The Only Problem with AI Adoption is the Lawyers

Australia sits at the forefront of a legal technology revolution. According to Clio’s 2025 Legal Trends Report, 98 per cent of Australian legal professionals now use AI in some capacity—making Australia one of the most AI-mature legal markets in the world, outpacing the United States, Canada, and the United Kingdom. Yet despite this widespread experimentation, many law firms struggle to translate AI curiosity into meaningful business transformation.

The technology works. The tools are available. The ROI is demonstrable. So what’s holding firms back?

The uncomfortable answer is increasingly clear: the only real problem with AI adoption is the lawyers themselves.

This isn’t a criticism—it’s a recognition that the barriers to AI transformation are overwhelmingly human, not technical. Understanding these barriers is the first step toward overcoming them and positioning your firm for sustainable growth in an AI-enhanced legal landscape.

Law Firms: Leading Adoption, Lagging Transformation

The statistics paint a compelling picture of AI adoption in Australian law. Clio’s research reveals that 66 per cent of firms using AI reported a direct positive impact on revenue. Growing firms are twice as likely to leverage automation compared to stable firms, and nearly three times more likely than shrinking firms.

Most Australian law firms have adopted AI within the past year alone, reflecting rapid acceleration as the profession embraces legal technology. Firms with wide AI adoption are nearly three times more likely to report revenue growth compared to firms that haven’t embraced these tools.

The 2025 ALPMA/Dye & Durham Changing Legal Landscape Report reinforces this trend. More than 90 per cent of law firm leaders reported experimenting with AI tools such as ChatGPT, Copilot, and CoCounsel. This represents usage rates of 70 per cent—significantly higher than the 44 per cent adoption rate across the broader Australian population.

Yet experimentation isn’t transformation. According to a Harvard Business Review survey of over 100 C-suite executives, 45 per cent found the ROI of AI adoption to be below expectations, while only 10 per cent reported results exceeding expectations. The most significant barriers? They’re organisational, not technical—rooted in people, processes, and politics.

For law firm principals and practice managers, this represents both a challenge and an opportunity. Your competitors are experimenting with AI. Some are succeeding. Many are failing to capture meaningful value. The firms that master the human side of AI adoption will define the next era of legal practice.

A Cautionary Tale: When AI Adoption Goes Wrong

Before exploring how to succeed with AI, it’s worth understanding what failure looks like. In August 2025, a Victorian lawyer became the first in Australia to face professional sanctions for using artificial intelligence in a court case—a watershed moment that sent shockwaves through the profession.

The solicitor, known only as “Mr Dayal,” was stripped of his ability to practise as a principal lawyer after submitting documents to the Federal Circuit and Family Court containing AI-generated citations that were entirely fabricated. He admitted he had not verified the contents before submission. The Victorian Legal Services Board varied his practising certificate, requiring him to work under supervision for two years.

This case was not isolated. Since then, more than 20 Australian court cases have involved lawyers or self-represented litigants submitting AI-generated material containing false references. The pattern is alarming in its consistency:

A Western Australian lawyer was referred to the Legal Practice Board and ordered to pay costs exceeding $8,000 after submitting documents citing four cases that either did not exist or were used inaccurately. The lawyer admitted he used Anthropic’s Claude AI as a “research tool” and then Microsoft’s Copilot to validate the information—a validation that clearly failed. He acknowledged having “an incorrect assumption that content generated by AI tools would be inherently reliable.”

In August 2025, a senior Victorian defence lawyer—a King’s Counsel named Rishi Nathwani—apologised to a Supreme Court judge after submitting documents containing fake legal citations and fabricated quotes from a parliamentary speech in a teenager’s murder trial. The error caused a 24-hour delay in proceedings. As Justice James Elliott observed, “The ability of the court to rely upon the accuracy of submissions made by counsel is fundamental to the due administration of justice.”

A Melbourne law firm, Massar Briggs Law, was ordered to pay costs after a junior solicitor submitted several fake and incorrect citations produced using AI. Federal Court Justice Bernard Murphy warned of a “growing problem regarding false citations in documents prepared using AI.”

These cautionary tales highlight a critical point: the problem isn’t AI itself—it’s how lawyers use it. Each case involved practitioners who failed to verify AI-generated outputs before submission. The technology didn’t fail; human judgment and professional discipline failed.

