolling off in 60 days, it surfaces them and asks whether you want help finding their next assignment. Instead of you noticing a coverage gap on a pursuit, it raises the gap and proposes a few people who fit. The questions are the same ones a good operations lead already asks; the change is that the asking starts to happen on its own. A few shapes show up first. A certification quietly approaching its expiry, surfaced before it lapses in the middle of a job. A senior superintendent freeing up sooner than expected, flagged as a chance to chase the pursuit you had shelved. A new hire three weeks in without a next assignment, raised before they start wondering whether taking the job was a mistake. In each case the agent is watching the patterns an experienced planner watches and doing the first ten minutes of the work, so the situation reaches you already half-handled instead of as a surprise. This is closer than it sounds: Deloitte expects half of AI users to be .

This is the direction the tools are openly heading. The honest version, and the one worth wanting, was described well in a recent industry session: the assistant offers options, makes its reasoning visible, and then waits. It might tell you who has availability and ask if you want it to draft the plan, but it does not move anyone or change a date until you say so. What it does is the groundwork, so the decision reaches you ready to make with your hands still on the wheel.

The human stays in the driver’s seat

The fear that comes with the word “agent” is that software starts making calls that belong to people who know the job. The safeguard is a design choice, and it is the single most important thing to check in anything sold to you as agentic: does it keep a person in the approval seat for decisions that carry weight? The version worth adopting proposes and prepares, then stops for your sign-off before it changes a schedule, a budget, or a person’s assignment.

That line holds no matter how capable the agent gets. An agent can assemble a staffing plan and have it ready for Monday; a person still decides whether that plan is right, because the agent cannot see the conversation you had last week about someone’s plans, or the politics of which crews work well together. Treat the agent as the one that does the legwork and lays out the options, and keep the judgment where it has always lived. A useful test before you trust any of this: ask the vendor what the tool does when no person is present, and how you would review and undo a step after the fact. Good answers sound like approvals, logs, and easy reversals. If a tool instead tries to act on its own where the stakes are real, read that as a liability dressed up as a feature. The caution is earned, since Gartner expects to be scrapped by 2027, most often where they were turned loose without that kind of control.

It also helps to be precise about a word the hype blurs. The agents doing real work in the field are human-in-the-loop workflows: the AI does the legwork, and a person decides. Full autonomy, where software runs your business without you in the loop, is mostly marketing for now. Building these workflows from scratch is a specialty in its own right, and most contractors do not need to take it on. A purpose-built system that already encodes them lets you skip the building and keep the control, which is the trade most contractors will want.

An agent is only as good as its data and access

An agent that can act is only useful if it can act on something true. Pointed at scattered, stale, or conflicting records, it will take confident steps in the wrong direction, which is worse than a wrong answer because a wrong answer just sits there while a wrong action moves things. Picture an agent that believes two crews are free because nobody logged that one got pulled to another job. Acting on that, it drafts a plan that double-books people, and now the mistake has a head start on you instead of waiting quietly in a chatbot window. Everything an agent does well rests on a foundation of clean, trusted, connected data, which is the unglamorous groundwork covered in .

Access matters just as much as accuracy. For an agent to flag the right people, it needs to reach your real workforce and project records, and to do that safely it has to work inside the permissions you already have. An agent that could quietly pull salary or cost data it has no business touching is not a time-saver but a risk, so the same access rules that govern your people should govern the tool. This is exactly why the highest-value agents in this space are built on structured workforce data rather than a general chatbot bolted onto a calendar. It is the thinking behind 做厙勛圖’s purpose-built AI workforce planning, where the AI reasons over your own verified people and project data and a person signs off on the moves. Get the data and the access right, and the agent stops guessing and starts saving you real time on the work that used to eat your mornings.

Getting ready for agents now

You do not have to wait for agents to arrive to prepare for them, and the preparation is the same work that pays off today. Get your workforce data into one trustworthy place, build the habit of using assistants for the drafting and summarizing that fills your week, and decide where your team draws the line on what a tool is allowed to do without a human. That last one is worth doing as a group and writing down, because the moment an agent can act is the wrong moment to start debating what it should be allowed to touch. A practical first move is the lowest-rung version of all of this, which a step-by-step on-ramp for getting started with AI walks through.

Agents are not magic, and they are not a threat to people who know how to build. They are a way to take the watching-and-drafting load off your plate so your attention goes to the calls that need judgment. Think of it as the difference between a planner who spends Monday morning hunting for problems and one who walks in to a short list of them already drafted, each with a suggested move attached. The contractors who will get the most from them are the ones already building clean data and the habit of working with AI, so that when the assistant starts offering to take the first step, they are ready to say yes with confidence and keep their hand on the wheel.

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This piece is pitched a little higher than the rest of this series, because the people who will evaluate this are often the operations and IT leaders who care how the connection works and whether it is safe. The short version: MCP lets the AI tools your team already uses reach your own data and systems, under your own rules, without a custom integration for every tool. Here is what that means in practice.

The problem MCP solves

Until recently, getting an AI assistant to work with a company’s own systems meant a one-off integration for each pairing. Connecting your project system to one assistant was its own project; connecting the same system to a second assistant meant building it again, differently, because every AI vendor had its own way of plugging in tools. For a contractor with an ERP, a document repository, and a workforce system, that is a lot of duplicated, brittle wiring, and it is the main reason so much AI never made it past a demo. Anyone who has watched an exciting pilot quietly die has usually watched this exact problem play out: the tool worked on the slide, and then nobody could connect it to the systems where the real data lived. Industry surveys back this up, with to AI in construction.

MCP replaces that mess with one open standard. The people who maintain it call MCP to external systems, and their analogy is the clearest one going: think of it as a USB-C port for AI. Just as USB-C gave every device one shape of plug, MCP gives AI tools one standard way to connect to your data and software. You build the connection once, and any AI assistant that speaks MCP can use it. For a contractor juggling an ERP, a document repository, and a workforce system, that is the difference between three brittle one-off integrations and one standard that any approved tool can plug into.

What an MCP connection actually looks like

Three pieces do the work, and you do not need to write code to follow them. The first is an MCP server, a small service that sits in front of one of your systems and exposes specific capabilities to AI. It offers two kinds of things: tools, which are actions like “get the status of Project 402” or “list everyone rolling off a job in 60 days,” and resources, which are data like a project’s documents or a team’s assignments. The server is where you decide exactly what an AI is allowed to touch.

The second piece is the MCP client, which is the AI application itself, the assistant or agent your team opens. It discovers which servers are available and what each one offers, then calls those tools when a request needs them. Ask it to summarize delays on a project and draft the owner email, and the client calls the server’s “get project delays” tool, reads what comes back, and writes the email from real data instead of guesswork. The third piece is the model underneath, which decides when to reach for a tool and when to just answer. In construction terms, an assistant connected this way could answer “which open RFIs on the hospital job are still waiting on the architect” by calling a read-only tool that returns exactly those records, then draft the follow-up, with nobody exporting a spreadsheet to make it happen.

The part that matters most for an IT or operations leader is that MCP is only the protocol; the door into your systems stays yours to open. You decide which systems get an MCP server at all, you implement the same authentication and authorization you already use for any integration, and you can make tools read-only, restrict the ones that write or change anything to specific roles, and log every call for an audit trail. Built properly, an MCP connection follows least-privilege: the AI can see and do only what you have explicitly allowed, and nothing more. That is the point to press a vendor on, because the protocol makes tight control possible but does not enforce good habits on its own.

