What the Construction Giants are saying about Tech | Q1 2026 Earnings Report Review
We read all the earnings reports so you don't have to
Every quarter, the largest publicly traded construction and contech companies release quarterly reports and host conference calls providing insights into their business and an outlook on the future of construction.
At Last Week in ConTech, we review these through the lens of technology and innovation to understand where the industry is moving towards.
This edition we learned:
Why EPC firms like WSP and AECOM believe AI can increase net revenue and grow demand for civil engineers
Why Autodesk is trialing a flexible pricing model
Trimble’s strategy behind the Document Crunch acquisition and how they believe Claude will help them to expand their addressable market
Trade Contractors prefabrication strategy to alleviate labor shortage pressures
Let’s dive in.
WSP
EPC Firm, Market Cap: $16.87b USD
WSP has been actively deploying AI tools across their business noting:
this year we have rolled out AI tools to more than 30,000 of our 80,000 employees.
They gave an example of this rollout sharing a product they’ve built:
One concrete example is Nature Vista, our AI-empowered environmental management platform, co-developed with clients and enhanced through our Microsoft partnership. It can give asset owners a single live view of their biodiversity environmental obligation across the project lifecycle, from impact assessment through ongoing monitoring, reporting, and disclosure.
This product is an example of their AI strategy shared in their last earnings call where they noted:
Microsoft Partnership
They’ve partnered with Microsoft to enable one of the largest agentic and AI deployments to make sure their frontline knows how to responsibly use AI.Ecosystem Strategy
They’ve partnered with firms like UrbanLogiq, Fathom, Google and small startups.
The latter point is interesting as last earnings call they mentioned that AI firms are coming to them as they need domain expertise. This allows WSP to negotiate favorable terms around IP ownership and see their scale, project knowledge, geographic breadth and unique data access as moats.
One challenge with AI however is that many believe that this could drastically reduce the cost of delivering services. The reason why is that design firms use a billable hour model creating a perverse incentive not to reduce the time tasks take.
The CEO addressed this concern stating:
I don’t see our revenue stream shrinking… don’t see this being a disruptor in the sense that this will reduce hours or reduce the work that we need to do. There’s so much to do to optimize the design that we do today that any tools will be welcome.
He also noted that WSP and the engineering industry more broadly is facing a labor shortage.
this year…the company will be growing between 4%-7% organically. Globally in our industry and the world today, We are only able to grow the pool of engineers globally in the world by 1%. We are capacity constrained. What if AI would not be a great tool for us to increase our capacity and be in a position to produce more?
This is an interesting perspective.
AI has the potential to reduce the cost of services per output. For example the cost of delivering a design may be $10k and take 8 hours. With AI, this cost could fall to $7.5k with the time for delivery falling to 4 hours.
If demand remained fixed at one design, revenue would fall. However, the CEO argues that engineering is currently capacity constrained and having more work available than they have engineers to deliver it. In that scenario, the engineer uses the freed four hours to deliver a second project, increasing revenue from $10k to $15k.
This means that while revenue per project falls by 25%, revenue per engineer per day rises by 50% because productivity doubles. He is framing AI as a way of expanding effective labor supply rather than replacing or removing engineers.
The example above describes a market where firms already have excess demand. The longer-term question is different. If AI reduces engineering costs, will lower prices create even more demand?
If demand is price elastic, lower engineering costs could make previously uneconomic projects financially viable, stimulating a more than proportional increase in project volume. In that scenario, AI would expand the overall engineering market rather than simply reduce the cost of serving the existing one.
This has another unexpected implication.
AI could actually increase demand for engineering talent rather than reduce it. If lower costs expand the market, firms may need more engineers to deliver the additional work, provided demand grows faster than AI improves engineering productivity.
What I’m going to say will sound funny given the discussions that we’ve been having together over the last two quarters on AI, at the moment our growth is limited by the amount of people that we can hire. We have a very strong backlog, and if we could hire faster, we would be in a position to probably generate more growth.