As Justice Murphy noted: “Many members of the legal profession use AI in some form, and they see it as a useful tool in the conduct of litigation.” The key word is “tool”—one that requires human oversight, verification, and professional judgment.

Why Lawyers Make Terrible Technology Adopters

The legal profession attracts careful, risk-averse individuals. These traits make excellent lawyers—methodical analysis, attention to detail, healthy scepticism of untested claims. Unfortunately, these same traits create formidable barriers to technology adoption.

Understanding why lawyers struggle with AI adoption is essential for developing strategies that actually work within your firm.

The Risk Aversion Paradox

Lawyers are trained to identify risks. It’s a professional imperative. When evaluating AI tools, this training creates a predictable pattern: every potential downside is meticulously catalogued while benefits remain abstract and theoretical.

Alex Shahrestani, a practising attorney and founding partner of Promise Legal, describes the situation bluntly: “Even the ‘bullish’ firms on AI are still hyper-cautious about it. There’s an obvious level of concern about AI in what is already a risk-averse industry.”

This caution isn’t irrational. The consequences of AI errors in legal work can be severe—from professional embarrassment to disciplinary action, as the cases above demonstrate. A Western Australian judge described the attraction of AI for lawyers as currently a “dangerous mirage.”

But risk aversion becomes counterproductive when it prevents firms from capturing competitive advantages. As Shahrestani notes, “Using AI right now is an exercise in maintaining relevance. Attorneys need to be prepared for the day that is certainly coming when AI can do our jobs.”

The paradox is clear: the risks of adopting AI must be weighed against the risks of not adopting it.

The Self-Image Problem

Fear of status loss can be even more powerful than fear of job loss. Research from Harvard Business Review identifies a phenomenon where professionals quietly use AI tools but conceal it to avoid appearing less skilled.

Many lawyers worry that admitting to using AI could make them seem lazy, incompetent, or even dishonest. Similar concerns lead radiologists to ignore AI recommendations to protect professional pride. The legal profession’s emphasis on individual expertise and personal judgment amplifies these anxieties.

One financial services firm addressed this by launching an “AI Masters” programme that fast-tracks employees who demonstrate exceptional AI skills, regardless of seniority. This approach celebrates AI proficiency as sophistication and forward-thinking rather than laziness or incompetence.

For law firms, the lesson is clear: how you position AI adoption matters as much as the tools you choose. AI should enhance professional identity, not threaten it.

The Uncertainty Problem

Slack’s 2024 global survey found that 61 per cent of employees had spent less than five hours learning about AI, and 30 per cent had received no training at all. In the absence of knowledge, opinions polarise. Some dismiss AI as mere hype, while others assume it can do everything.

This uncertainty extends beyond technical capability. One audit firm identified AI opportunities across its workflow, but both clients and auditors resisted, citing regulatory risk. The firm ultimately abandoned many of its AI-based approaches.

DBS Bank addressed similar uncertainty by introducing the PURE framework—Purposeful, Unsurprising, Respectful, and Explainable—to evaluate every AI use case. Instead of relying on lengthy policy documents, employees are guided by four simple questions that demystify AI while ensuring responsible use. By 2023, AI had generated $274 million in value for DBS.

For law firms, developing clear, practical governance frameworks reduces uncertainty while empowering responsible innovation. Your teams need to understand not just what AI can do, but when and how to use it appropriately.

Australia’s Regulatory Landscape: Light Touch, High Expectations

Understanding the regulatory context is essential for law firms navigating AI adoption. In December 2025, the Australian Government released its National AI Plan, which shapes the future of AI investment, policy, and business for years to come.

The key message for law firm leaders: Australia will not introduce a standalone AI Act. Instead, the government will rely on existing laws—including privacy, consumer protection, copyright, workplace law, sector-specific regulation, and online safety—while considering where uplifts are required to manage AI risk.

As MinterEllison’s AI Advisory team notes, this regulatory posture is “seemingly designed to accelerate investment and innovation.” The Plan confirms Australia will not mandate the Proposed Mandatory Guardrails for AI in high-risk settings that were previously floated. Instead, a new National AI Safety Institute will monitor AI harms, conduct testing and evaluation of advanced systems, and advise the government about when additional legal intervention may be necessary.

For law firms, this creates a nuanced environment. Heavy regulation is paused, but expectations for governance and organisational readiness are rising. While you won’t face prescriptive AI-specific compliance requirements, you will face higher expectations for transparency, testing, oversight, and workforce capability.