Why MCP matters now

MCP went from a proposal to a near-standard quickly. It was as an open, vendor-neutral specification, and within roughly a year it was supported across the major assistants and developer tools, including Claude and ChatGPT, with a growing catalog of ready-made servers for common systems. The momentum matters more than any single announcement, because when the major assistants converge on one way of connecting, the software vendors and the systems you depend on tend to follow, since supporting one standard is far less work than building for each AI separately. The promise the standard makes to a business is “build once, integrate everywhere,” and that is the part worth paying attention to: a system connected through MCP is reachable by whichever AI tools your team prefers, now and as they change, without redoing the work each time. It also means you are not betting on one AI vendor winning the market; connect your systems once and you can switch or add assistants later without tearing out the plumbing.

For a construction company, that turns a long-running headache into a manageable decision. The reason 61% of construction firms now use AI or plan to invest more, yet so little of it touches real operations, is that the data was never connected. A standard for safe connection is what moves AI from the demo to the daily job, and it is arriving across the tools your team already has.

What MCP changes for construction

The practical effect is that the systems where your real work lives can become things your AI can safely use. Your workforce system, your project records, your document repository, and your job-cost data can each sit behind an MCP server that exposes exactly the right tools and resources, under your existing permissions. The pattern reaches past people, too: your safety manuals, your spec library, and your closeout documents can each be reachable through their own controlled connection, so the assistant answers from the current version instead of whatever someone last emailed around. An assistant can then answer a real question, like which qualified people are free for a pursuit, because it is reading your verified records through a controlled connection rather than guessing from the open internet. Concretely, a labor coordinator could ask the assistant they already use who is certified and available for the substation job in August and get an answer pulled from the live workforce records, because that system is exposed through MCP with the right read-only tools. The same connection lets the assistant draft the staffing summary, while actually moving anyone stays a human decision behind your permissions.

This is also where the difference between a general tool and a purpose-built one gets sharp. Exposing raw workforce data to an AI is not the same as exposing it well, with the right actions, the right limits, and a person approving anything that changes a plan. That is the thinking behind 做厙勛圖’s purpose-built AI workforce planning: structured people and project data, reachable by the AI your team uses, with the permissions and the human sign-off built in rather than bolted on. The connection is only as valuable as the data and the guardrails on the other end of it, which is why is the prerequisite for any of this paying off.

Where this leaves you

You do not need to become an expert in protocols to make a good decision here. The questions to carry into any AI conversation are practical ones: can this tool connect to the systems we already use, does it honor the permissions we already set, and does a person stay in control of anything it changes. A fourth is worth keeping in your pocket: when the tool takes an action, is there a record of what it did and a way to undo it. MCP is what makes a clean yes to the first question possible, and it is becoming common enough that you can reasonably expect it.

There is also a choice in who does the connecting. You will see people online wiring their own connections with tools like Claude Code, and that path is real, but it is a skill to learn and a system to maintain. For most contractors the better route is a closed-loop system that already connects to the data and ships with the guardrails in place, reaching the same destination without the build and the upkeep. Using AI is for everyone; operating the plumbing behind it does not have to be.

The contractors who benefit first will be the ones whose data is already in order and whose systems are ready to connect, because a standard for connection only helps if there is something trustworthy on the other side. Get the data foundation right, understand that the connection should run under your own rules, and the arrival of MCP across your tools becomes an opportunity you are ready to use. When your AI can finally reach your systems safely, the work that used to mean exporting a spreadsheet and pasting it into a chatbot starts to happen in a single step, with your controls intact and a record of what the tool did.

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做厙勛圖 AI was an exciting launch for us last year, and we’ve been busy since that milestone. The world of AI changes by the day, and our team has been hard at work on the next generation of 做厙勛圖 AI features. This post offers a sneak peek into what’s coming in the near future.

Evolving the structure

Our first version of Ask 做厙勛圖 worked, but it was a fairly monolithic approach to the problem – essentially a sophisticated chatbot. We quickly saw real-world usage trending in two directions: data questions, but also a lot of support questions, which we were initially unable to answer because Ask 做厙勛圖 only knew its own database as a data source. It became clear we needed an agent loop with intent-based routing.

So we set about revamping Ask 做厙勛圖 internally to introduce what we call “the Receptionist”: a layer that detects the intent behind a user’s query and dispatches it to the right agent. As part of this, we renamed the original Ask 做厙勛圖 to the Data Analyst Agent, which in turn let us introduce a second agent: the Customer Support Assistant, dedicated to the support questions Ask 做厙勛圖 couldn’t previously handle. The structure looks like this:

This is already running internally, and it’s a meaningful step forward – but it doesn’t yet solve our longer-term vision: getting to genuine agents that can help with real workforce planning tasks. And one question slowly but surely emerged: is Ask 做厙勛圖 a proper foundation we can build agents on?

Hackathon to the rescue

Sometimes the best thing to do is take a big step back and let the creative juices flow, which is exactly what a hackathon is built for. At the end of April, the entire team met in Montreal with a single goal: a hackathon dedicated entirely to agents. Our product team prepared a long list of agents 做厙勛圖 could offer, and over two days our teams built and experimented with different approaches and technologies. The experience was genuinely enlightening.

It also answered our question: Ask 做厙勛圖 can become our AI foundation���not just a platform feature���but it needs one more concept: skills (also known as workflows). One model emerged: one agent, many skills and workflows.

Adding skills

Take the objective of building a team for a new project. Technically, Ask 做厙勛圖 already has all the data required to do it. What it doesn’t have is the layer of logic to understand what a good team actually is���which parameters to look at, how to weigh them, how to capture each user’s preferences, and so on.

As it happens, Claude has introduced just the right vehicle for this: skills. So what if we reused that concept inside Ask 做厙勛圖? That led us to a third agent in our internal suite: the Skill Agent, which works as follows.

Skills are described in Markdown files, loaded into Ask 做厙勛圖 through a skill registry. Each skill roughly defines:

• the type of question it should answer
• the data it requires (which can leverage the existing Data Analyst Agent)
• the workflow it performs
• the structure of the data it outputs

When a user asks a question that matches a skill, the Receptionist routes the intent to the Skill Agent, which reads and executes the appropriate skill.

The beauty of this structure is how generic it is: adding a new workflow “simply” means adding a new skill. It also unlocks what we call dynamically generated UI – because each skill defines its own contract, we can map that contract in our frontend and generate the right components for each workflow on the fly.

This has been a real breakthrough for us, but we’re still in the territory of answering questions, albeit much more complex ones. In our team-building example, and in general, how do we get from answering to doing?

Leveraging our MCP

In parallel, we’ve been working on developing our MCP (Model Context Protocol). MCP is an open standard that lets AI assistants connect to external tools and data sources. The first version was read-only, but we’ve been working since then to enable writes. The advantage of routing writes through the MCP is that it already respects all of our validation, permission guards, and business rules – because it leverages our existing API internally.

