AI and emerging legal challenges in construction

Following on from last year’s horizon scanning, the construction industry has witnessed AI transition from experimental technology to operational reality.

Looking ahead to 2026, AI adoption is accelerating beyond early adopter firms to become standard practice, fundamentally reshaping project delivery through predictive analytics, autonomous machinery and generative design tools. However, as AI systems become more sophisticated and integrated into core construction processes, stakeholders must navigate an increasingly complex landscape of legal, contractual and regulatory considerations.

The regulatory landscape in 2026

The EU AI Act becomes generally applicable on 2 August 2026, with high-risk AI system obligations taking effect. Construction firms operating in or supplying the EU market must assess whether their AI tools fall within the high-risk category, particularly those used for safety-critical applications, worker monitoring or automated decision-making. The European Commission's guidelines on high-risk AI systems, expected by February 2026, will provide essential clarity on compliance.

In the UK, the anticipated AI Bill has been delayed until at least the second half of 2026. Meanwhile, the government is pursuing a principles-based approach through existing regulators using existing laws, and 2026 may see the implementation of AI Growth Lab sandboxes to test innovations in construction and advanced manufacturing in a controlled environment.

Liability frameworks and contract gaps

The fundamental challenge remains: when an AI system makes a decision or recommendation that contributes to a defect, delay or safety incident, determining liability between the contractor, AI system provider and other parties is complex.

Standard form contracts have not kept pace with AI adoption, creating uncertainty about how existing liability provisions apply to AI-generated outputs. Bespoke contractual provisions specifically addressing AI usage are increasingly required, covering disclosure requirements, human oversight and sign-off obligations, liability allocation and insurance. Where AI-driven scheduling tools provide inaccurate forecasts or BIM-integrated clash detection overlooks conflicts, contracts must clearly allocate responsibility.

Intellectual property and AI-generated outputs

Ownership questions intensify as AI tools generate designs, models and project documentation. The US Copyright Office's May 2025 report confirmed that works require human authorship, raising questions about protection for AI-generated content. Contracts must include detailed provisions addressing IP ownership in AI-generated materials, including rights to use outputs, ownership of training data, and restrictions on using project-specific AI models for other purposes. Construction firms should carefully review vendor licensing terms, as some AI tools retain rights to generated designs.

Safety, monitoring and data governance

AI-powered safety monitoring is expanding rapidly, with computer vision cameras detecting PPE violations, drones conducting structural assessments and predictive analytics identifying hazards before incidents occur.

These systems generate substantial personal data about workers, requiring careful compliance with GDPR and emerging AI-specific regulations around transparency and human oversight. When AI systems fail to detect hazards or misidentify risks, liability questions become acute. Traditional professional indemnity policies may not cover AI-related errors, and firms should review insurance coverage as a priority.

Bias, discrimination and data governance

As AI systems become deeply embedded in construction operations, concern grows about how bias and discrimination may emerge through the AI training process. AI systems trained on historical construction data may perpetuate existing biases, potentially leading to discrimination in subcontractor selection, workforce allocation or other decisions.

Construction firms must assess AI systems for potential bias and implement measures ensuring fair outcomes, including bias audits of training data, fairness constraints in algorithm design, and robust monitoring systems. AI-powered safety monitoring also generates substantial personal data about workers, requiring compliance with GDPR and emerging AI-specific transparency obligations.

Data centres: Growth meets sustainability

Due to the increasing adoption of AI, the exponential demand for data centres continues, but the focus in 2026 is shifting to sustainability and infrastructure challenges. Data centres now consume approximately 2-3% of global electricity, creating tension with decarbonisation objectives. Several local authorities have introduced specific planning policies requiring detailed energy assessments and evidence of renewable energy procurement.

Developers face increased scrutiny regarding grid connection capacity and water usage. These projects present both opportunities and significant contractual risks around delays and performance guarantees for energy efficiency metrics.

Practical steps for 2026

Construction firms should audit AI deployments against EU AI Act risk classifications, move beyond generic AI clauses to bespoke contractual provisions addressing specific systems deployed, review insurance coverage (noting that professional indemnity insurers increasingly require AI disclosure), and establish governance frameworks for AI tool selection and human oversight. Those who navigate this transition successfully will be well-positioned for the increasingly AI-enabled construction industry of the coming years.

Our construction team advises clients on the full spectrum of AI-related legal matters, from bespoke contract drafting and regulatory compliance to dispute resolution. Get in touch to discuss how we can support your organisation.