Generative AI has transformed contract drafting. Something that once took a few hours can now take seconds. Documents arrive for review at a volume and pace that the unaided reviewer cannot match, assembled from firm precedent, AI-generated amendments, counterparty redlines of uncertain origin, and human edits.  A document reads cleanly, the definitions are tidy, the cross-references, on the surface, work.

While contract drafting has transformed, contract review is conducted largely as it was a decade ago: a lawyer, a screen, and the time to read. Undertaking contract review has always generally been framed by some sort of tension whether it be negotiation with a counterparty, a second set of eyes review, senior lawyers supervising junior lawyers, and the signposts of human intervention. With the advent of legal technologies, it has become increasingly difficult to identify and highlight any such tension. A lawyer now must take personal accountability for every clause in a document, despite having spent no time writing any of them.

The Issue

Under the new reality of unclear provenance of documents, particularly in a world where generative AI continues to creep into contract preparation, unaided review risks becoming an exercise which is no longer fit for purpose and runs the risk of being no longer able to carry the accountability owed to clients, regulators, the courts, and the profession itself.

We call the resulting gap, comprehension debt, which is the distance between the content of an existing document and how much the lawyer dealing with it understands. It shows up as an indemnity that does not map to the risk allocation everyone agreed on a call two weeks ago, or a defined term that gradually drifts in meaning across 200 pages.

One question this issue raises is what, in the age of generative AI in document production, is required for solicitors to meet their professional regulatory obligations when reviewing legal documents. 

‍
The Argument for Augmented Review

Solicitors professional obligations are established by the Solicitors Regulatory Authority Principles and in the Code of Conduct. These include, among others, the duties of competence, supervision, not to mislead and the ability to justify a judgment. In our opinion, these duties point toward a specific practical requirement in the context of contract review: technology built to challenge documents should be used alongside technology that generates them, particularly, when a document's provenance is unclear.

The Four Properties of Credible Assisted Review

However, not all "AI review" is equal, and the differences matter enormously for accountability. In Definely’s view, adequate contract review should be premised on four properties as set out below and we have matched the existing relevant SRA Principles and Code of Conduct provisions to support these properties.

1. Structural separation of generation and review, demonstrable on inspection. 

The technology checking a contract must be genuinely independent of the technology that helped draft it - independent in how it reasons - and a lawyer must be able to show that separation to a client, regulator, or risk committee. This is important because a generative system reviewing output produced by the same reasoning architecture tends to reproduce the very failure modes it's meant to catch. Its known tendency toward sycophancy inclines it to ratify text rather than test it.

^{Relevant SRA Principles/Code of Conduct: Principle 2: Uphold public trust and confidence in the profession, Principle 7: Act in the client's best interests, Code Para 3.5(b): Supervise others' work effectively.}

2. Per-output traceability. 

For each material finding, there should be a record of what was checked, against what reference, and where human judgment entered - detailed enough for the lawyer to reconstruct and stand behind the reasoning, not merely to point back at a prompt.

^{Relevant SRA Principles/Code of Conduct: Code Para 3.2: Provide competent and timely service to clients, Code Para 1.4: Do not mislead clients, the court, or others, Code Para 7.2: Be able to justify why decisions and actions complied with obligations.}

3. Reproducibility of findings. 

Running the same check on the same document should produce the same result, so that a flagged issue is a fact about the document, not an artefact of a particular run. General-purpose LLMs are probabilistic and may not reliably return identical results; deterministic approaches offer better certainty.

^{Relevant SRA Principles/Code of Conduct: Code Para 3.2: Provide competent and timely service to clients, Code Para 7.2: Be able to justify why decisions and actions complied with obligations.}

4. Structured and visible human oversight points. 

A credible tool identifies, rather than blends away, the points where the system has reached its limits and human judgment must take over, in a form the supervising lawyer can act on.

^{Relevant SRA Principles//Code of Conduct: Principle 7: Act in the client's best interests, Code Para 3.5(b): Supervise others' work effectively.}

Why the urgency?

Courts and regulators are already responding to failures of exactly this kind.

In R (Ayinde) v London Borough of Haringey [2025] EWHC 1383 (Admin), the Divisional Court articulated the duty of independent verification of AI-assisted material and expressly invited regulators to consider further measures. In Bandla v SRA [2025] EWHC 1167 (Admin), a solicitor who filed 25 non-existent AI-generated authorities was ordered to pay over £24,000 in costs. Courts have begun locating responsibility at the level of systems rather than individuals: in Ndaryiyumvire v Birmingham City University (November 2025), the court made a wasted costs order against the firm, not the named solicitor, treating the filing of fabricated authorities as, in substance, a failure of management and verification controls.

By July 2026, more than 1,700 judicial decisions identifying AI-generated errors in filings had been recorded internationally. Errors of this kind have passed both partner-level and secondary review at leading US firms, a sign that the problem is not confined to solo practitioners or under-resourced teams. 

Regulatory and professional bodies across jurisdictions are converging on the same themes, even where they have stopped short of issuing new rules. The Civil Justice Council's February 2026 consultation on AI in court documents proceeded from the premise that no new rules are needed for advocacy documents, provided a legal representative takes professional responsibility for them. Recent SRA compliance and supervision guidance — the latter expressly extending supervision expectations to AI use — restates existing standards rather than adding to them. The EU AI Act's transparency obligations took effect on 2 August 2026, with the fuller high-risk regime, including its Article 14 human oversight requirements, deferred to December 2027 under the Digital Omnibus, leaving professional judgment and firm-level discipline, not statute, as the binding constraint in the interim. ABA Formal Opinion 512, Bar Council and Law Society guidance, and the CCBE's October 2025 guide all converge on the same four themes: auditability, traceability, human oversight, and demonstrable independence. The Solicitors Regulatory Authority’s  authorisations of Garfield.Law (2025) and LawFairy (2026) — both hybrid or deterministic architectures with generative AI in a bounded role — show the regulator already treats architecture as a substantive regulatory question.

What the Industry Needs to Consider

‍
Taken together, the industry - firms, in-house teams, technology providers, and the bodies that set standards, should evaluate what tools are most effective to comply with existing regulatory frameworks in the context of contract review in a world of rapid changes and generative AI drafting of documents. The Definely premise is that this contract review should be assisted with tools which are structurally separate from the tools which generated the documents, allow traceability, produce consistent findings and are structured and identify where human judgement should be adopted.

None of this is an argument against generative AI in legal work. It is an argument that drafting and review need to remain separable - architecturally and procedurally, if the profession's existing accountability to clients, courts, and regulators is going to survive contact with how documents are produced now.

‍