Construction builds everything. Hospitals, highways, data centres, energy infrastructure, office towers. It employs hundreds of millions of people across every country and generates somewhere north of $13 trillion in annual output globally. By almost any measure, it is the largest industry on earth.
It is also one of the least digitized.
That is not an observation. It is a documented, well-researched problem that has persisted for decades. McKinsey’s landmark analysis of construction productivity found that while industries like manufacturing and agriculture have seen productivity compound steadily over the past half- century, construction has remained essentially flat. 1 The culprit is not the work itself. It is the systems, or the absence of them, used to manage it.
Most large construction firms still coordinate complex, high-value projects through a combination of PDFs, Word documents, Excel spreadsheets, and email chains. Tender documents that run to thousands of pages are reviewed manually. Contract obligations are tracked in shared drives. Institutional knowledge lives in the heads of senior estimators who retire, leave, or move to competitors.
For investors watching the AI wave reshape industry after industry, the question worth asking is simple: what happens when AI finally arrives in construction at scale?
The Workflow That Matters Most
To understand where AI creates value in construction, it helps to understand where the money is made and lost.
Before a construction firm breaks ground on anything, it competes. It responds to requests for proposals, prices complex scopes of work, negotiates contract terms, and commits to obligations that will determine whether a project is profitable or not. This process, from RFP to signed contract, is where margins are set, risks are priced, and competitive advantage is established or surrendered.
It is also where the industry’s digital deficit is most costly.
A large construction company might pursue hundreds of bids annually. Each response requires teams of estimators, legal professionals, technical specialists, and commercial managers to coordinate across thousands of documents, often under compressed timelines. Requirements get missed. Pricing errors create exposure. Knowledge from past projects, what worked, what did not, what obligations caused problems, sits in archived folders that no one has time to search.
The companies that get this right win more work at better margins. The ones that do not absorb cost overruns, miss obligations, and leave revenue on the table that never gets recovered.
This is not a productivity problem at the user level. It is a revenue problem at the enterprise level.
Why Now
Sectors do not digitize because technology becomes available. They digitize when the cost of staying manual becomes unsustainable, and when the technology becomes reliable enough to trust with high-stakes decisions.
Both conditions are converging in construction.
Project complexity is rising. Contract volumes are expanding. Compliance requirements, environmental, regulatory, supply chain, are layering new obligations onto every tender. The global construction IT market is valued at $10.6 billion in 2026 and is growing, yet the core revenue-critical workflows around tendering and contract handoff remain largely manual. 2 At the same time, margins in large-scale construction remain thin. Even modest improvements in bid quality, win rates, or obligation tracking can have outsized effects on profitability.
The AI technology question has also shifted. General-purpose AI tools have demonstrated real capability but have exposed a critical limitation: they hallucinate. For a construction firm pricing a $300 million infrastructure contract, an AI system that invents clauses, misreads specifications, or generates confident-sounding but inaccurate responses is not a productivity tool. It is a liability. The market for construction AI is not waiting for AI to get smarter in general. It is waiting for AI that is trained on validated enterprise data, deployed inside secure environments, and reliable enough to trust with decisions that carry real financial consequences.
That infrastructure is beginning to exist.
What the Smart Money Has Already Decided
Institutional investors have not been waiting for construction to catch up. They have been positioning.
In 2023, Salesforce Ventures and Spark Capital co-led a $39.5 million funding round into an AI platform built for the tendering and proposal process, bringing total institutional investment in that category to $65.3 million. 3 The premise, as Salesforce Ventures stated at the time, was that AI applied to tendering is “a game-changer for enterprises that secure business via tendering.” That validation came from some of the most sophisticated technology investors in the world.
The company they backed is a horizontal platform. It serves government contractors, healthcare organisations, nonprofits, and grant writers across dozens of industries. It is private, venture- funded, and inaccessible to retail investors.
What it represents is market confirmation at the institutional level. The category is real, the demand is real, and the early players are attracting serious capital.
The question for Canadian investors is not whether AI-enabled construction workflow software is a viable business. That has already been answered. The question is where the public market entry point is.
