27.07.26

Construction Professionals – The Use of AI and Your Professional Indemnity Insurance

Artificial intelligence (AI) is rapidly becoming embedded across the construction and surveying sectors, and its growing use is raising important questions around professional indemnity insurance for construction professionals. From design optimisation to programme management, AI-driven tools are helping firms improve efficiency, manage costs and deliver projects more effectively.

However, as adoption accelerates, it is vital that construction professionals understand how the use of AI may affect their professional risk profile – and, crucially, their Professional Indemnity Insurance (PII).

While AI offers significant potential, it also introduces new and evolving exposures. Without appropriate controls, oversight and governance, AI can create liabilities just as readily as it can deliver innovation.

The growing role of AI in construction

Construction projects are complex by nature, involving multiple stakeholders, interdependent design decisions and tight regulatory frameworks. It is therefore unsurprising that the sector has been quick to utilise digital tools, including AI, to support decision-making and delivery.

AI is now being used at various stages of the project lifecycle, including:

• Design enhancement AI is increasingly integrated with Building Information Modelling (BIM), enabling the combination of multiple data sets to test and optimise layouts, massing, light penetration, sustainability metrics and spatial efficiency.
• Document automation Text-generation tools are being used to assist with bid preparation, planning submissions, reports, correspondence and fee proposals – reducing administrative burden and turnaround times.
• Programme and cost forecasting AI can analyse historic project data to identify potential scheduling risks, predict delays and flag likely cost overruns at an early stage.
• Procurement support Data-driven analysis is being used to anticipate material requirements, identify supply chain vulnerabilities and recommend procurement strategies.
• Health and safety applications Some tools are designed to detect design clashes, site hazards or unsafe equipment usage before issues escalate.
• Asset and facilities management Predictive maintenance models can schedule servicing and forecast equipment failure, helping reduce downtime and disruption.

These applications can deliver tangible benefits. However, their use also raises important questions around accountability, reliability and professional responsibility.

Understanding the risk landscape

AI systems are only as robust as the data, assumptions and training that underpin them. Despite advances in capability, AI tools remain susceptible to errors, context gaps and bias within data sets. In some cases, insufficient or flawed data can result in outputs that appear plausible but are fundamentally incorrect – sometimes referred to as “hallucinations”.

For construction professionals, this can create clear professional risk. For example:

• An AI-assisted design proposal may satisfy aesthetic or sustainability objectives but fail to properly address statutory requirements such as fire egress, accessibility or building regulations.
• A material specification generated with AI support may not account for incompatibility between products when used in combination, creating potential performance or safety issues.
• Automated text outputs may contain inaccuracies or omissions that go unnoticed if not adequately reviewed by qualified professionals.

Where AI-generated content or recommendations are relied upon without appropriate human checking and governance, errors may only come to light later in the construction process – when remediation is costly and disruptive.

From a professional indemnity perspective, the core issue is not the use of AI itself, but how it is used. Over‑reliance on automated outputs, inadequate oversight or failure to apply professional judgement could leave firms exposed to allegations of negligence, financial loss and reputational damage.

The implications for Professional Indemnity Insurance

Professional indemnity claims are often “long-tail” in nature, meaning claims may arise many years after the work was completed. Although AI‑related PII claims have not yet become prevalent, insurers and underwriters are increasingly alert to the potential future exposure as AI adoption becomes more widespread.

As a result, firms are likely to face more detailed questions during renewal and placement discussions, including:

• How AI tools are being used within the business
• Whether AI outputs are subject to human review and sign-off
• What governance, training and accountability measures are in place
• Whether the firm has a documented AI usage policy

In some cases, insurers may request sight of existing AI policies or seek assurances around internal controls.

Managing risk and demonstrating good practice

Firms using AI should consider developing a clear, documented policy governing its use. This should set out:

• Permitted applications of AI within the business
• Requirements for human oversight and professional judgement
• Accountability for decisions informed by AI outputs
• Data protection, confidentiality and intellectual property considerations

This policy should not sit in isolation but form part of a wider business framework that embeds governance, risk management and compliance at every level. Regular review is essential, particularly as AI capabilities, regulatory expectations and insurer attitudes continue to evolve.

It is also important to recognise that AI-related risk is not limited to professional negligence. Misuse may result in breaches of data protection and privacy obligations, sector-specific regulatory requirements or emerging legislation such as the EU AI Act.

In summary

AI has the potential to be a powerful enabler for construction and surveying professionals. However, its use brings new responsibilities and risks that must be carefully managed.

From a professional indemnity standpoint, firms should focus on transparency, governance and ongoing engagement with their insurance adviser to ensure that AI adoption does not inadvertently compromise cover or expose the business to uninsured risk.

Contact us today for more information and insurance solutions.

Information provided by Zywave with a contribution from Lisa Langley, Cert CII, Team Leader, Professional Risks, Cox Mahon Ltd.