Over the next 12 months, as AI systems improve and firms embed them into engineering workflows, the industry should gain a clearer picture of whether AI expands demand for engineering services or simply enables firms to deliver existing work more efficiently.
AECOM
EPC Firm, Market Cap: $8.67b USD
AECOM noted that their acquisition of Consigli, an AI startup, has been helping them signal to the market their expertise and seriousness in improving productivity.
The best measure of how AI is benefiting AECOM is our largest wins. We were recently selected for a substantial recompete for a major energy client, where our proprietary AI solution was a central element of the project proposal and our competitive edge.
They continue to highlight this edge:
What we are seeing is an improved revenue opportunity as a result of the…competitive advantage that we’ve created…Specifically, on Scottish Water that we did give you a lot of detail in Q1, recall, we virtually had practically no exposure to this client, and now we’re part of the largest…water contract, that has ever been let out by that client in Europe, U.K. geography for us.
They too highlighted that the industry is capacity constrained and AI is helping to alleviate that:
When you bring technology that drives efficiency, our clients are asking for more because the demand for our services far exceed sometimes the funding that has historically been in place.
Additionally they note that AI will allow them to enter new markets:
What this does is this allows us to actually have a way of entering some markets that we hadn’t previously participated in…An example of that would be healthcare…we’re effectively, again, building tools to support our professionals in their conversation with customers that reduce time, the uncertainty associated with complexity and cost. That allows us to more easily enter new markets.
They noted they spent “$13 million” on their AI roadmap.
Autodesk
Tech, Market Cap: $42.94b USD
Autodesk highlighted that they have started testing a new Flex Consumption pricing with a global contractor.
This is a pay as you go token based system where a company can prepay for tokens that are deducted daily whenever a user opens a product. It seems that AutoCAD costs 7 tokens per day while Revit costs 10 tokens per day with the minimum purchase requirement being 33 tokens for $99.
The value is this allows them to access a larger part of the market including smaller teams and freelancers for whom their solutions are cost prohibitive. This shift is grounded in a State of Small Business report they completed finding:
Nearly 1 in 5 Design and Make professionals (18%) are considering starting their own business in 2026.
Solopreneur and micro Design and Make firms grew nearly 10% in 2025 and almost 35% faster than the rest of the small business economy.
More than one third of the Design and Make workforce (36%) now operates as freelancers or contractors, outpacing the broader workforce (32%) and signaling a workforce more reliant on independent talent than the broader economy.
They also highlighted a change in their partnership approach:
We want fewer, more solution-focused channel partners out there, and we want, I mean, more, sorry, more, and we want fewer transactionally focused channel partners out there in our ecosystem.
To define each:
A transactional channel partner is one that primarily sells and implements a software product.
While a solution-focused channel partner primarily solves a customer’s business problem, using software as one part of a broader solution.
The value of this shift appears to be embedding Autodesk’s products more deeply into customers’ workflows. If a partner only sells the Revit license, the customer may only use a fraction of its capabilities whereas if the partner helps transform how they design, collaborate, and deliver projects, Autodesk becomes embedded in the customer’s workflows.
It’s valuable as customers adopting AI don’t just install new features, they need to redesign workflows, data management and rethink business processes. Solution-focused partners are better positioned to guide this transformation while demonstrating how Autodesk’s expanding AI capabilities can deliver measurable business outcomes.
This is reflected in pricing as Autodesk is seeking to capture AI market share by providing value first and then adjusting pricing downstream once it is captured.
at some point, we will be able to recover price like that, but it’s still early days. Let us deliver some of the value, and the customers recognize that, and then we’ll be able to kind of explore the deeper implications in terms of revenue uplift.
Trimble
Tech, Market Cap: $11.68b USD
Trimble highlighted that they rethinking their pricing model for an AI world:
While we monetize our software and AI today primarily through named user licenses, we are architecting ourselves to scale hybrid value delivery at the intersection of licenses and consumption…our recent native AI products deliver autonomous procurement and autonomous quotation on a consumption basis.