The Listing That Changes the Picture
Aitenders is a construction-specific enterprise AI platform connecting the full tender-to-contract lifecycle, from RFP analysis through contract execution, using AI trained exclusively on each customer’s validated internal data, deployed behind the client firewall.
It is not a general-purpose writing tool adapted for construction. It is purpose-built for the workflows that determine whether a construction firm wins profitable work and delivers on what it promised.
The company reported $2.0 million in 2025 revenue, $1.6 million in ARR, and 81% gross margins, with 92% year-over-year growth. 4 Its enterprise customers include some of the largest construction companies in Europe. Customers report up to 13x ROI, decisions made three times faster, and RFP team productivity gains of 40%. Current penetration inside existing customer accounts sits at less than 1% of their global business units, meaning the expansion runway is already embedded in
contracts already signed.
Aitenders is completing a reverse takeover transaction with eXeBlock Technology Corporation and has reserved the ticker CSE: BIDS on the Canadian Securities Exchange, targeting a public listing in mid-2026. 5 At a pre-listing valuation of C$35 million, representing approximately 17.5x 2025 revenue, it is priced at a significant discount to Canadian AI technology peers trading at a median of 55.9x revenue as at February 12, 2026. 6
Construction is entering its AI transformation era. The institutions that fund technology companies already know it. The enterprise customers that sign multi-year contracts already know it. The listing that gives Canadian investors direct exposure to it is approaching.
This article is for informational purposes only and does not constitute investment advice, an offer to sell, or a solicitation to purchase securities. This content contains forward-looking information based on management assumptions and subject to known and unknown risks. Actual results may differ materially. The securities described have not been registered under the United States Securities Act of 1933 and may not be offered or sold in the United States. Please consult a licensed financial advisor before making any investment decision.
Source Notes
- McKinsey Global Institute — Reinventing Construction: A Route to Higher Productivity
mckinsey.com/capabilities/operations/our-insights/reinventing-construction-through-a-productivity-revolution
Tier 1 — Approved
Primary source for the construction productivity gap narrative. Used for the industry-level productivity stagnation
claim. Widely cited, high editorial credibility. ↩︎ - Fortune Business Insights — Construction Software Market Report
fortunebusinessinsights.com/construction-software-market-110155
Tier 1 — Approved
Primary source for the $10.6B (2026) Construction IT TAM figure. This is the specific report cited in the Aitenders
investor presentation v5, Slide 4. Always cite with this URL.
↩︎ - TechCrunch — AutogenAI Series A and Series B funding coverage
techcrunch.com/2023/07/26/autogenai-a-generative-ai-tool-for-writing-bids-and-pitches-secures-22-3m
Tier 2 — Approved
Used for market validation context only. Confirms $65.3M in institutional capital has entered the AI tendering category.
AutogenAI is not named in the article body. The Salesforce Ventures quote originated in the AutogenAI Series B press
release distributed via wire. FLAG: Geoffrey/Brennan to confirm comfort with this market validation framing before
publication. ↩︎ - Aitenders Investor Presentation v5
investors.aitenders.com/investor-presentation
Tier 1 — Approved
Primary source for all Aitenders financial and operating metrics: $2.0M 2025 revenue, $1.6M ARR, 81% gross margin,
92% YoY growth, customer outcome figures (13x ROI, 3x faster decisions, 40% productivity). All customer outcome
figures are customer-reported. Unaudited figures per management-prepared statements as of December 31, 2025. ↩︎ - eXeBlock Technology Corporation — Acquisition of Aitenders (News Release)
investors.aitenders.com/news/exeblock-technology-corporation-announcesacquisition-of-aitenders
Tier 1 — Approved
Primary source for RTO structure, CSE: BIDS ticker reservation, and listing timeline reference. Distributed via Newsfile
Corp (Tier 1 wire service). ↩︎ - Yahoo Finance — Canadian AI Technology Peer Valuation Data
finance.yahoo.com
Tier 1 — Approved
Source for the 55.9x median revenue multiple and 17.5x Aitenders pre-listing multiple. Data as at February 12, 2026 per
investor deck Slide 15. FLAG: Geoffrey/Brennan to confirm whether updated peer data is needed or whether the
February 12, 2026 date reference is acceptable for publication. ↩︎
