Procore Acquires Datagrid AI: What Agentic Intelligence Means for Construction Project Management

This deal signals a fundamental change in construction technology strategy. Project professionals should pay attention to both the opportunity and the risks.

Procore Technologies announced its acquisition of Datagrid AI in January 2026, and project professionals should take notice. This is not simply another construction technology consolidation. The deal signals a strategic shift from data collection toward autonomous decision-making, with significant implications for how projects get delivered.

The acquisition unites two of the most powerful AI solutions in the built world, according to Procore. Financial terms were not disclosed, but the strategic intent is clear: Procore is moving beyond embedded assistive AI features toward something closer to an agentic, cross-platform intelligence layer for construction.

What Datagrid Actually Does

Datagrid is not a chatbot dressed up for construction. Its core value lies in connecting fragmented data sources, including ERP systems, cloud storage, document repositories and project platforms, then applying AI reasoning to orchestrate actions across them.

In practical terms, this means automating multi-step processes such as submittal reviews, RFI drafting, document classification and cross-system search. The technology does not simply summarise text or answer questions. It executes tasks across platforms with minimal human intervention.

The company offers AI agents that can perform deep searches, RFI validation, scope checks, prequalification, audits, daily reports and other construction-specific tasks. This is not theoretical capability. These are operational tools already deployed with construction clients.

Thiago da Costa, Datagrid's CEO who joins Procore to lead AI and data strategy, captured the philosophy with clarity:

"Modern work has outgrown human capacity for manual processing. Our focus has always been on building an AI that can execute, not just talk. By joining Procore, we can now unlock unprecedented levels of productivity and quality for the thousands of customers who already build on its platform." — Thiago da Costa, CEO, Datagrid (Business Wire)

That distinction matters. Most AI tools in construction assist users with individual tasks. Datagrid's approach is fundamentally different: AI systems that can learn, remember and act independently within set boundaries.

Why This Matters for Project Delivery

Construction has long suffered from data fragmentation. Most firms operate a patchwork of ERP, accounting, document management and field tools alongside their primary project platform. Information exists in silos that rarely communicate, forcing project teams to spend hours on administrative tasks that add no value.

The scale of this problem extends beyond construction.

MuleSoft's 2025 Connectivity Benchmark Report found that organisations average 897 applications, but only 29% are integrated. Ninety percent of IT leaders say data silos are creating business challenges, and 80% cite data integration as one of the biggest obstacles to achieving AI goals.

Procore's Steve Davis, President of Product and Technology, frames the acquisition as enabling customers to bridge gaps between siloed data and initiate actions across their entire ecosystem:

"By integrating Datagrid's AI and deep search capabilities, we will enable customers to bridge the gaps between siloed data and initiate actions across their entire ecosystem. This connectivity unlocks the true value of construction data, allowing our customers to innovate faster and focus on building the world around us." — Steve Davis, President of Product and Technology, Procore (Business Wire)

The promise is significant. If realised, project managers could see AI systems that do not just surface insights but actually trigger workflows, move data between platforms and close procedural loops.

A submittal review that currently requires manual checking across multiple systems could happen automatically. RFI responses could be drafted by AI agents that access relevant documentation across platforms.

The Questions Project Professionals Must Ask

We approach this acquisition with cautious optimism. Platform consolidation often promises integration but delivers vendor lock in.

The construction industry has seen this pattern before, where acquisitions that promise interoperability eventually pull technology tightly into proprietary ecosystems.

Procore says Datagrid will continue serving both Procore and non Procore customers.

That decision will be closely watched. If Procore keeps Datagrid relatively open, it could position itself as an AI broker across the wider construction technology stack. If it eventually restricts the technology to its own platform, it risks reinforcing the data gravity that has limited interoperability elsewhere in the sector.

From a strategic perspective, there are not many credible, vendor-agnostic data connectivity and reasoning layers available in construction technology. This gives Procore a significant edge but also a responsibility to the industry.

Project professionals should also consider questions about responsibility.

If an AI agent makes a scheduling decision that leads to delays, who bears liability? How do these systems integrate with existing professional workflows and contractual obligations?

The technology sector's tendency to move fast and break things does not align with construction's risk frameworks.

The Bigger Picture

This acquisition sits within a broader trend toward agentic AI in enterprise software. Unlike the copilots currently offered by most AEC vendors, which assist users with individual tasks, agentic systems can learn, remember and act independently within set boundaries.

The construction software industry has been grappling with interoperability for years. As Construction Briefing recently reported, interoperability is absolutely essential in today's construction industry, but the focus is shifting.

It is no longer just about making tools connect; it is about unifying fragmented systems into a single environment where data moves freely and accurately. Industry clouds that serve as connected and secure platforms are helping eliminate data silos, reduce rework, and enable real-time decision-making.

For project delivery, this represents a fundamental change. The question is no longer whether AI will automate project administration but how quickly and with what governance.

Organisations that develop clear protocols for AI agent usage, data ownership and professional oversight will navigate this transition better than those that adopt tools reactively.

The combination of Procore's project management data with Datagrid's AI agents could genuinely transform project delivery. Or it could create an expensive, complex system that few teams fully utilise.

History suggests both outcomes are possible, often within the same organisation.

What To Do Now

Project professionals should demand clarity on how these AI systems make decisions, what data they use, and how their recommendations integrate with existing responsibilities. The time to establish those expectations is before implementation, not after.

Key questions for organisations evaluating this technology:

• How will AI agent decisions be audited and reviewed?

• What happens when an AI recommendation conflicts with professional judgement?

• Who owns the data that AI agents access and the outputs they produce?

• How do AI driven workflows integrate with contractual requirements and professional obligations?

These questions are not obstacles to adoption. They are prerequisites for responsible implementation.

Organisations that answer them thoughtfully will extract genuine value. Those that rush to implement will likely join the 56% seeing no returns.

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All content reflects our personal views and is not intended as professional advice or to represent any organisation.