AI can assist in organising and reviewing large volumes of documents, but it struggles with subjectivity. For instance, it might extract data from invoices and link them to a claim, but it cannot verify:

• Whether the invoice is relevant to the specific claim being analysed.

• If the invoice is accurate—for example, whether it matches the agreed scope, terms, or quantities.

Forensic Quantity Surveyors on the other hand, can critically assess documents, ask follow-up questions, and identify issues that AI might overlook. This ability to connect the dots makes human expertise indispensable.

Why can’t AI handle subjectivity in disputes?

AI is built to process data and detect patterns, but it doesn’t understand context. For example:

A Forensic Quantity Surveyor can reconcile invoices and remittance advice and recognise discrepancies, such as payments applied to the wrong project or claim.

AI might flag missing information, but it can’t decide whether that missing piece is critical or not.

This subjectivity—deciding what’s important and why—requires human judgment.

Can you give an example where AI has failed in a similar scenario?

Absolutely. Let’s look at a real-world example:

In 2020, an AI system was used in a financial auditing case to process invoices and flag errors. The system flagged numerous 'suspicious' invoices because they were missing expected metadata. However, AI completely missed actual fraudulent invoices that matched the expected format but were unrelated to the company's operations.

When real human auditors reviewed the flagged data, they realised the AI’s output wasn’t reliable because it is focused on superficial patterns, not the context or intent of the invoices. And AI couldn’t cross-check the invoices against the project scope or contract terms.

This is a perfect analogy for construction disputes. If an AI system were used to reconcile invoices or costs in a quantum claim, it might flag invoices based on surface-level anomalies, like formatting or incomplete data. But it will also miss critical issues, such as whether an invoice aligns with the claim or matches the scope of work.

In construction disputes, overlooking these details could lead to incorrect conclusions and that’s a risk no party can afford.

Why is human expertise essential in these scenarios?

Forensic Quantity Surveyors bring contextual judgment and critical thinking that AI cannot replicate.

A Forensic QS can verify the accuracy of the data and the documentation down to the smallest detail. They can cross-check against contracts, work logs, remittance advice, and even on-site realities.

Whilst this level of scrutiny is time-consuming, it’s what ensures disputes are resolved fairly and accurately.

Is AI faster and more efficient at certain tasks?

While it’s claimed AI is faster at repetitive tasks like sorting documents or extracting data, when it comes to tasks like reconciling invoices to claims, humans can analyse the context and relevance of each document better. Forensic QSs can spot anomalies or inconsistencies that AI might miss.

While AI might save time in the initial stages, human oversight ensures that nothing critical is overlooked, which can save significant time and cost in the long run.

What are the risks of over-relying on AI in construction disputes?

There are several risks.

You can miss the context - AI might analyse a document based on keywords but miss its relevance to the overall dispute.

There can be flawed outputs. If the input data is incomplete, inaccurate, or biased, the AI’s results will be unreliable.

There’s also False Confidence. Parties may trust AI-generated outputs without validating them, leading to flawed claims or defenses.

Ultimately, relying solely on AI increases the risk of errors, which could lead to incorrect conclusions and financial losses.

How should AI be used in construction disputes?

AI should be used as a tool to assist, not replace. For example, you can use AI for preliminary tasks, like organising large volumes of correspondence or identifying patterns in within the data.

But, you should pair AI insights with human expertise to ensure findings are accurate and relevant.

Always validate AI-generated results with a detailed review by experienced professionals.

AI is a powerful tool, but it has clear limitations. It cannot replace human expertise, especially in construction disputes where context, subjectivity, and judgment are critical.

Maybe use AI to save time on repetitive tasks, but rely on humans to verify accuracy and ensure fairness.

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