Legal AI Adoption: Navigating Challenges with People-First, Risk-Aware Strategies

When legal professionals gather to discuss generative AI, the tone often sways between urgency and measured skepticism. The promise of large language models to drive transformation in legal services has brought both excitement and a host of pragmatic questions about safe, meaningful adoption. In a recent webinar hosted by Legal IT Insider in partnership with Stridon—a technology consultancy with deep roots in the UK legal sector—the conversation dug into the nitty-gritty of GenAI’s role in law firms, separating blue-sky ambition from the operational, ethical, and cultural hurdles that define real-world adoption.

Understanding the Legal AI Landscape: Why Adoption Remains a Challenge​

Within the legal domain, GenAI’s hype is juxtaposed against security concerns, regulatory intricacies, and deeply entrenched working patterns. Stridon’s CEO Matthew Stringer, speaking with Legal IT Insider’s editor Caroline Hill, articulated what many industry leaders wrestle with: the chasm between initial enthusiasm and widespread, safe engagement with AI.
Law firms, which operate with an elevated need for privacy and risk management, are naturally cautious adopters of any technology that could impact client confidentiality or introduce new vectors for liability. Adding complexity, generative AI tools like Microsoft Copilot or custom LLM (large language model) agents are evolving rapidly, often outpacing the ability of firms to assess, integrate, and adequately govern them.
Stringer’s summary is blunt: “People come first, then we bring the technology in.” This principle reflects a growing recognition that legal technology projects rarely flounder because of poor software; most stumble due to inattentiveness to cultural context, user need, and change management.

The Stridon Copilot Success Roadmap: Layered Foundations​

Stridon’s methodology, codified in its “Copilot success roadmap,” offers a rare look into practical steps for GenAI success. Used by clients such as Wedlake Bell, the roadmap is underpinned by strongly people-centric routines. The logic is simple but profound: only by fostering curiosity, skills, and buy-in among lawyers and support staff can a firm hope to unlock the strategic benefits of modern AI.
The roadmap unfolds in several phases:

• Assessment of Readiness: Firms must honestly gauge not only their technical infrastructure but also their workforce’s willingness and ability to engage with GenAI tools. Surveys, interviews, and pilot programs are invaluable for mapping out current knowledge and identifying blockers.
• Foundational Training and Literacy: Generative AI is unfamiliar territory—even technologically adept teams may need fresh guidance around concepts like prompt engineering, responsible usage, and data hygiene. Stridon’s approach is to demystify the technology for everyone, not just IT or innovation teams.
• Risk and Governance Strategy: Here, Stridon’s legal focus shines. Beyond the standard IT risks, GenAI in law introduces new nuances to confidentiality, privilege, and regulatory compliance. Policies must be tailored to reflect both the letter and spirit of prevailing legal and ethical norms.
• Co-created Use Cases: Instead of imposing tools, successful firms work with lawyers to co-design workflows where GenAI adds meaningful value—drafting, summarizing, due diligence, or client Q&A, for example—while ensuring that productivity gains do not degrade legal quality or accuracy.
• Iterative Feedback and Improvement: Embedding new tools is not a one-off; ongoing feedback cycles and agile adjustments are critical to move from pilot to mainstream adoption.

The “Agentic AI” Wave: Why Firms Must Prepare Now​

A pivotal theme emerging from the discussion is the shift toward “agentic AI.” Unlike passive assistants, these systems don’t just respond to requests but can take actions across digital environments—drafting emails, triggering case workflows, or surfacing suggestions autonomously. The leap from simple chatbots to agentic, decision-making tools raises the stakes, as the boundary between human and machine agency becomes blurred.
Stringer’s warning is clear: firms must have robust AI governance and user training “baked in” before rolling out more autonomous systems. Without strong foundations, agentic AI could compromise confidentiality, inadvertently breach ethics rules, or undermine firm reputation with a single unchecked action.

People-First Transformation: More Than a Slogan​

Stridon’s core principle—“put people first”—demands deeper analysis than a surface-level HR platitude. In practice, it means law firm leaders must:

• Engage users early, listening to their concerns about job security, change fatigue, and tool usability.
• Offer ongoing education, not just one-off training, evolving programs as the technology and its risks mature.
• Foster a culture of experimentation—rewarding those who surface creative uses and bug reports alike, instead of penalizing failure.
• Provide transparency about how AI is tested, governed, and monitored, building trust among employees and clients.

Notably, this approach isn’t only about soft skills. People-centric projects tend to result in more resilient, thoughtful policies regarding data usage, privacy, and compliance. Applied diligently, they guard against the kind of clumsy rollouts that have made headlines elsewhere in the industry.

Pitfalls of GenAI Adoption in Legal: Risks and Cautionary Tales​

1. Overpromising and Disillusionment​

Law firms often fall prey to inflated expectations, seduced by headlines suggesting AI will “revolutionize” the profession overnight. The reality is messier. Early pilots may spark intrigue but, without clear alignment to real legal tasks or measurable ROI, interest quickly wanes.