To truly turn Ask 做厙勛圖 into an agentic “Do 做厙勛圖”, we decided to dogfood our own MCP inside it. This is the architecture we���re building towards: adding a fourth agent, dedicated to performing actions suggested by the others. We see a world where any agent can emit a generic list of suggested actions, which Ask 做厙勛圖 re-injects into this fourth agent, which in turn calls our MCP to carry them out.

Put together, the picture starts to come into focus: the Receptionist understands what you’re asking, the Data Analyst and Support Agents answer, the Skill Agent runs the domain workflows, and this fourth agent turns their suggestions into real actions through our MCP���safely, within your existing permissions. Each piece is built independently, but they compose into something larger than the sum of its parts: a foundation where adding a new capability is a matter of adding a skill, not rebuilding from scratch every time.

And what about quality?

That’s a lot of building in a short amount of time. But at the end of the day, what matters most to customers is the quality of our agents. Back to the team-building example: how do we ensure we actually suggest a good team?

The missing piece tying all of this together is evals – the agent harness – which has been a hot topic across the AI world. We’re actively building our internal harness, which will let us aggressively monitor the quality of 做厙勛圖 AI across response accuracy, latency, and limitations. More to come on that specific piece in an upcoming dedicated blog post.

What���s coming next

I won’t pretend to claim that we���re finished, some of this is still in development, and the most interesting parts are the ones we���re not quite ready to share publicly. But the foundation is real: intent routing is live in production, skills are already executing in our development environment, and our MCP is on its way from read to write. The hard architectural questions are answered. What’s left is building on it.

Stay tuned. Agents are coming, and this time “coming” means we’re standing on something solid rather than sketching on a whiteboard. It’s a genuinely exciting time to be a 做厙勛圖 customer!

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Built on proven success with general contractors and their self-perform teams, 做厙勛圖 now brings its AI workforce planning capabilities to specialty contractors.

TORONTO ��� June 2, 2026 ��� 做厙勛圖, the leading AI workforce planning software for construction, today announced the official expansion of its platform to serve specialty contractors. The launch introduces two powerful new capabilities ��� Labor Forecasting and advanced Crew Management ��� designed specifically to address the complex, crew-centric demands of the specialty trades.

The expansion marks a natural evolution of 做厙勛圖���s platform, which has become the definitive workforce planning platform for top ENR-ranked general contractors and their self-perform divisions. With over 40% of the ENR 400 already trusting 做厙勛圖 to manage their most complex workforce challenges, along with a growing number of specialty contractors, the company is now delivering the purpose-built capabilities that support the needs of the trades, making it a natural choice to support the full construction workforce.

From General Contractors to the Specialty Market: A Proven Model Scales

Specialty contractors are the backbone of every project. And yet workforce planning ��� one of the highest-leverage disciplines in the business ��� rarely gets the dedicated support it deserves.

做厙勛圖 is changing that. What started as workforce planning for GCs expanded naturally when those same contractors brought work in-house and adopted 做厙勛圖 for their self-perform teams. Specialty contractors are the logical next step, with new capabilities built for the way they forecast labor and deploy their crews.  做厙勛圖 now brings the same AI-forward, data-driven model that’s transformed how leading GCs run their self-perform operations ��� real-time visibility into team composition, experience balance, and utilization ��� to the trades who execute in the field.

���做厙勛圖 has helped leading general contractors turn workforce planning into a strategic advantage. Expanding into the specialty contractor market is the natural next step – but it’s not a step we took lightly,��� said Mallorie Brodie, CEO of 做厙勛圖. ���We spent significant time listening to our existing specialty customers and learning how they plan labor, manage crews, and protect margins across fast-moving projects. They have distinct needs and deserve solutions built around those realities ��� not general contractor tools retrofitted to fit. These new features allow us to bring the same market-leading workforce planning capabilities to the specialty trades and drive greater impact across the construction industry.���

A Structural Challenge Across the Industry

The workforce pressures facing specialty contractors are not cyclical ��� they are structural. According to the 2026 Hiring Outlook (AGC, January 2026) 82% of construction firms report difficulty filling hourly craft positions ��� a higher share than at any point in the past three years. Fortune reports a 4:1 ratio of posted skilled trade positions compared to actual workers entering the labor pool (April 2026). And 做厙勛圖���s own found that the median industry attrition rate has reached 18.7%. For a specialty contractor targeting 100 net new hires, that means making approximately 125 total hires just to stand still.

It���s clear that as labor markets tighten, project complexity deepens, and workforce pressure intensifies, the trades that can plan with confidence will be the ones that win the work, protect their margins, and keep their best people.

What���s New: Labor Forecasting and Crew Management

The specialty contractor expansion of 做厙勛圖 introduces two capabilities developed specifically for the crew-centric demands of the trades:

• Labor Forecasting gives specialty contractors a standardized, visual way to model labor demand across each project using the Labor Curve. Rather than reacting to workforce gaps as they emerge, contractors can see when labor needs are expected to ramp up, peak, or taper off, then compare that curve against planned assignments. Ask 做厙勛圖 then lets you ask direct questions of that workforce data – who���s available, when, and for how long – making it easier to spot misalignment across the project portfolio, adjust crews earlier, and keep work on schedule and within budget.

• Crew Management allows specialty contractors to plan their workforce the same way they actually think about it ��� in crews. For specialty trades, the unit of work has always been the team. When a crew needs to shift from one job site to another, the logistics of tracking who goes where typically means a flood of calls, texts, and manual updates. 做厙勛圖 lets contractors move an entire crew from one project to another in a single action – with the full roster updated instantly and visible to everyone who needs to see it – and uses AI to suggest the best people to fill any gaps.

Together, these capabilities extend the core promise of 做厙勛圖’s platform to the unique operating model of specialty trades: crew-level precision, faster reallocation across jobs, and full roster visibility the moment assignments change.

“做厙勛圖 has allowed us to streamline our new hire process for the team and send out communication promptly and accurately every week,��� said Nate Unruh, Chief Information Officer, Nox Group. ���The planning and projection abilities has allowed our team to hone-in the expected headcount and ensure transfers and reassignments do not get lost in the shuffle. By having one spot to review manpower needs, all of our support teams feel more included in the planning process and allow everyone to have less meetings and get to action quicker!”

Availability

做厙勛圖 for specialty contractors is available now. Interested contractors can learn more and request a demonstration at gobridgit.com.

About 做厙勛圖

做厙勛圖 is the only AI workforce planning platform built exclusively for construction. Trusted by 40% of top contractors, 做厙勛圖 gives teams instant answers about their people, their pipeline, and their workforce gaps – so the right crews are on the right jobs, every time. Contractors get stronger project teams, smarter staffing and bidding decisions, and a workforce strategy that stays ahead of demand instead of reacting to it. 做厙勛圖 is a privately held company backed by investors such as Autodesk, Salesforce Ventures, and Sands Capital, among others.

For more information, visit gobridgit.com.

Media Contact:
Amy Palmer, Vice President of Marketing
做厙勛圖
amy.palmer@gobridgit.com

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The challenge 

Growth brings obstacles

CPPI is a general contractor with six offices across Florida. The Central Florida region has tripled in size in recent years in both headcount and office footprint.

This growth, however, also brought significant obstacles. Vice President and Regional Manager John Weaver explained the issue: “Organizational stabilization became a real challenge. Making sure that our top talent is always maximized and working on our projects and being efficient.”