The National AI Centre’s updated “Guidance for AI Adoption” articulates the “AI6″—six essential governance practices for AI developers and deployers. These practices are becoming industry best practice, and leading firms are already uplifting their AI governance frameworks accordingly.

Courts have also signalled their expectations clearly. Practice notes from the Supreme Court of Victoria, NSW Supreme Court, Federal Court, and various tribunals now address AI use in litigation. The Victorian guidelines explicitly state: “It is not acceptable for artificial intelligence to be used unless the product of that use is independently and thoroughly verified.”

Law Council of Australia president Juliana Warner summarised the position: “Where these tools are utilised by lawyers, this must be done with extreme care… Banning it outright risks hindering innovation and limiting access to justice. But lawyers must keep front of mind their professional and ethical obligations to the court and to their clients.”

The Three Pillars of AI Adoption Failure

Research consistently identifies three interconnected areas where AI adoption falters: people, processes, and politics. Law firms that address all three pillars systematically will outperform those that treat AI as purely a technology investment.

People: Cultivating Readiness

Beyond risk aversion and self-image concerns, law firms face fundamental workforce challenges around AI adoption.

Fear of replacement creates passive resistance. When employees suspect they’re training systems that will replace them, they comply minimally. They drag their feet when asked to “label data” or “teach the model.” This “training trap” slows AI adoption across professional services.

Companies can counter this by sharing the upside—offering productivity bonuses tied to realised gains and career guarantees that channel efficiency gains into reskilling rather than layoffs. One e-commerce company pledged to increase total labour spending by 1 per cent annually to demonstrate commitment to investing in employees. This simple, verifiable commitment helped build trust.

Skill gaps present another challenge. Research from Thomson Reuters found that among legal professionals currently using AI tools, 77 per cent use it for document review, 74 per cent use it for legal research, 74 per cent use it to summarise documents, and 59 per cent use it to draft briefs or memos. But effective use requires understanding both capabilities and limitations—knowledge many lawyers lack.

Professor George Shinkle from UNSW Business School predicts that “professional education must shift from procedural knowledge to strategic competence much earlier in the pipeline.” This suggests law firms cannot rely solely on traditional legal training—they must invest in developing AI fluency alongside legal expertise.

Processes: Redesigning Workflows

AI adoption often falters when firms treat it as a simple overlay on existing processes. True transformation demands systematic change at multiple levels.

At the individual level, firms must transform how lawyers work. One consulting firm’s legal team initially used AI like a spell-check tool—running it at the very end of traditional reviews. This approach produced negligible benefits, as AI was only 100 per cent accurate for 40 per cent of error types. By restructuring the workflow so AI conducted the first pass—checking only error types it handled best—lawyers could focus on the remaining ones. This redesign unlocked AI’s value.

Some firms accelerated change by setting “mission impossible” goals that force teams to abandon old habits. One startup required that documents previously completed in a week be finished within a single day. The extreme time pressure left employees no choice but to integrate AI from the start and redesign processes around it.

At the departmental level, improved local judgments and data can transform cross-functional processes. At a Japanese cosmetics company, beauty advisors in stores once supplied untrusted, anecdotal feedback. Generative AI helped them analyse customer conversations and traffic patterns, giving structured insights. Headquarters, now confident in the data, built a two-way loop where campaigns could launch faster and be tweaked in real time based on credible field intelligence.

At the firm-wide level, organisations must consider how improvements across multiple nodes and edges interact within the broader system. Without this perspective, AI can simply shift bottlenecks from one part of the firm to another, limiting overall performance gains.

For law firms, this means considering how AI improvements in one practice area or function affect the entire client service delivery chain. Developing a coherent digital strategy that addresses firm-wide integration is essential.

Politics: Navigating Power and Influence

AI shapes who gains and who loses inside organisations. The resulting politics—over data, hierarchy, and accountability—often prove more formidable than technical issues.

Resource hoarding emerges when AI’s hunger for data collides with competitive instincts. At a large Chinese IT firm, researchers discovered that programmers were 16-18 per cent less likely to recommend AI access to their own teammates, effectively hoarding knowledge to preserve their personal edge.

Across business units, larger, more successful divisions that own sophisticated AI models and valuable datasets often see little incentive to share with smaller units that could benefit most. Sharing feels like enabling potential internal competitors while diluting their own performance metrics.

