Artificial Intelligence in Construction Projects

AI and advanced digital technologies have moved beyond the experimental stage in construction projects. By the first quarter of 2026, it is evident that these tools are already affecting schedules, estimates, submittals, safety reporting, and daily project documentation. As we approach peak construction season, many teams are quickening their adoption of AI to improve efficiency.

However, the contractual framework governing the use of these tools—and the handling of their outputs when issues arise—often falls behind. This gap can quickly lead to disputes in complex construction environments.

AI Applications on Job Sites

Throughout the region, project teams are leveraging AI-enabled tools to:

• Model schedule scenarios and “what-if” sequences;
• Perform estimating takeoffs and analyze productivity;
• Draft or summarize RFIs, submittals, and meeting minutes;
• Generate safety documentation and incident reports.

While these tools significantly reduce administrative burdens, they also introduce new questions about who relies on the outputs, the adequacy of their review, and whether contracts recognize those outputs as authoritative.

Key Contractual Issues to Address

Before peak season commences, it is crucial for owners, contractors, and design teams to revisit several key contractual concerns:

1. Reliance and Standard of Care: AI-generated outputs should be viewed as supportive rather than conclusive. Contracts that inadvertently suggest reliance on automated outputs may lead to arguments over accuracy or completeness, a particularly risky position in disputes over delays or defects.
2. Data Ownership and Use Rights: Many AI tools utilize project data. Contracts must clearly define ownership of inputs and outputs, as well as whether vendors can use that data for training or other purposes. This issue is particularly critical on California projects involving public entities or proprietary designs.
3. Confidentiality and Privilege: Uploading RFIs, correspondence, or legal analyses into AI platforms can raise confidentiality issues. Teams should ensure that their use of AI platforms complies with confidentiality obligations and does not inadvertently waive protections.
4. Cybersecurity and Access Controls: Project owners are demanding stronger cybersecurity measures. Contracts should clearly outline access permissions, subcontractor use of tools, and notification requirements in case of data breaches.
5. Record Authenticity and Audit Trails: Disputes typically hinge on the reliability of project records. If AI assists in creating logs, reports, or summaries, clarity around human review, version control, and document retention is essential.
6. Flow-Down to Subcontractors: Inconsistencies in tool usage across tiers create risk. If AI is allowed or restricted at the prime contract level, subcontract agreements should reflect the same requirements.

Operational Controls for Peak Season

In addition to contract adjustments, leading project teams are instituting operational safeguards:

• Defining approved and prohibited AI use cases;
• Mandating human review for schedule, cost, and safety outputs;
• Providing training for project managers on the limits of AI’s role in professional judgment;
• Ensuring alignment between legal, IT, and project leadership to prevent disputes before they arise.

These safeguards help to ensure that efficiency improvements do not compromise defensibility.

As projects become increasingly complex—featuring aggressive timelines and sophisticated stakeholders—the motivation to leverage AI and digital tools grows. However, disputes often bring attention back to documentation, reliance, and contractual obligations. AI can serve as a powerful asset for projects, but it must be employed correctly and in accordance with the governing contracts. As the peak season approaches, it is critical to ensure technology enhances project delivery rather than leads to conflict.