To address this issue, executives met in a conference room, armed with notebooks and whiteboards, to manually piece together staffing across a growing operation.

The team knew they needed to plan 12���36 months out, but the manual process couldn’t support it. “A lot of times I have to get executives into a room,��� John said, ���And then it’s four hours to try and get to a strategic point.”

The solution 

Making the transition to 做厙勛圖

CPPI discovered 做厙勛圖 and realized that it might be the solution they had been waiting for, but not everyone bought in immediately. John started out skeptical:

“There’s not much I can’t do in an Excel spreadsheet. So when it comes to justifying an expense, I’m pretty tough.”

What soon changed his mind was the experience itself. The platform was intuitive, and a major upgrade from their previous whiteboard-centered process. John detailed how the 做厙勛圖 team showed up differently than other enterprise vendors:

“When you reach out to one of these large enterprise organizations to make a request, they’re going to tell you, yeah, we’re looking at that. It’s going to be two years. 做厙勛圖 has been different. I’ve been able to pick up the phone. Our CIO has been able to pick up the phone. And right away 做厙勛圖 jumps into a meeting with us.”

The impact

Immediate ROI through improved staffing efficiency��

CPPI saw ROI immediately after rolling out 做厙勛圖, and was able to elevate staffing efficiency from 70% to 99%.

“In our industry, the cost of people is our biggest expense. So when you make a shift from the 70s to the 90s���a 20 to 30% increase in efficiency of staff���that’s a tremendous savings and a margin shift due to a single application,” John explained

做厙勛圖 has brought measurable savings in other areas as well, with the amount of time spent planning in meetings getting cut in half.  

���Instead of struggling to get through where everybody’s going in an hour, we can do it in 20, 30 minutes and then we can start long-term forecasting, which affects our business development and our executive staff planning,��� John continued.

One additional impact of 做厙勛圖 is that it���s allowed CPPI to become more strategic and long-term-minded. The CPPI team has been empowered with the ability to toggle between three-month, one-year, and five-year views in seconds, making strategic planning part of the weekly rhythm.  

Using 做厙勛圖 as a source-of-truth, they now reach out to clients when a preferred superintendent or PM is about to become available���giving them the first shot at booking that person.

When CPPI needs to justify a new hire, 做厙勛圖 provides instant validation: every person in that role is booked, no one is coming available soon, and work is in the pipeline.

“Don’t hesitate to start putting things into the system. It’s intuitive. It’s smooth. It has an effect immediately. From a business standpoint, the thing you’ll see is immediate ROI from your investment in the 做厙勛圖 platform.”

John Weaver

Vice President and Regional Manager

What’s next?

Weaver is excited about making the most of 做厙勛圖���s ability to track which clients team members have worked with in the past. This data point currently ���lives inside his brain,��� and he recognizes that formalizing those relationships in the platform will sharpen CPPI’s ability to match the right people to the right clients.

His advice to anyone considering 做厙勛圖:

“Don’t hesitate to start putting things into the system. It’s intuitive. It’s smooth. It has an effect immediately. From a business standpoint, the thing you’ll see is immediate ROI from your investment in the 做厙勛圖 platform.”

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The strategic partnership equips Sir Robert McAlpine with 做厙勛圖 to address the growing need for proactive people planning across complex, long-horizon UK construction programmes.

TORONTO & LONDON ��� May 12, 2026 ��� 做厙勛圖, the leading AI workforce planning software for construction, today announced a strategic partnership with Sir Robert McAlpine (SRM), one of the United Kingdom���s leading construction and infrastructure companies. The partnership will see SRM adopt 做厙勛圖���s workforce planning platform to modernise how it plans, allocates, and retains the talent needed to deliver some of Britain���s most complex and consequential infrastructure projects.

Founded in 1869, Sir Robert McAlpine has more than 150 years��� experience delivering some of Britain���s most iconic projects ��� from flagship commercial developments and major NHS facilities to national infrastructure and heritage landmarks. Today, SRM operates across infrastructure, industrial, commercial, healthcare, defence, and heritage sectors, with a workforce drawn from some of the industry���s most skilled and experienced professionals. As project complexity deepens and the pipeline of major UK programmes continues to grow, the firm recognised the need for a more structured, data-led approach to workforce planning.

A Strategic Response to a Structural Challenge

The UK and broader European construction sector faces a well-documented workforce crisis: skilled labour shortages, demographic change, and the retirement of experienced project managers and superintendents are widening the gap between project demand and delivery capacity. According to 做厙勛圖’s 2026 ��� the industry’s largest workforce intelligence study ��� the median industry attrition rate has reached 18.7%. Senior talent is scarcer still; Senior Project Managers turn over at just 3.6%, but when they do leave, the impact on project continuity is significant. For contractors like SRM managing multi-year programmes, retaining and strategically deploying experienced professionals isn’t just a people issue ��� it’s a project delivery issue.

���Our people are our greatest competitive advantage, and ensuring the right talent is in the right place at the right time is central to how we deliver for our clients,��� said Nadeem Mirza, Resourcing and Workforce Planning Director, Sir Robert McAlpine. ���做厙勛圖 gives us the visibility and rigour to plan our workforce with the same precision we bring to our project programmes. In an environment where skilled talent is increasingly constrained, that capability is essential.���

做厙勛圖���s 做厙勛圖 at the Heart of the Partnership

Through the partnership, SRM will deploy 做厙勛圖’s AI Workforce Planning platform ��� the only AI purpose-built for construction workforce planning ��� marking a significant step forward in how the firm manages talent across its growing project portfolio. 做厙勛圖 builds on SRM���s own workforce history and data, surfacing patterns and suggestions that get sharper over time. These valuable insights will provide SRM with deep, immediate visibility into the experiences and skills that make each team member unique ��� spanning past projects, certifications, availability, location, and tenure. Planners will be able to ask 做厙勛圖 questions directly and receive AI-powered smart suggestions as they assemble and balance project teams, enabling the firm to move away from spreadsheet-based processes and toward a structured, data-driven model built for proactive decision-making.

With 做厙勛圖, SRM will be able to:

• Easily put the right people on every project – AI-powered suggestions recommend the right person for each role based on skills, experience, and availability, with the ability to query 做厙勛圖 directly during planning

• Align workforce plans with project pipeline – Leverage project timelines and sector mix to ensure more precise team planning with longer lead time

• Gain better team visibility – Quickly see team composition, tenure, and experience balance for active and upcoming projects

• Ensure junior talent is supported – Analyse ���rookie ratio��� to ensure junior talent is effectively paired with experienced colleagues before projects mobilise

• Better understand attrition and retention – Attrition tracking and talent retention insights can protect institutional knowledge as SRM continues to scale

���Sir Robert McAlpine is exactly the kind of contractor that demonstrates why workforce intelligence matters,��� said Mallorie Brodie, CEO of 做厙勛圖. ���They operate at the highest level of complexity, with programmes that span years and teams that must perform without margin for error. Our data shows that the companies leading the industry in workforce planning have a measurably longer planning horizon and lower attrition than their peers. Partnering with SRM to bring that approach to the UK market is something we���re genuinely proud of.���

The UK and European Opportunity

The partnership with Sir Robert McAlpine marks a significant step in 做厙勛圖���s expansion into the UK and European construction markets, where demand for structured workforce intelligence is accelerating. Major UK infrastructure commitments ��� including investment in transport, energy, defence, and healthcare ��� are creating sustained demand for construction services at a time when the talent pipeline is under real pressure. UK contractors that invest now in systematic workforce planning will be better positioned to win and deliver the decade���s most significant programmes.