They also announced the acquisition of Document Crunch, noting it as an expansion play rather than an AI capability related acquisition.
The Document Crunch example is one where we acquired to create a new category.
This is to be a new AI-powered risk management category which bringing: “bringing contract intelligence and compliance automation into the project management, estimating, and ERP workflows”
They also noted:
Our M&A strategy remains focused on strengthening our core market positions and adding capabilities that allow us to run the cross-sell motions and provide high ROI for our customers.
Trimble also launched an integration between SketchUp, a 3D modeling and CAD tool and Claude.
This makes it easy for Claude users to create Trimble SketchUp 3D models directly from conversational text, image, or speech prompts enabled by a SketchUp AI-MCP service that allows Claude to create and modify SketchUp files.
This is to grow their market:
we see more opportunity to expand the addressable market for people who are not Trimble customers today….We believe we can capture customers and users who haven’t used the tool before.
…Our opportunity then from a downstream monetization play is to create new SketchUp users and then to upsell those SketchUp users, into inside…the Trimble Construction One offering.
They see a clear differentiation between what they provide and Claude, arguing that frontier models won’t be able to automate the design process:
Imagine going to Claude through natural language prompting…If you want a new patio for the backyard and it’s of a certain size…and style…Claude’s gonna deliver you a model.
We believe that that’s not enough. You need to do something with that model. If you just wanted a picture of the model, you could create that in Claude, but that’s not actually gonna translate…What you then do is if you’ve created that design of that model in Claude, you bring it into the SketchUp ecosystem in order to iterate on it.
The challenge is monetization:
Let’s separate maybe the professional user from the consumer user of SketchUp…I totally embrace SketchUp consumers…We really monetize at the professional grade level.
The question here is if the integration will increase their access to the professional market who likely already have an existing tool stack and familiarity with SketchUp as a design tool option. The integration may be an early edge if Professional users show a preference to prompt based design.
Another question is whether there is a clear pathway from consumer adoption to professional adoption. Consumers represent the majority of SketchUp’s user base and contribute to brand awareness and community content but it is unclear how effectively this translates into professional users and revenue growth.
Procore
Tech, Market Cap: $6.28b USD
Procore’s recent AI feature announcements reflect where they believe AI development and adoption will focus on:
Agents & Triggers
Customers are able to define automated event driven AI workflows allowing proactive test execution on projects.Voice AI
They are piloting a voice AI interface for field workers to have hands free access.
These features are being deployed via a “dedicated specialist team” that is working alongside their core sales force. As they understand the commercial motion, they will transfer the knowledge across the team.
EMCOR
Trade Contractor, Market cap: $33.56b
EMCOR highlighted their key labor force challenge:
our real bottleneck…is supervision. We have to create more foremen…We have to get project engineers to be able to move to project managers, project managers to be able to move to project executives. That’s how we really grow.
For startups and technology providers this is a clear opportunity. EMCOR has a clear desire to help workers and engineers to learn as quickly as possible to upskill in their careers. It’s as 40% of the construction workforce from before 2020 is expected to retire by 2031. Their knowledge needs to be captured and transferred if they want to be able to continue to deliver work.
EMCOR is also heavily investing in industrialization and modularization. They break down fabrication into multiple parts:
Traditional Prefabrication
This is completed on almost every job where support aftermarket such as adding fitting on sheet metal or completing pipe fabrication.Dedicated Prefabrication
This is split into two parts:Creating Kits
They essentially have a catalog where they take different parts from distributors and OEMs and put them together and ship to site (common on electrical jobs).Job Specific
Creating conduit racks and different bends that are required for each specific project (common for mechanical jobs).
Within this they have pipe rack shops that do sizes from small bore to large bore and sheet metal shops which transform sheets of metal into custom parts, structures or components.
Job Site Prefabrication
They also bring equipment into a tent on the job site and complete fabrication onsite.
If you’d like a firm included in these summaries, please reply and let me know!
Great writeup!