Q: Which technologies are truly transforming the legal profession today, and which are overhyped?

AI is the biggest force reshaping legal work, particularly in contract review, drafting, and playbook-driven workflows. Tools that integrate directly into where lawyers work, like Word, are driving real adoption. Automation that helps legal teams embed logic once and apply it repeatedly is also gaining traction. In contrast, blockchain still lacks a clear use case in mainstream practice. And many CLM platforms remain bloated and underutilized, with poor adoption outside legal.

Q: How would you describe the current stage of LegalTech development — experimental or mature?

The foundations are in place. E-signature, storage, and workflow tools are mature. But AI-assisted legal review and playbook automation are still evolving. We’re moving from proof-of-concept to practical deployment, especially as lawyers begin building systems that reflect their own thinking and risk positions.

Q: Which jurisdictions or regions do you see as leaders in LegalTech innovation, and why?

The US leads in terms of market size and VC-backed experimentation. The UK excels in contract standardization and public-private innovation. Innovation tends to flourish where legal teams are under pressure to scale or show value, and where infrastructure makes integration feasible.

Q: How do you see AI impacting contract work and legal operations over the next 3 to 5 years?

AI will handle much of the initial contract review, spotting issues and suggesting improvements based on predefined playbooks. Legal teams will move from line-by-line review to system-level thinking. More business stakeholders will be able to safely self-serve on contracts, with AI reducing the risk of missed issues.

Q: Which legal functions are most likely to be fully automated soon?

Any high-volume, rules-based tasks. Think NDA reviews, vendor intake forms, policy alignment checks. These functions are ideal for automation because they follow consistent logic and benefit from embedded playbook rules.

Q: What’s your take on the use of generative AI tools like ChatGPT in legal teams?

Used thoughtfully, they are powerful accelerators. But they must be grounded in legal context, trusted frameworks, and clear definitions. Generative tools should be guided by structured logic, not left to improvise. The best use cases involve combining human-designed playbooks with AI execution.

Q: What legal processes are most suitable for standardisation, and why is it critical?

Processes that are repetitive and structurally predictable. NDAs, DPAs, MSAs, and vendor agreements are all prime candidates. Standardisation reduces noise, cuts negotiation cycles, and opens the door to automation. Without it, every contract becomes a one-off, making scale impossible.

Q: How do you respond to critics who argue standardisation limits the "art" of legal practice?

Standardisation handles the repeatable core. The art lives in edge cases, judgment calls, and exceptions. Good lawyers still exercise creativity. They just spend less of it rewriting boilerplate and more of it advising on risk and strategy.

Q: Do you see automation improving access to justice? How?

Yes, when paired with simplicity and clarity. Automation can guide people through legal processes without needing a lawyer for every step. It also reduces the cost of delivering legal services, which matters most to those underserved by the current system.

Q: What are the main risks of widespread automation in legal services?

Blind trust in outputs. Hallucinations. Bias in training data. And poor implementation of guardrails. Without transparency, users won’t know when to question what they’re seeing. The risk is not the AI itself, but how it’s used and supervised.

Q: How can we build and maintain trust in AI-powered legal tools?

Clarity is key. Tools should explain what they’re doing, cite sources, and leave an audit trail. Human review must stay in the loop, especially on decisions with material legal impact. Trust grows when lawyers can see how the machine thinks.

Q: Common mistakes organizations make when adopting LegalTech?

Buying tools without a plan for adoption. Failing to involve users early. Thinking tech alone fixes broken processes. Good implementation requires mapping the workflow first, aligning roles and logic, then layering in the tool. Without this, even great software will fail.

Q: What makes a LegalTech product not just innovative, but truly useful and legally sound?

It fits into real workflows, reflects legal nuance, and produces outputs that lawyers can use straight away. A good product doesn’t just look smart, it reduces friction, speeds up decisions, and holds up under scrutiny.

Q: Which skills should young lawyers develop to thrive in a LegalTech-driven profession?

Prompt design, system thinking, and fluency in product tools. They need to know how to encode legal logic into reusable formats, and how to collaborate with product and data teams. The ability to abstract legal thinking into frameworks will define future success.

Q: What will the role of the lawyer look like in 2030?

More architect, less drafter. Lawyers will design legal systems, manage AI-driven execution, and oversee governance. They will spend more time creating scalable models and less time formatting clauses. Judgment, communication, and ethical leadership will matter more than ever.