Across Europe, the challenge is similarly acute. Supply chain re-shoring, energy transition infrastructure, and urban regeneration programmes are driving substantial construction activity, even as the available pool of experienced construction professionals narrows. 做厙勛圖���s platform is purpose-built to help contractors in these conditions turn workforce planning from a reactive overhead into a strategic capability.

About

Sir Robert McAlpine is a family-owned building and infrastructure company operating across the UK. We have been proudly building Britain���s future heritage since 1869.

We are honoured to have worked on some of the country���s most iconic buildings and projects.

The values at the heart of our operations include a commitment to the highest standards of safety, quality, engineering excellence, sustainability, and a steadfast focus on the needs and aspirations of our clients.

We champion equality and welcome a diversity of talent to our inclusive family culture.

Working in partnership with our clients, we aim to make a positive impact on the communities and the environment in which we operate, as we construct a better world for future generations.

About 做厙勛圖

做厙勛圖 is the only AI workforce planning platform built exclusively for construction. Trusted by nearly 40% of top contractors, 做厙勛圖 blends deep data on people and projects with AI that turns insights into action. Contractors get stronger project teams, smarter staffing and bidding decisions, and a workforce strategy that stays ahead of demand instead of reacting to it.

Media Contact:
Amy Palmer, Vice President of Marketing
做厙勛圖
amy.palmer@gobridgit.com

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The background 

Pariseault Builders does a lot of business in healthcare���a sector that demands prior experience and deep knowledge. COO Chris Integlia explains it: “Anyone can’t walk off the street and do a project in a healthcare facility. One of the barriers to entry is, how long have you been working in healthcare?”

This prerequisite in turn requires something most contractors struggle to track: detailed knowledge of who has done what, where, and when. For years, Pariseault tracked this data the way most builders do: in a spreadsheet.

The challenge 

Chasing accuracy with spreadsheets

Before 做厙勛圖, Pariseault was attempting���and often failing���to track the ins and outs of their workforce in an ever-evolving spreadsheet.

“The data that was in that Excel spreadsheet was typically characterized by one person’s memory���or lack thereof���and qualitative assessments of role capabilities by employee,” Chris explains. “It was difficult to harness. It was difficult to implement and update consistently. It just took a long time. At best it was probably 50% accurate, and it was 100% inaccurate within about an hour and a half of being deployed.”

The spreadsheet wasn’t just unreliable, it was also a blocker for collaboration.

Field operations didn’t talk to HR. Training and certifications had no link to upcoming projects. The active project list got pruned because keeping the spreadsheet alive was exhausting on its own, never mind layering in pursuits, certifications, or future staffing needs.

Downstream costs showed up everywhere. Field crews felt yanked from job to job without notice. “There was a perceived disrespect,” Integlia says. “There was no real disrespect there, but they felt disrespected. They were sent to jobs where they weren’t really needed.”

To compound the issues, project executives chasing pursuits had no way to see whether the team they wanted would actually be available a year and a half out.

The solution

The right tool without a fight

Integlia is candid about what usually happens when he rolls out new software. “Normally when I have to implement a new tool, I have to push for a long period of time to get people to see it.”

做厙勛圖 was different.

“做厙勛圖 was able to effectively convince a wide range of people from different walks of life in this industry to accept it. And that’s pretty atypical,” he says. “I got project executives, I got field operations people, I got superintendents, all jumping on board and contributing. We are making keystrokes in the system, which speaks to the functionality of the tool.”

Within months, operations, HR, and the field were working from a single source of truth for who was on what, who was coming off, and who needed certifications before the next job kicked off.

From silos to a team event

Ask Integlia what’s changed in a year with 做厙勛圖 and it all boils down to coordination.

“Now we not only have all the active projects, we have all the pursuits,” he says. “From a project executive viewpoint, they’re less excited about what’s going on in real time and more excited about what’s coming up. Can you fulfill my staffing needs? Am I going to get this job? Now with 做厙勛圖, all of leadership is able to see one platform and they’re collaborating across the board, which is making us very effective.”

That collaboration shows up in places Pariseault never had visibility before. “We’ve got guys already on an existing job, already pre-planned a year and a half out for the next job, getting certifications and training that might be unique for that job so they can just hit the road running when they get there. We never had that before.”

People in the field feel the difference too.

“Now, because we’re doing the proper planning, things are smoother. There’s more proactive communication. There’s a higher level of respect,” Integlia says.

HR isn’t getting ambushed anymore, either. “No one’s running into their office and saying I need a superintendent tomorrow. Which is what used to happen.”

Unlocking data insights

做厙勛圖 AI enters the chat

Building on the value 做厙勛圖 has unlocked so far, Ask 做厙勛圖 was introduced to Pariseault. This conversational AI assistant lets their team query workforce data in plain language. It was an immediate hit with the team.

“The very first thing I did, I started typing. I said, ���show me all the employees with AED certification.��� Normally I’d have to run a report, but bang, up it came. Then I started saying, ���tell me all my employees with OSHA 10.��� Then OSHA 30, because they may not have 10, they may have 30.”

“These are all things that I was getting answers to within seconds that historically I’d have to run a report for, and under our old Excel method could never have gotten. I’d be in an HR file, waist deep in antiquated information to try to figure that out.”

The reaction wasn’t limited to the C-suite. One of Pariseault’s business unit directors used Ask 做厙勛圖 to instantly pull up length of service for team members with healthcare experience, the exact stat project owners want to see. “The ability to answer these questions and to harvest this and to show our clients, or even show ourselves, is fantastic,” Integlia says.

Ask 做厙勛圖 is also the moment data entry started paying dividends.

“People appreciate that all the work they’ve done building a database comes full circle and is useful,” he says. “Ask 做厙勛圖 is giving us actionable data that management can use. It’s making the case for putting the data into 做厙勛圖. Spend the time, put it in, because later on you’re going to get the benefits of it.”

Asked how he’d explain 做厙勛圖 to a peer, Integlia doesn’t hedge. “Unless you’re addicted to pain, you’ve got to move over to this platform. It’s efficient, it’s accurate, it gives you actionable management data. You’re going to go from a siloed event to a team event, and you’re going to be making team decisions.”

“Unless you’re addicted to pain, you’ve got to move over to this platform. It’s efficient, it’s accurate, it gives you actionable management data. You’re going to go from a siloed event to a team event, and you’re going to be making team decisions.”

Chris Integlia

Chief Operating Officer, Pariseault Builders

What’s next?

Pariseault is still in what Integlia calls “the infancy” of its journey with 做厙勛圖, and he’s already looking at where to push next. Project tagging is high on his list: capturing the unique characteristics of a job (complicated MEPs, ground-up builds, accelerated schedules) and connecting those tags to experience tracking so BD can pitch with confidence.

