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Employment Law · AI Governance

Someone Is About to Send You This Headline

The research behind the headline is sound. The conclusion being drawn from it is not.

Melt Strydom 22 July 2026 6 min read

If you work anywhere near employment law, human resources, or professional services in New Zealand, a headline is going to make the rounds in the next few weeks, either by landing in your inbox or popping up in your LinkedIn feed. It will tell you that most legal professionals now think the cost of checking AI outputs has overtaken the benefit of using AI at all.

It will be shared by someone who has been waiting three years to say I told you so. I have sympathy for the impulse. There is satisfaction in watching an over-promised technology come back down to earth, and if you have spent a career being told your judgement was about to be automated into obsolescence, you have earned a small moment of vindication.

The problem is that the headline does not describe the study it claims to report.

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What the research actually found

The underlying work is the Morae AI in Legal Report 2026, published on 8 July this year under the title The Intelligence Gap: Why AI in Legal Isn't Delivering and What Needs to Change. It surveyed 850 senior legal professionals across the United States, the United Kingdom, Australia, and the Middle East, split evenly between in-house legal departments and private practice. Fieldwork was carried out by Coleman Parkes in February and March 2026.

The numbers are not comfortable reading. Only 33 per cent of respondents said they trust the results of AI-assisted legal work. Some 48 per cent named poor accuracy and hallucinations as the most significant constraint on effective use. Half reported high concern about liability if AI-assisted work produces errors, and 62 per cent were extremely or very concerned about the reputational damage that would follow.

And yes, 67 per cent were concerned that the cost of human verification and oversight might outweigh the efficiency benefits.

That last sentence is where the trouble starts.

The first problem is a change of tense

Morae's own account says that 67 per cent are concerned that the cost of verification might outweigh the benefits. It is a worry about a possibility.

By the time it reached the trade press, that concern had become a finding that respondents believe “the burden of human verification outweighs the benefits AI was supposed to deliver” (Global Legal Post, 14 July 2026).

A concern has been converted into a conclusion. An anxiety about the future has been reported as a measurement of the present. This is not fabrication, and I doubt anyone did it deliberately. It is the ordinary compression that happens when a survey of 850 people is reduced to a headline of nine words. But the compression removed exactly the qualifier that was doing the work.

Nobody in that survey measured anything. They were asked how they feel about a cost they do not track, weighed against a benefit they do not track. That is still a legitimate and useful thing to ask senior people. It is not evidence that AI has stopped paying for itself.

The second problem is the omission

Here is the part that ought to be on the front of every summary of this report, and is on almost none of them.

Morae's own conclusion is that the problem is not the technology.

The media release carries it in the subheading: the challenges stem from flawed implementation, not from the tools. The report page says the fix lies in implementation, data, and governance rather than in better software. Morae's chairman and chief executive, Shahzad Bashir, puts it in seven words: “The root of the problem isn't the technology itself.”

The study that is about to be forwarded to you as proof that AI does not work is a study concluding that AI is being deployed badly by organisations that have not put their own house in order first. Those are not the same claim. They are close to opposite claims.

And the report's own data supports its authors, not its headline:

Read that list again without the words “AI” anywhere near it. Fragmented systems. No reliable file inventory. Policies on paper that nobody follows. Material that has never been correctly classified as privileged or confidential.

Those are records management failures. They were failures in 2015. They will be failures in 2035. What generative AI has done is switch on a light in a room nobody had looked at properly for twenty years, and the room's condition is now blamed on the light.

What the verification tax actually is

This is the whole argument. The survey asks whether verification costs more than AI saves. It does not ask what verification cost before.

And verification always cost something. Reading a junior's memorandum before it went out. Checking that the precedent pulled off the shared drive was not the 2019 version. Sitting with someone less experienced to explain, again, why the authority they had found did not say what they thought it said. Whether you did that work yourself or someone above you did it, the answer is the same. Quality control has never been free.

It simply never appeared anywhere. It was absorbed into supervision, training, hierarchy, and the general overhead of running a professional practice. It had no line item, so it had no visible cost, so it felt like nothing at all.

