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As transactions become larger, faster and more complex, due diligence teams are under increasing pressure to surface material issues earlier.
Technology has long played a role in meeting that challenge, helping teams manage scale, complexity and risk. Increasingly, the question is how technology can be applied thoughtfully to create more value for clients – not simply to automate existing processes.
For all the noise surrounding GenAI, one point is often overlooked: using technology in due diligence is not new. Deal teams have been applying automation, data extraction, clustering and other forms of AI for years to help manage scale, reduce noise and bring order to increasingly complex transactions – with the clear aim of delivering better, faster outcomes for clients.
What is new is the acceleration created by GenAI – opening up opportunities to rethink how diligence is delivered and how insight is surfaced earlier in the deal lifecycle. Across the market, the terms AI and GenAI are frequently used as if they are interchangeable. They are not. And failing to draw that distinction leads to poor deployment, misplaced expectations and, ultimately, more risk rather than less.
Understanding the difference – and knowing how to combine both intelligently – enables teams to move beyond process efficiency and towards deeper insight, sharper judgement and more confident decision‑making. This is where the value lies.
AI vs GenAI: Two different tools, one integrated approach
Traditional AI
Traditional AI is the technology that has quietly underpinned large-scale due diligence for years. It helps with:
- organising documents;
- detecting deviations;
- extracting key terms; and
- segmenting and prioritising so human reviewers spend their time where it counts.
It is stable, predictable and repeatable – attributes that matter enormously when advising on high-value, high-risk cross-border deals.
GenAI
GenAI, by contrast, brings a different kind of capability:
- narrative generation;
- accelerated reasoning;
- early-stage recommendations; and
- the ability to synthesise large volumes quickly.
But it is probabilistic, and its outputs need to be tested. It can accelerate judgment, but it cannot replace it.
The most effective diligence models recognise this: AI provides the structure; GenAI accelerates understanding; and lawyers anchor both with experience, context and commercial judgement.
What this means for deal teams today
The question we're all ultimately trying to answer is how AI-augmented diligence can meaningfully improve outcomes for clients. Four clear benefits have emerged from our recent experience across global transactions:
1. Faster paths to clarity
Both AI and GenAI enable quicker identification of the issues that matter, allowing teams to get ahead of risks earlier rather than reacting late in the process. This improves negotiation positioning and reduces surprises.
2. Better use of human time
The goal is not to eliminate human review – it's to make sure the time spent by lawyers is spent on judgement, context and strategy, not wading through repeat content or administrative volume.
3. Production-grade consistency
When AI is used well, you get reliable extraction and structured views of risk. When GenAI is used well, you get more complete early insight and enhanced narrative. Combined – and validated – they raise the quality of outputs.
4. More defensible processes
Diligence has always required traceability. AI does not remove that need – it increases it. A well-designed AI-augmented workflow improves auditability and helps teams demonstrate that decisions were anchored in a clear, consistent process.
AI allows us to move faster. Humans ensure we don't move fast in the wrong direction.
The human-in-the-loop: Still non-negotiable
Even in a GenAI era, professional oversight is essential. A human‑in‑the‑loop approach ensures that AI outputs are assessed with legal judgement, sector‑specific context and commercial insight. This safeguards quality and helps teams move quickly without increasing risk.
Translation variability, mixed document sets and domain-specific nuance can all challenge AI and GenAI models. Retaining legal judgement at the heart of the process ensures:
- accuracy is verified;
- context is incorporated; and
- outputs remain defensible in contentious or post-completion scenarios.
AI allows us to move faster. Humans ensure we don't move fast in the wrong direction.
Responsible deployment: Where risk is mitigated
Successfully integrating AI into diligence requires more than tools. It requires governance to ensure:
- clear workflows;
- data privacy management across jurisdictions;
- transparent reasoning;
- quality gates for GenAI outputs; and
- deliberate choices about when to apply each technology.
Getting this balance right is how firms can harness the benefits without falling into the trap of over-reliance on GenAI or under-valuing the proven stability of traditional AI.
So, what does AI-augmented due diligence deliver?
In short:
- earlier insight;
- workflows that move at deal speed;
- sharper visibility of risk;
- better allocation of lawyer time;
- more accurate, defensible outputs; and
- a model that scales with complexity, not against it.
This is not about jumping on a technology trend. It is about using the full spectrum of AI – traditional and generative – to deliver clarity, confidence and commercial value faster and more effectively for clients.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.