The team has also started using 做厙勛圖 beyond traditional projects, tagging training as its own category and tying scheduled training to the certifications people need on the job. “We’ve gone from clawing our eyes out to get training scheduled and completed, to it’s just a matter of course now.”

For Integlia, the reason Pariseault keeps leaning in is part platform and part the people behind it.

“Open, honest, two-way dialogue is what makes a true partnership. Someone wrote good code, they made great functionality. But at the end of the day, it has to evolve through dialogue. And 做厙勛圖 has great people. Whoever gets this platform also gets the people.”

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That changes what retention actually means in practice. The conversation used to be about stopping people from leaving. Now it’s about how to plan around predictable attrition, develop the people you already have, and make assignment decisions before the exit interview rather than after it. The data backs this up clearly. Senior superintendents and project managers turn over at roughly a quarter the rate of their non-senior counterparts, which means the contractors who hold onto people through the first four years end up with a senior bench that competitors can’t easily hire in.

What follows are 50+ statistics across nine categories: the labor shortage, how turnover has shifted, what it costs, who stays and who leaves, why people leave, the commute factor, the treadmill effect, the rookie ratio, and where the workforce is heading. Most are public data from BLS, AGC, ABC, the Construction Industry Institute, the Census Bureau, and Deloitte; some come from 做厙勛圖’s , which analyzed anonymized data from 233 companies and 114,000 people, including nearly 40% of the ENR 400.

TL;DR

• Quit rates are at a nine-year low and hiring is at a record low, but the industry still needs roughly 349,000 net new workers in 2026
• Net international migration is projected to fall from 2.7 million in 2024 to about 321,000 in 2026, removing the demographic backstop the industry has leaned on
• Senior superintendents and project managers turn over at one-quarter the rate of their non-senior counterparts, making early-career retention the highest-leverage move
• The Top 50 of the ENR 400 face roughly the same attrition as the broader industry but grow at three times the rate, because they plan around turnover rather than try to eliminate it
• The average team rookie ratio sits at 36.4% and climbs to 56.2% on teams of 51+ people, with measurable consequences for safety, quality, and project outcomes
• 41% of the current construction workforce will reach retirement age by 2031, which makes the next four years of senior-tenure retention decisions disproportionately important

The construction labor shortage in 2026

Demand is outrunning supply across nearly every category, and the gap is widening as immigration policy and demographics compound the pipeline problem.

worked in construction as of March 2026, with year-over-year growth of 57,000 positions. The headline employment number is up, but the unmet demand is bigger:

• report difficulty filling open positions (AGC 2025 Workforce Survey)
• , and 80% report the same for salaried openings (AGC 2026 Outlook)
• The industry needs , rising to 456,000 in 2027 (ABC)
• Every creates demand for approximately 3,450 jobs
• report delaying projects due to labor shortages
• Project abandonment activity in August 2025

The immigration pipeline is part of why this is harder to solve through hiring alone. Net international migration (U.S. Census Bureau, January 2026). Immigrant workers make up , and that share exceeds 40% in high-activity states like California and Texas. A report being affected by immigration enforcement in the past six months, with 24% saying subcontractors lost workers as a result.

How turnover has actually shifted

Despite the shortage headlines, turnover itself has been falling, which is the part of the story most leaders miss. The in July 2025, and by February 2026 the hiring rate had dropped to , with quits at 1.5% and layoffs at 1.8%. Job openings fell to , a decline of 53,000 year-over-year.

Average employee tenure in construction sits at roughly four years according to , which is among the shortest of any major industry. The combination of lower quits, lower hiring, and short tenure overall describes a cooling labor market rather than a stable one. Fewer people are leaving voluntarily, but the industry still can’t find enough new workers to grow. The retention question shifts accordingly: less about how to stop the bleeding, more about how to keep and develop the people you’ve already invested in.

What turnover costs

The financial impact of losing people goes well beyond the cost of posting a job. Replacing a worker costs , depending on specialization and seniority, with junior craft workers at the lower end and superintendents, project managers, and specialized trades at the higher end. The cost compounds with role complexity, because the harder roles take months to source and longer still to bring up to full productivity.

The Construction Industry Institute found that a . The hidden costs sit underneath that headline number. Lost productivity during a vacancy, quality issues and rework from less-experienced replacements, and overtime to cover open positions all accumulate well beyond the direct cost of recruiting and onboarding.

“Company morale goes down, employees are burnt out because they’re going to do whatever it takes to get the job done,” says Shawn Gallant, COO at Columbia Construction. “It affects your employee retention and increases safety incidents on a project. You never want an unsafe site because you’re cutting a dollar on staffing.”

At the macro level, McKinsey projects that construction output could fall if current workforce trends persist.

Who stays and who leaves

Not all turnover is equal, and the seniority split inside two key roles is where the most useful retention data lives. The 做厙勛圖 Benchmark Report shows a striking gap between senior and non-senior attrition for the two roles that have the greatest impact on project outcomes:

Senior superintendents and project managers turn over at roughly a quarter the rate of their non-senior counterparts. The growth data tells you why: non-senior supers saw while senior supers showed , and the same pattern holds for PMs (non-senior +4.8%, senior 0.0%). Senior-level supers and PMs simply don’t move around. Trying to hire experienced talent away from competitors is an expensive long shot. The more reliable path is hiring earlier in the career arc and being intentional about keeping people through the first four years.

The tenure data shows where the retention cliff sits:

If a superintendent or PM stays past the 3.7-year median, they’re on the path to senior tenure. The contractors that figure out how to retain people through that window end up with something competitors can’t easily replicate.

“What happens when you don’t have a clear picture of your staff is you don’t see ‘John Smith’ is ready for a promotion,” says Lisa Villasmil, VP of People & Culture at Cauldwell Wingate. “So you hire an outside senior PM instead of promoting internally and backfilling the open position.”

The Benchmark Report also draws on findings from 做厙勛圖’s 2025 State of Workforce Planning survey: 100% of construction leaders agree a project team’s collective experience plays a significant role in creating positive project outcomes, and 93% have experienced talent-related impact on operations.

Why construction workers leave

Career development is the leading reason workers leave, and it outpaces compensation by nearly 2:1 across industries. The breaks down the top departure drivers:

That ranking matters in construction specifically because earlier-career superintendents and PMs are actively evaluating employers based on the work itself: the project types, owners, and delivery methods that will define their reputation and open future doors. The Benchmark Report reinforces this directly. Top contractors that plan according to the unique needs of each project type can offer newer team members the variety of experience that keeps them engaged, while ensuring they’re paired with senior talent who can mentor them.

Mental health is another factor that compounds compensation alone. CDC data shows that , and (CDC MMWR, National Vital Statistics System). Hours compound the strain: , 25% work 60 or more, and .

Commute as an actionable retention lever

One of the most actionable retention variables in construction is commute distance, because it’s a decision the contractor controls during assignment planning. The superintendent commute distribution from the Benchmark Report , which is where retention risk concentrates. Peer-reviewed research published in AERA Open found that (Santelli & Grissom, 2024). The study examined public-sector workers, but the underlying mechanism (commute fatigue compounding job dissatisfaction) generalizes naturally to construction roles where supers and PMs travel meaningful distances daily.