Hierarchy disruption occurs when AI unsettles traditional structures built on experience and headcount. The first pillar weakens when junior employees armed with AI outperform seasoned veterans. In one software firm, programmers with only two years’ experience began producing more and cleaner code than colleagues with five years’ tenure. Juniors felt they were doing more for less.

The second pillar—power through headcounts—creates even stronger resistance. Managers are gatekeepers of AI adoption, yet their authority often depends on team size. When efficiency threatens to shrink those teams, self-interest can quietly derail otherwise valuable AI initiatives.

OPPO, the smartphone maker, tackled this by staging an AI tournament where every employee had equal access to tools and results were ranked by department. Suddenly, managers had to champion AI adoption or risk public embarrassment if their teams lagged. The contest reframed success: status no longer came from managing large teams but from enabling them to achieve more with AI.

How Leading Australian Firms Are Getting AI Right

While cautionary tales dominate headlines, leading Australian firms are demonstrating what successful AI adoption looks like. Their approaches offer practical lessons for firms at any stage of the AI journey.

MinterEllison: Firmwide Commitment

In September 2025, MinterEllison took a decisive step by rolling out Legora across the entire organisation. This firmwide adoption signals a commitment to embedding AI not as a peripheral tool, but as a core driver of how legal work is delivered.

Virginia Briggs, CEO of MinterEllison, articulated the philosophy: “Our approach to AI is grounded in the belief that technology should amplify human judgement. We’re investing in tools that empower our people to unlock broader thinking, accelerate delivery and elevate the value we bring to clients. This is about enhancing expertise, not automating it.”

The firm’s approach reflects several key principles. First, embedding Legora into workflows allows teams to handle core tasks within a single system, supporting end-to-end processes such as due diligence and helping embed firm standards into daily work. Second, the adoption creates greater consistency while freeing time for more strategic matters. Third, the firm has developed its own tool, Cortex, which integrates with Legora to surface MinterEllison-specific expertise and intellectual property.

As Briggs explained: “When our people use Cortex and Legora together, we’re delivering a client experience built on our unique Australian-based IP that no other firm in Australia can match. This is what leading-edge AI looks like in practice.”

Ashurst: Global Rollout with Human Oversight

Ashurst became the first global law firm to roll out Harvey AI to all staff across all global offices simultaneously. Their controlled experiments measured time savings of 80 per cent for drafting UK corporate filings, 59 per cent for research reports, and 45 per cent for creating first-draft legal briefings. More than 95 per cent of Ashurst’s workforce has completed AI training.

Hilary Goodier, Partner and Global Head of Ashurst Advance, emphasises the importance of human-centred implementation: “Ensuring that our people are digitally fluent means they are comfortable not only using AI tools, but knowing where they can add value, and importantly, where they can’t. That’s critical, and it’s a core focus of our AI enablement programs and responsible deployment of AI at Ashurst. We call this the ‘human in the loop.'”

Ashurst’s Vox PopulAI report, based on trials involving over 400 people across 23 offices and 14 countries, emphasised a crucial lesson: “A human-centred, experience-led approach was essential for our people to be curious about using AI. Creating a culture of curiosity and learning helps break down the barriers to adoption.”

Client Collaboration: The Next Frontier

Leading firms are now extending AI capabilities to clients through collaborative platforms. Legora’s Portal, developed in cooperation with firms including MinterEllison, Allens, Linklaters, and Cleary Gottlieb, represents a fundamental shift in how legal services are delivered.

The platform allows law firms to deliver specialised knowledge to clients through custom AI workflows, legal playbooks, document sharing, and live online collaboration. This creates new ways for law firms to build client relationships and revenue streams while helping clients who are increasingly performing more legal work internally.

As Kyle Poe, VP of Legal Innovation at Legora, explains: “We’re creating an entirely new model where law firms can scale their expertise, deepen client relationships, and build durable competitive advantages. The firms that embrace this approach will be the ones leading the industry in five years.”

Platform Diversity and Strategic Selection

The University of Melbourne’s Centre for AI and Digital Ethics documented how major Australian firms are deploying diverse tools matched to specific use cases:

Allens launched “Airlie” using Microsoft Azure, followed by “Chronology Plus” for streamlining dispute chronologies. They’ve adopted Microsoft Copilot and share insights with clients exploring their own AI deployments.