What 67 per cent of the respondents are describing is not a new expense. It is the first time in their careers that quality control has arrived with a price tag attached.

That is uncomfortable. It is not the same thing as being new.

And the same survey settles the point in the respondents' own voices: 89 per cent of them said AI-generated legal work should be checked by a human before it is used. Eighty-nine. The same people, in the same questionnaire, who said verification might cost more than it saves also said it cannot be skipped. The position of this profession is that verification is expensive and that verification is non-negotiable.

That is not a profession giving up on AI. That is a profession discovering that it has to build, deliberately and at cost, a supervisory function it used to get for nothing.

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Who was actually in this survey

The average respondent organisation had 3,832 employees, revenue of $1.5 billion, and $2.2 million invested in AI. The respondents were general counsel, heads of legal operations, managing partners, chief information officers, and chief information security officers.

These are enterprise legal functions. Their problem is that AI has been layered on top of a sprawling, siloed, decades-deep data estate that nobody has ever fully mapped. It is a genuine problem and an expensive one, and Morae — which sells information governance and managed legal services — is quite open about being in the business of fixing it. That is worth knowing, and it does not make the numbers wrong.

But it does mean the findings need translating before they cross the Tasman, let alone the Pacific. The survey covered four markets. New Zealand was not one of them.

What this means for a New Zealand employer

The average New Zealand employer does not have a $1.5 billion data estate. A 40-person Auckland business does not have twenty years of unclassified legacy files across six systems.

It has the opposite problem, and the opposite problem is not obviously better.

It has no data estate to fix, no legal operations function, no information governance policy, and — crucially — no supervisory hierarchy to hide verification inside. When a manager at a mid-sized New Zealand employer uses an AI tool to draft a warning letter, a restructuring proposal, or an investigation summary, there is no junior partner reviewing it, no precedent bank, no risk team. There is one person, one output, and a decision that affects somebody's job.

That is where our exposure actually sits, and it is why the enterprise framing of this report can be quietly misleading here.

Under s 103A of the Employment Relations Act 2000, the question is whether the employer's actions, and how the employer acted, were what a fair and reasonable employer could have done in all the circumstances at the time. Under s 4, good faith requires an employer proposing a decision that may adversely affect continuation of employment to give affected employees access to relevant information and a genuine opportunity to comment.

No New Zealand authority has yet held that an employer must produce a verification record for AI-assisted employment decisions, and I am not going to suggest otherwise. But both of those provisions are about what you can show, after the fact, about how a decision was reached. If part of that decision was drafted by a system you cannot account for, the difficulty is not that AI was used. The difficulty is that you cannot demonstrate what a fair and reasonable employer would have needed to demonstrate.

There is a related figure in the Morae research that translates almost directly into employment terms: 73 per cent of respondents said clients deserve full visibility into how AI is used on their matters, and only 21 per cent actually provide it. Replace “client” with “employee” and you have a fair description of where most New Zealand workplaces sit today.

Where this leaves the argument

So when the headline arrives, and it will, here is what I would say to whoever sent it.

Every number in that study is probably right. Take them all. The trust figure, the accuracy figure, the liability figure, all of it. They still do not support the conclusion being drawn, because the people who ran the survey drew the opposite conclusion from the same data, and said so in their own release.

Verification is not the tax you pay for using AI. It is the invoice for a function this profession has always relied on and never priced.

The organisations that will do well over the next five years are not the ones that avoided the technology, and they are not the ones that adopted it hardest. They are the ones that treated verification as a deliverable rather than a burden — because a documented, reviewable account of how a decision was reached is worth something to a client, to an employee, and to the Employment Relations Authority.

An unverified output is worth nothing to any of them, and it never was.

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Lex Praxis advises New Zealand employers on the employment law consequences of AI in the workplace, including verification, documentation, and decision accountability. This article is general commentary and does not constitute legal advice. For advice specific to your circumstances, contact us directly.

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