The construction-specific commute data shows how demanding the travel can be:

• each way
• Another
• each way

The point of pulling commute into the conversation is that it’s a variable you can adjust ahead of time. Knowing which superintendents face long commutes on their current assignments, and factoring that into the next assignment, turns retention into a planning decision that happens months before anyone starts thinking about leaving.

The treadmill effect

Attrition shows up as a growth problem, not just a people problem. 做厙勛圖’s Benchmark Report names the dynamic the “treadmill effect,” where attrition offsets hiring so companies have to run hard just to hold their position. The math is simple: an organization aiming to add 100 people with a to net the growth. At .

The real-world impact shows up in the growth distribution. In 2025, and another 26% remained flat. Nearly half the industry failed to achieve net headcount growth.

The most useful finding in the report sits in the comparison between the Top 50 ENR 400 and the rest of the industry. Top 50 contractors face , but their . The largest contractors aren’t winning because they’ve solved turnover. They’re winning because they plan around it. Proactive hiring and workforce planning, rather than lower attrition, is what separates the leaders from the pack.

McKinsey’s productivity research supports the same point from another angle: productivity for major construction projects each time labor markets tightened. The contractors that maintained planning capacity through tight markets came out ahead.

Rookie ratios and the experience mix

With high attrition flowing through project teams, one metric that has emerged among strategic contractors is the “rookie ratio,” which measures the share of newer team members (typically under one year of company tenure) relative to the total team. 做厙勛圖’s Benchmark Report puts a number on it for the first time. The , and the average masks meaningful variation by team size:

On teams of 51 or more people, the rookie ratio averages above 56%, meaning more than half the team is in their first year with the company. That has direct consequences for safety, quality, and project outcomes. Travelers’ , which analyzed more than 1.2 million workers compensation claims, found that first-year employees account for approximately 36% of all workplace injuries and 34% of overall claim costs across industries. In construction, the early-tenure injury rate skews higher because new workers are concentrated in the most physically demanding tasks before they build the muscle memory and risk awareness that come with experience.

NCCER’s research with the Construction Industry Institute shows the flip side. Trained craft workers achieve a in training, with productivity targets met more reliably and retention improved when formal training programs are in place.

The contractors who use rookie ratio well don’t just track it. They set targets for it by project type and complexity, pairing newer team members with experienced mentors and routing the most straightforward projects toward teams that can accommodate a higher share of newer workers without compromising outcomes.

Where the workforce is heading

The sectors driving the most workforce demand are also the ones requiring the largest teams and longest commitments. Year-over-year growth data from the Benchmark Report shows where the workforce is being pulled:

Solar projects stand out for the sheer scale of workforce commitment, with a . Data center construction spending , per the AIA Consensus Construction Forecast, making it the only sector showing strong growth in an otherwise weak market.

The pipeline of new workers is showing early signs of improving. The share of young adults interested in construction in 2026 (NAHB), and at a said they would reconsider construction. currently offer median wages at or above that threshold.

The demographic shift is already visible in the data. Gen Z’s share of the construction workforce , while Baby Boomers over the same period. Women in construction reached (NAHB analysis of BLS data). Deloitte estimates , which puts a clock on how much time contractors have to develop the next generation before the senior bench thins out.

What contractors who plan ahead do differently

The Top 50 of the ENR 400 are , nearly two years further than the . That gap reflects something specific about how they operate. Reliable data, integrated systems, and company-wide coordination are what extend a planning horizon, and the longer horizon is what creates the optionality the rest of the industry doesn’t have.

“Strategic workforce planning gives our clients confidence that we can provide the right people to build their projects,” says , Vice President of Operations at W.E. O’Neil Construction. “If we don’t consider all the necessary strategic factors, we won’t be able to assign the appropriate teams, and those clients won’t keep coming back.”

The supporting evidence is consistent. Contractors with realized profits on more jobs, completed more projects on or ahead of schedule, and posted better safety performance, according to the Construction Industry Institute. Career development opportunities correlate with (Work Institute). NCCER’s research with the Construction Industry Institute shows that .

The common thread across these findings isn’t a single tactic. It’s visibility. The contractors pulling ahead know who they have, where those people are, what they’ve built, and what they need next. Experience-based staffing tools like 做厙勛圖 consolidate the people, project, and pipeline data so that retention decisions happen during assignment planning, not during exit interviews. Whether the goal is closing the planning horizon gap, getting ahead of attrition before it constrains growth, or building teams with the right experience mix, the work starts with the data being in one place.

The post 50+ Construction Workforce Retention and Turnover Statistics for 2026 appeared first on 做厙勛圖.

The challenge 

Scaling preconstruction in a growing organization

Suffolk manages one of the largest portfolios in the country.

In Boston alone, the company���s largest office, dozens of major projects are running concurrently that all require large project teams.

The pieces rarely aligned.

• Estimates were disconnected from the lifecycle of a project 
• Workforce planning decisions were made without full visibility into how the project was intended to run.

���We used to use a simple Excel sheet to keep track of who might be available soon,��� explains , Project Manager and Operations Performance Manager at Suffolk. 

For a 3,000+ person organization + contractors? That doesn’t scale.

Steven continues, ���A staffing meeting would basically be: ���This person���s job is finishing in a month. Who wants them next?��� People didn���t know what was next for them and projects were understaffed until someone happened to become available.���

It was an inefficient and reactive process where leadership teams spent hours verifying information and reconciling spreadsheets. Meanwhile, estimating teams were building project budgets without a fully integrated view of workforce availability.

So, they built something new.

The solution

Building a connected platform for preconstruction

Talk to Suffolk���s National Director of Preconstruction Scott Menard for more than a few minutes and he���ll articulate everything that a connected platform should be.

He muses about connected digital ecosystems ��� where data flows across the entire lifecycle of a project so teams can ���use data when we need data for any use case.���

���The ideal state is putting in information one time and anyone who needs it has access to it.��� – Scott Menard, National Director of Preconstruction at Suffolk

That top-down vision starts in Ediphi.

���Ediphi trains our teams to think from first principles,��� says Brendan. ���We can���t just say general conditions are a percentage of cost. We have to build the team that���s actually required to execute the project ��� when people start, when they roll off, and how they���re utilized.���

To make that level of detail practical across their dozens of projects and offices, Suffolk relies on Ediphi���s cloud-based estimating environment, where historical pricing data lives inside the cloud and estimators reference what worked before to model the unique conditions of every new project.

���If you solve for the budget first, you risk creating a plan that doesn���t actually work in the field,��� Brendan explains. By structuring estimates this way, Ediphi produces something far more powerful than a cost breakdown: it creates a data model of the project itself.

From estimate to workforce planning

做厙勛圖 utilizes the estimating work done in Ediphi to unlock high-performing teams across the portfolio:

• Roles required for the project
• Start and end dates for each role
• Utilization expectations
• Assigned personnel, when known

���The most granular unit of work in Ediphi is the exact same unit needed in 做厙勛圖. That���s why the integration works so well.��� – Brendan O���Riordan, Director of Portfolio Intelligence at Suffolk

(Because the data structures align so closely, Suffolk���s data team was able to integrate the systems very quickly, notes Scott)

Once an estimate is developed, workforce plans automatically appear in 做厙勛圖, where operations leaders gain a portfolio-wide view of workforce needs.

This allows teams to see multiple projects, staffing roles, and employee availability in a single interface.