Clayton Utz has deployed multiple tools including Lexis+AI for drafting advice, court filings, and client correspondence, alongside proprietary tools for environmental law analysis and obligations management.

Holding Redlich reported that legal research tasks taking four and a half hours using traditional methods could be replicated in 30 minutes using Lexis+AI.

The pattern is clear: successful firms evaluate multiple solutions, pilot extensively, and match tools to specific workflows rather than seeking universal solutions.

What’s Actually Blocking Your Firm’s AI Transformation

Understanding generic barriers is useful. But what specifically prevents Australian law firms from capturing AI value?

Confidentiality and Data Privacy Concerns

This represents perhaps the biggest sticking point for law firms. According to Embroker’s 2024 survey, 41 per cent of American lawyers reported concerns about data privacy related to AI adoption in practice—and Australian lawyers share similar concerns.

Legal authorities in New South Wales, Victoria, and Western Australia have explicitly warned that lawyers “cannot safely enter” confidential or commercially-sensitive information into generative AI tools. The guidance recommends limiting uses to “lower-risk and easier to verify tasks.”

While publicly available LLMs like ChatGPT perform reasonably on tasks like drafting and contract review, most lawyers don’t trust them with privileged client data. Larger firms have addressed this by developing in-house solutions and subscribing to enterprise-grade providers like Harvey and Legora. But many smaller firms are unwilling to take the risk on such investments.

Interestingly, this perception may not reflect reality. As Alex Shahrestani observes: “The huge irony here is that for the past 30 years, attorneys have been divulging the exact same information to all sorts of legal platform providers. On the back end, OpenAI is more or less the same as Westlaw in this respect.”

The key is implementing appropriate safeguards—and understanding that many existing legal technology platforms carry similar data exposure considerations that firms have long accepted.

Accuracy and Hallucination Risks

The cases of sanctioned Australian lawyers demonstrate that accuracy concerns are well-founded. AI tools can and do generate plausible-sounding but entirely fictitious legal citations. The Western Australian lawyer’s admission is telling: he had “an overconfidence in relying on AI tools and failed to adequately verify the generated results.”

Cayce Lynch, national managing partner at Tyson & Mendes, captures the balanced approach: “AI may give us the bare bones of a draft, but it is absolutely no substitute for our professional judgment and still requires substantial revision by a licensed attorney before it’s ready to go out the door.”

Understanding AI limitations is essential. As Shahrestani explains: “It’s not a search engine. It’s not going to retrieve information for you, it’s going to predict what the answer might look like.” More sophisticated prompting techniques—using specific questions and additional context materials—address hallucination risks.

This underscores why developing comprehensive content strategies requires understanding both AI capabilities and limitations. Human expertise remains essential for quality control.

Cost Perception Versus Reality

One of the more interesting early narratives around AI adoption was that it might break BigLaw’s stranglehold on certain practice areas. Emerging data suggests the opposite. According to a Federal Bar Association study, American firms with 51 or more attorneys use AI at roughly double the rate of smaller firms.

However, the perception that AI is prohibitively expensive may be exaggerated. Shahrestani notes: “Smaller firms are contemplating a monthly Westlaw subscription of $600 per user as their only option. But, if you hire a low code or no code expert to build out the system for you, it’s pretty much dirt cheap. You’re talking $10,000 all in for a robust system that does exactly what you want it to do.”

For many firms, the issue isn’t that they can’t afford AI—it’s that they don’t trust it enough to make the investment. Understanding how to measure marketing ROI applies equally to AI investments: you need clear metrics and realistic expectations.

Integration Challenges

Many AI tools fail adoption tests because they don’t integrate with existing workflows or demonstrate clear ROI. Firms that are less tech-oriented face a longer road to AI integration.

It’s also likely that firms haven’t considered the full range of functions they could potentially automate. Quality control and data privacy are huge concerns for mission-critical tasks like drafting, but they don’t factor nearly as much into decisions around administrative functions.

Take timekeeping. Lawyers at Tyson & Mendes use Traced, an AI-driven tool that automatically tracks what they’re working on and drafts detailed billing entries. “It’s really improved our accuracy,” says Lynch. “It’s also provided a mental health benefit, because our lawyers aren’t having to track every minute of their day. It’s given folks relief.”

The lesson: start with lower-risk applications where AI integration is easier and benefits are immediately visible. Success builds confidence for tackling higher-stakes implementations.

The Business Model Question: Will AI Kill the Billable Hour?

