More than a third of Australian legal professionals surveyed cite leaking confidential data as a top concern when using AI tools, yet only around a third of firms have created a policy for the internal use of AI . Read one way, that gap looks like a warning sign. Read the way I read it, after a decade working alongside legal technology teams, it looks like an opportunity. The firms that close that gap first will not simply be the safest. They will be the ones clients trust with their most sensitive work, and the ones best placed to use artificial intelligence with genuine confidence rather than hesitation.

Governance is what turns a risk into a capability

It is tempting to treat artificial intelligence and cyber security as two separate items on a risk register, one about innovation and one about defence. In practice, they are the same conversation. A firm that has not thought through how it uses generative tools, where client data goes, and who is accountable for the outcome, has not really adopted artificial intelligence. It has simply introduced a new, unmanaged variable into its existing systems. A firm that has done that thinking, by contrast, has built something durable. Governance is not the brake on adoption. It is the mechanism that makes adoption safe enough to scale.

This is why the regulatory environment now matters as much to a firm’s technology strategy as its choice of case management platform. Australia’s Cyber Security Act 2024 introduced mandatory ransomware and cyber extortion payment reporting, formal protections for information shared with the National Cyber Security Coordinator, and an independent review body for significant incidents. The Australian Cyber Security Strategy has since moved into its second horizon, with the Law Council of Australia and state law institutes actively examining what expanded compliance obligations will mean for firms of every size. None of this exists in isolation from artificial intelligence. The same governance muscles a firm builds to meet these obligations, clear data handling rules, defined accountability, tested incident response, are exactly the muscles that make artificial intelligence adoption sound rather than speculative.

The threat landscape is real, and so is the opportunity to lead

It would be dishonest to pretend the threat side of this equation has stood still. Social engineering that once required real skill can now be attempted by far less sophisticated actors, aided by tools that generate convincing voice and video content on demand. Legal practice is a natural target for this kind of attack, given the urgency and trust that underpin so much client communication, from settlement instructions to time-critical filings.

The right response to that reality is not caution for its own sake. It is precision. Firms that build verification into their processes, that treat unusual instructions as a prompt to confirm rather than a reason to rush, and that train their teams to recognise manipulated content, are not slowing down. They are protecting the very thing that makes legal practice valuable in the first place, which is the client’s confidence that their matter is being handled with care. Artificial intelligence, used well, strengthens that confidence rather than undermining it. Pattern recognition across large data sets, consistency checks on searches and filings, and faster identification of anomalies are all capabilities that support the same verification discipline the threat environment now demands.

What does good AI governance actually looks like?

A strong AI policy does not need to be long, but it does need to answer a small number of concrete questions clearly. Which tools are approved for use, and for which categories of client information. Who is accountable when an AI-assisted output feeds into client-facing work. How is client confidentiality preserved when data is processed by a third-party model. What is the process when something goes wrong. Firms that can answer these questions in a page or two are, in my experience, considerably better placed than firms with a much longer document that nobody has read.

This is also where the profession’s existing compliance instincts are an asset rather than a burden. Legal practitioners already understand risk frameworks, client due diligence, and reporting obligations in ways that most industries do not. Applying that same discipline to artificial intelligence is not a new skill. It is an extension of a skill the profession already has, directed at a new category of tool.

Building for the practice that is coming, not the one that has passed

The direction of travel is clear. Regulatory scrutiny is intensifying, client expectations around data handling are rising, and the tools available to both defenders and attackers are becoming more capable each year. None of that is a reason to slow down artificial intelligence adoption in legal practice. It is a reason to adopt it with the same rigour the profession already applies to everything else that matters.

At InfoTrack, we see this every day in the way practitioners approach searches, settlements, and due diligence. The firms getting the most value from intelligent tools are consistently the ones who took the time to understand how the technology fits their obligations, not just their efficiency targets. That is the mindset the next stage of legal practice will reward.

Explore how InfoTrack’s AI-driven intelligence supports secure, compliant workflows for Australian legal and property professionals.

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