2. Security and Confidentiality Threats​

Even with leading tools like Microsoft Copilot, integrating cloud-based AI raises unavoidable questions about where data is processed, who can access it, and how results are audited. For highly regulated lawyers handling sensitive matters, a single data leak or unauthorized use can cause immense reputational and financial damage.

3. Hidden Bias and Ethical Traps​

Legal professionals are bound by strict codes of ethics, and the risk of GenAI amplifying hidden biases remains a live issue. Case summaries, contract reviews, or due diligence tasks completed with an LLM are only as robust as their training data and prompt rigor. Unseen bias or errors can lead to misguided legal advice or missed risks for clients.

4. Change Management Fatigue​

Seasoned IT leaders know “change fatigue” is real, particularly in conservative sectors like law. If GenAI adoption is layered atop a history of failed tech rollouts or unclear benefits, skepticism may calcify into outright resistance.

5. Regulatory and Professional Responsibility Gaps​

Regulators and bar associations are still sprinting to update rules. The result is that many firms operate in a regulatory grey zone, lacking definitive guidance on acceptable use, liability, or the handling of AI-generated documents. This ambiguity itself can breed conservative IT postures or slow-rolling adoption.

Strengths of Stridon’s Framework: Why “Slow and Steady” Wins in Law​

Despite the obstacles, Stridon’s roadmap for Copilot and broader GenAI initiatives gets several crucial things right:

• Prioritizing Measured Rollout: By advancing only as fast as users are ready, firms sidestep the risks of shadow IT and the unmanageable proliferation of unsanctioned AI usage.
• Centering Governance: The explicit focus on data governance and regulatory compliance means that when firms do scale up, they do so in a defensible, auditable manner.
• Enabling Business Value: Co-designing AI use cases with practicing lawyers ensures that technology spend is mapped to real business efficiency, not vanity metrics or clunky dashboards.
• Building Firmwide Trust: Transparency about data flows, monitoring, and oversight is integral, which, in turn, helps to win over doubters in both IT and legal ranks.

Microsoft Copilot in Legal: Case Study Insights​

Stridon’s Copilot-centric strategy is especially relevant as Microsoft doubles down on the legal sector, evolving its product to embed security controls and task-specific legal workflows. Pilots with clients like Wedlake Bell suggest that, when carefully scoped, Copilot can:

• Automate basic legal drafting, reducing time on repetitive template-driven tasks.
• Summarize large volumes of documents for early case assessment, saving hours of billable research.
• Power smarter search and retrieval, surfacing relevant precedents and statutes from sprawling file systems.

However, real-world feedback highlights some caveats: Copilot is only as valuable as its integration into existing case management and DMS (Document Management Systems). Without tailored configuration and customized prompt patterns, generic results frustrate users and prolong the journey to ROI.

The Coming Wave: Preparing for Next-Generation AI Agents​

Looking ahead, the pace of innovation shows no signs of cooling. Generative AI in law is moving toward systems that can proactively identify red flags in client communications, spot anomalies in contract terms, or even suggest remedial actions during live negotiations. These agentic tools, while promising, will expose firms to new frontiers of risk and reward:

• Positive disruption: Firms that successfully balance experimentation with strong governance can leapfrog competitors—offering more efficient, client-centered services and unlocking new business models.
• Potential pitfalls: Firms that rush without solid controls could see privilege breached, client trust eroded, or even face disciplinary action on ethical grounds.

The Bottom Line: GenAI Requires Human-Led, Policy-Backed Innovation​

For law firms in 2025 and beyond, the message from Stridon and Legal IT Insider’s session is unambiguous. GenAI’s potential will only be unlocked when the sector moves beyond “if” and “when” to ask “how”—deploying measured, policy-backed, user-centric rollouts. People, not algorithms, will remain at the center of legal practice. The most successful firms will be those who systematically:

• Invest in AI literacy for all staff;
• Iterate policies and workflows in step with technology’s evolution;
• Anchor every GenAI deployment in rigorous governance, with a clear audit trail;
• Encourage a culture that values innovation but never at the expense of client security, ethical integrity, or truth.

Transformation in legal isn’t about being the first to buy the latest AI. It’s about earning the right—through trust, skill-building, and governance infrastructure—to deploy it wisely, safely, and for the ultimate benefit of lawyer and client alike.
As agentic AI becomes a reality and as platforms like Microsoft Copilot become everyday companions in law offices, the lessons from Stridon’s people-first, methodical approach may prove to be not just wise, but mission-critical. The legal sector may not move at the breakneck speed of Silicon Valley, but when it moves with purpose, it rarely stumbles.

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Source: Insights and reporting re-confirmed via Legal IT Insider and direct references to Stridon’s public framework; claims checked against recent guidance from Microsoft and industry best practices for legal technology adoption. For up-to-date regulatory insights, readers are encouraged to consult their national law society or bar association guidelines concerning AI in legal practice to ensure compliance with evolving standards.

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Source: Legal IT Insider Webinar replay: GenAI adoption – The pitfalls and roadmap to success - Legal IT Insider