Clio CEO Jack Newton predicted earlier this year that “the billable hour model cannot survive” the AI generation. He described a “structural incompatibility” between AI-driven productivity gains and hourly billing—if AI lets a lawyer accomplish in one hour what used to take five, their time-based invoice would shrink by 80 per cent despite identical output.

In Thomson Reuters’ 2025 Generative AI in Professional Services Report, 40 per cent of law firm respondents believed AI will lead to increased non-hourly billing methods.

Yet research from Harvard Law School’s Center on the Legal Profession suggests the billable hour may prove more resilient than expected.

The Client Value Equation

Interviews with AmLaw100 firms reveal a dominant viewpoint: the total number of hours worked will remain similar or even expand, while attorneys spend more time on analysis and strategy. There’s an expectation that additional time now available will improve outside counsel’s “quality of service”—not just cheaper results.

This opinion was expressed by 90 per cent of firms interviewed. Crucially, their clients agreed with this expectation and are comfortable with current fee arrangements.

One interviewee summarised: “AI may cause the ’80/20 inversion’: 80 per cent of time was spent collecting information, and 20 per cent was strategic analysis and implications. We’re trying to flip those timeframes.”

Alternative Fee Arrangements

Professor Michael Legg from UNSW notes that while the billable hour is the traditional foundation for law firm revenue, the profession has always employed alternative approaches. “We’ve always had flat fees for things like conveyancing, wills or consumer-level legal services. I think we will see more flat fees or subscription fees as an option.”

The interesting development involves value-based billing. “The interesting question is whether lawyers can actually master that mindset, and then whether clients will want to pay in that way. If a lawyer comes up with tax advice that saves the client millions of dollars, does the lawyer get a percentage of those savings?”

Hilary Goodier says this transformation has already begun: “I believe the business model of law will finally undergo genuine disruption due to AI advancements. The billable hour may have finally met its match, and this may result in increased alternative fee arrangements as law firms share the efficiency benefits with clients.”

For Australian law firms, exploring different pricing models represents both a competitive opportunity and a strategic imperative.

A Practical Framework for AI Adoption

Based on the research and experience of leading firms, here’s a practical framework for Australian law firms seeking to capture AI value.

Step 1: Assess Your Current State

Before investing in AI tools, understand your starting point:

• What technology platforms does your firm currently use?
• Which workflows are most time-intensive and repetitive?
• What data do you have access to, and how is it currently managed?
• What are your team’s current attitudes toward technology?
• Where are your clients in their own AI adoption journeys?

This assessment should identify both quick wins (lower-risk applications where AI can demonstrate immediate value) and strategic priorities (higher-impact applications that may require more extensive change management).

Step 2: Address People First

Technology implementations fail when human factors are ignored. Before deploying AI tools:

Build AI literacy across the firm. Ensure everyone understands what AI can and cannot do. Address fears and misconceptions directly. Create safe spaces for experimentation.

Establish governance frameworks that are practical and memorable. Following DBS Bank’s PURE model, develop simple questions that guide appropriate AI use. Is the application purposeful? Will results surprise clients? Does it respect confidentiality? Can outputs be explained?

Align incentives with desired behaviours. Reward AI proficiency. Create pathways for advancement that incorporate technology fluency. Consider how compensation structures might need to evolve.

Preserve professional identity. Position AI as enhancing expertise rather than replacing it. The “human in the loop” concept should guide implementation—AI augments human judgment, it doesn’t substitute for it.

Step 3: Implement Verification Protocols

Given the Australian cases of AI-generated false citations, establishing robust verification processes is non-negotiable. Every firm should implement:

Mandatory verification requirements for all AI-generated content before submission to courts, clients, or counterparties. No exceptions.

Clear accountability structures that ensure senior lawyers review AI-assisted work product. The Melbourne law firm case highlighted failures in supervision—don’t let that happen in your firm.

Documentation protocols that track when and how AI tools are used, enabling quality assurance and continuous improvement.

Training on AI limitations that specifically addresses hallucination risks and the importance of independent verification. Every lawyer should understand that AI tools predict plausible outputs—they don’t guarantee accuracy.

Step 4: Redesign Processes

AI delivers maximum value when workflows are redesigned around its capabilities rather than bolting it onto existing processes.

Start with documentation and administrative functions where risks are lower and benefits are immediately visible. Timekeeping, document management, and research summaries offer excellent starting points.