���As you build the estimate in Ediphi, you���re already thinking about the roles required for the job,��� says Steven. ���That information flows cleanly into 做厙勛圖 so we can see multiple projects and staffing plans in one place.���

From there, leadership teams can evaluate project team decisions based on, well, everything���

• Employee availability
• Relevant experience
• Project timelines
• Geographic proximity or travel preferences
• Budget

���You can see the open roles, see the available people, and match them together very quickly. In 做厙勛圖, it becomes almost plug-and-play.���

Steven Jennings

Project Manager

The impact

Smoother preconstruction, better project teams

The impact of Suffolk���s connected workflow is visible in the day-to-day lives of leadership teams.

Staffing discussions prior required large meetings reviewing spreadsheets and debating personnel assignments.

���If you���re not staffing him, I���m taking him!���

���Superintendent needed for April! Who���s got one?���

���Wait, thought she was finishing in March?���

���We would march through that every other week with 20 plus people in the room,��� says Brendan. ���We���d spend an hour or more going line by line through charts trying to figure out who was available.���

Those meetings look different now. Now, it���s just a handful of decision-makers reviewing what���s already in the system. Most decisions even happen before the meeting begins (shoutout to ).

More importantly, Suffolk has eliminated the uncertainty.

Because projects are estimated in Ediphi using , staffing discussions in 做厙勛圖 start with a clear picture of what the job actually requires.

���We added time back into our people���s lives and we���re getting better outcomes.���

Brendan O���Riordan

Director of Portfolio Intelligence

Building a process than can handle growth

Suffolk���s portfolio has grown rapidly in recent years.

Building 17.5-acre, , renovations of ; that kind of thing���.

The systems they���ve chosen to use to manage preconstruction and workforce planning have played a critical role in ensuring that that growth remains profitable.

���Our revenue growth has been very rapid over the last five years,��� Brendan O���Riordan says. ���The tools and processes we���ve put in place enable that growth ��� but more importantly, they help make sure it���s profitable growth.���

With the 做厙勛圖 and Ediphi duo, Suffolk is actively:

• Building more realistic project budgets
• Assembling stronger project teams earlier
• Reducing staffing conflicts across projects
• And improving employee and contractor experience throughout

Even Suffolk���s People and Culture teams benefit from the increased visibility.

���Knowing where someone���s next project assignment is creates a much better experience for employees,��� Brendan says with visible pride, ���That visibility helps us support people throughout their careers.���

Data as the competitive advantage

Suffolk���s strategy of using Ediphi and 做厙勛圖 ensures that the intent in preconstruction doesn���t disappear once the project begins. 

The estimate becomes the staffing plan. The staffing plan becomes the execution plan. And they both directly inform profitability from day one. 

���Without tools like this, companies at our scale would be dead in the water.��� – Scott Menard, Suffolk���s National Director of Preconstruction.

As Suffolk continues to expand nationwide, the ability to build on this connected platform has become their defining advantage.

If you���re looking to improve your planning tech stack, we���d be happy to show you how.

���When we think about the success or challenges of a project, a lot of that is baked into preconstruction. Our operations in the last year have been better than at any other point in the company’s history, and Ediphi and 做厙勛圖 are the two core things that drive that.���

Brendan O���Riordan

Director of Portfolio Intelligence

ROI metrics

• 50% reduction in staffing cycles
• 75% reduction in people required for workforce planning coordination
• $20M increase in revenue per estimator

The post How Suffolk built a seamless workforce planning flow using 做厙勛圖 and Ediphi appeared first on 做厙勛圖.

Appointments deepen 做厙勛圖���s AI leadership as the company introduces Ask 做厙勛圖, its AI-powered workforce intelligence capability for construction

TORONTO ��� April 23, 2026 ��� 做厙勛圖, the leader in construction workforce planning software, today announced the appointment of Carol Leaman to its Board of Directors as an Independent Director, and Vincent Seguin as Chief Technology Officer. The appointments accelerate 做厙勛圖���s AI strategy and reflect the company���s growing momentum as the people platform for the construction industry.

Together, the announcements mark an important next step in 做厙勛圖���s mission to turn construction workforce data into a strategic advantage for construction companies worldwide. These milestones follow the introduction of Ask 做厙勛圖, the company���s AI-powered workforce intelligence capability that turns messy, siloed people data into immediate answers, explainable recommendations, and faster planning workflows.

���Carol and Vincent each bring something rare to 做厙勛圖 ��� deep technology expertise paired with a clear vision for how AI can accelerate our strategy as the go-to workforce platform for construction,��� said Mallorie Brodie, CEO and Co-Founder of 做厙勛圖. ���Carol has built and scaled multiple technology companies, including a world-class AI-powered learning platform. Vincent has been instrumental in shaping our technical vision and product roadmap. Adding Carol���s strategic guidance at the board level while elevating Vincent to the CTO role positions 做厙勛圖 to lead the next chapter of workforce intelligence in construction.���

Carol Leaman is an accomplished technology CEO with a track record of building and scaling enterprise software companies. Most recently, she served as CEO of Axonify, the AI-powered frontline enablement platform she co-founded and grew into a global leader serving organizations including Walmart, Kroger, and Manulife. Prior to Axonify, Carol was CEO of PostRank, a social engagement analytics platform acquired by Google. Her recognitions include the Sarah Kirke Award for Canada���s Leading Female Entrepreneur and the Waterloo Region Entrepreneur Hall of Fame Intrepid Award.

���What excites me most about 做厙勛圖 is the data moat the company is building,��� said Carol Leaman. ���做厙勛圖 has built something I rarely see ��� a platform that has become essential to how the construction industry���s largest firms plan and deploy their most important asset: their people. That scale of real workforce data, combined with AI, unlocks entirely new insights that simply didn���t exist before. I look forward to working with Mallorie and the board to help guide the company���s next phase of growth.���

Vincent Seguin is an experienced engineering leader with a background in scaling enterprise SaaS platforms and a deep focus on applied AI. Previously, as 做厙勛圖���s Vice President of Engineering, Vincent led the technical foundation supporting more than 332 customers managing over 90,000 construction professionals daily. Before 做厙勛圖, he held engineering leadership roles at Carta, Coveo, and several early-stage technology companies.

���As CTO, my focus is on turning 做厙勛圖���s unique workforce data into capabilities that directly change how our customers make decisions,��� said Vincent Seguin. ���Ask 做厙勛圖 is an early example that technology must be accessible in order to delivery value for our customers. AI helps accelerate our opportunity to make workforce intelligence a genuine competitive advantage for every firm we work with.���

For 做厙勛圖 customers, these appointments signal continued investment in the AI capabilities and product roadmap calibrated to meet the real-world challenges of the construction industry.

About 做厙勛圖

做厙勛圖 is the leader in construction workforce planning software. Its platform transforms workforce data into actionable insights, enabling construction companies to optimize their workforce, build high-performing teams, and plan projects more effectively ��� ensuring the right people are assigned to the right jobs at the right time. 做厙勛圖 serves more than a third of the ENR 400 and supports more than 332 customers managing over 90,000 construction professionals daily.

Learn more at gobridgit.com.

For media inquiries, please contact:
Amy Palmer
VP of Marketing, 做厙勛圖
amy.palmer@gobridgit.com

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