Move to drafting and analysis with appropriate safeguards. AI-generated first drafts should always receive human review. Develop checklists and quality control protocols specific to AI-assisted work.

Consider client service implications. How will AI adoption change your client interactions? Faster responses? More thorough analysis? Different pricing models? Communicate changes proactively.

Think firm-wide. Improvements in one area shouldn’t create bottlenecks elsewhere. Map your entire service delivery chain and identify where AI improvements have downstream effects.

Step 5: Navigate Politics

AI adoption creates winners and losers within organisations. Managing this reality is essential.

Involve stakeholders early. Those affected by AI implementation should have voice in how it’s deployed. Resistance decreases when people feel heard.

Create incentives for collaboration. Reward teams that share data and insights. Make success metrics collective rather than purely individual.

Address hierarchy concerns directly. If AI enables junior staff to produce senior-quality work, how does this affect career progression? Compensation? Recognition? These questions deserve explicit answers.

Maintain human accountability. Even as AI takes on more tasks, humans must remain responsible for outcomes. Clear accountability structures prevent both blame-shifting and paralysis.

Step 6: Measure and Iterate

AI adoption should be measured against clear metrics:

• Time saved on specific tasks
• Quality improvements (error rates, client satisfaction)
• Revenue impact (new work enabled, pricing changes)
• Team engagement and adoption rates
• Client feedback and retention

Use these metrics to identify what’s working and what isn’t. Be willing to abandon approaches that don’t deliver value, as leading firms do regularly.

What Remains Uniquely Human

Despite AI’s expanding capabilities, certain aspects of legal practice remain distinctly human.

Hilary Goodier identifies the core advantages: “The elements of legal work that remain core to any firm’s success and are, at least for now, ‘uniquely human’, are the strength of their relationships and judgment. Relationships will perhaps become even more essential as technology permeates more and more of our personal and professional lives.”

Professor Michael Legg emphasises that legal expertise involves more than pattern recognition: “One of the points that is important in this debate is that the law is not necessarily just sitting there and able to just be picked up. One of the things that we spend a lot of time developing with students, which carries through into practice, is first defining the problem and then identifying and analysing relevant law.”

This analytical process requires sophisticated judgment. A lawyer might be advising a client, arguing in court, or structuring a transaction. They need to determine if a case decides the outcome—or if there’s a way for it to be distinguished. That’s the sort of legal knowledge that remains essential.

For law firms, this suggests a strategic priority: use AI to handle routine work, freeing human expertise for high-value activities that technology cannot replicate. Building distinctive brand positioning should emphasise these uniquely human capabilities.

The Competitive Imperative

The ALPMA/Dye & Durham report found that old value-adds such as offering access to senior staff, fixed fees, and personalisation of service will soon be considered baseline expectations. Technology, AI, and innovation-driven delivery are becoming the next real differentiators.

Meanwhile, cybersecurity and regulatory compliance reached its highest-ever level of importance in the 2025 survey at 63 per cent, showing the profession views cyber risk, data protection, and regulatory compliance as existential strategic issues.

These trends create a clear competitive imperative: firms that embrace AI responsibly will differentiate themselves. Firms that don’t will struggle to meet baseline client expectations.

As ALPMA CEO Emma Elliott notes: “Firms that are curious, open to change, embrace AI responsibly, invest in culture and talent, and balance flexibility with connection will not only attract the best people but also redefine what it means to deliver legal services.”

The Path Forward

The challenge is not adopting AI but evolving alongside it. The true advantage lies in building an organisation that can fully harness AI’s power. Firms that see it merely as a technical upgrade will inevitably fall short.

Professor George Shinkle summarises the strategic imperative: “Those that evolve their operating models around client outcomes, rather than internal process efficiency, will outperform in an increasingly competitive landscape.”

Jack Newton of Clio puts it more starkly: “Law firms are facing a once-in-a-generation opportunity to redefine how they work. Firms stuck in old habits will stall, while those betting on AI and client-first innovation will define the next era. The age of billable hours and hiring sprees is fading. The firms that thrive will be the ones building sustainable, technology-driven practices.”

The only problem with AI adoption is the lawyers. But that problem is solvable. With the right approach to people, processes, and politics—and with robust verification protocols to avoid the pitfalls that have ensnared colleagues—Australian law firms can capture the value that AI promises and position themselves for sustainable growth in an AI-enhanced legal landscape.