Insights

Looking back, 2024 and 2025 were the years of pilots, proofs of concept, and deploying AI anywhere we could. They were also the years that brought us to this realisation.

AI can create massive impact. However, AI can’t create impact where the foundation isn’t ready.

So, if we had to name the biggest trend for legal transformation in 2026, it wouldn’t be a flashy new tool or an ‘AI-first’ operating model. It would be something far less glamorous, and far more effective: going back to the fundamentals.

That’s the shift we expect to see. Less chasing the next deployment, more building the conditions where transformation actually sticks.

Fundamentals in Practice

Here are the basics: simple, interconnected, and easy to implement.

1. Data strategy first, before the tool

A lot of teams try to deploy AI and automation into systems where data is scattered, inconsistently labelled, duplicated, outdated, or locked inside systems.

And hence, AI doesn’t work as it should. It performs like a sports car on a road full of potholes. It moves, but the ride is slow, unpredictable, and dangerous.

Putting in place an intentional data strategy means stepping back and looking at how information is stored, accessed, and maintained across contracts and clause data, case/matter management, advisory guidelines and playbooks, intake requests (and the context around them), and compliance logs, approvals, and decisions.

Once we have this view, the three maturity questions to ask are:

• What do we have? (and where is it sitting?)
• What’s reliable enough to use? (and what needs remediation?)
• How do we maintain integrity going forward? (so, it doesn’t become messy again in six months)

Because without trustworthy data, workflows underperform and AI outputs remain “interesting” rather than usable.

Here’s an example from a recent interaction.

• A company was implementing a CLM and later added an AI layer for clause extraction and risk flagging. The demo looked great, but the rollout failed.
• Their contracts weren’t standardised, old templates were floating around, metadata was missing, and executed versions weren’t consistently stored. The AI wasn’t “bad”. It was just operating in fog.
• In such a case, a short data remediation sprint (standard template mapping, metadata discipline, repository hygiene) often does more for outcomes than adding another feature.

2. Fix the workflow end-to-end, not in patches

The second pattern we’ve noticed is the temptation to improve workflows in silos:

• “Can we automate this one part of the intake form?”
• “Can you build a playbook?”
• “Can you improve the NDA process?”

When these happen as isolated interventions, you get pockets of improvement inside an overall system that still feels slow, unpredictable, and people dependent.

If there is one change legal and compliance teams can make in 2026, it is this: map their workflow end-to-end, from request to outcome, and identify improvements in the right sequence. Start with quick wins that reduce friction immediately. Move on to structural changes that prevent recurrence. And then build governance that keeps the system performing.

Think of it like renovating a house: you can buy beautiful furniture (point solutions), but if the plumbing and wiring are shaky (workflow design), the experience will be far from optimal.

A team I worked with spent weeks optimising NDAs, including templates, fallback clauses, and approval pathways. The business was happy until the next bottleneck popped up: intake is unclear, requests lack context, escalation rules are fuzzy, and turnaround time depends on who is online.

When the team finally mapped the full flow, they found the real culprit wasn’t the NDA template. It was the front door: inconsistent intake and no triage logic.

Once intake fields were redesigned around “decision-ready context” and triage rules were introduced, cycle time improved across multiple contract types, not just NDAs.

3. People and roles matter more than ever

The third principle is where 2026 gets especially interesting: AI changes the shape of legal work, which means roles need to evolve with it.

Yes, AI can draft faster, summarise, classify, and structure information well. But that doesn’t remove lawyers from the equation. It shifts what lawyers spend time on.

Two role shifts will become prominent:

1. Lawyers as reviewers and challengers of AI output

Review won’t just mean “read and approve.” It will mean knowing how to challenge the output on reference-ability (Where did this come from? Can I trace the sources?) and explainability (Why did the AI reach this conclusion? Does the reasoning hold up?).

Lawyers are already trained to do this. They challenge assumptions, interrogate logic, and test arguments all day.

Now they will be applying that same muscle to AI outputs.

2. Lawyers as business partners

If AI reduces time spent on first drafts and basic synthesis, legal’s leverage increases. That leverage should convert into higher-value work: business partnering earlier in decisions, judgement calls in grey areas, predictive risk spotting (not just reactive risk management), mapping patterns across matters/contracts to prevent repeat issues.

That shift won’t happen automatically. It takes intentional upskilling and role clarity, so lawyers don’t remain stuck doing the same work, just faster.

The practical takeaway for 2026 is transformation that sticks.

These fundamentals don’t operate in isolation; they form an interconnected system. Trustworthy data makes workflows usable and AI reliable. Strong workflows turn that data into consistent outcomes. Clear roles and skilled people make sure the system is adopted, governed, and improved, not just launched.

While these shifts will drive 2026, there are two more ecosystem shifts that will accelerate this year.

• Legal tech consolidation will continue. We’re already seeing point solutions being acquired by larger players. That means when evaluating niche tools, teams should consider survivability and long-term product roadmap, not just current capability.
• And as AI moves to core workflows, vetting vendor governance will become non-negotiable: how models are trained, how data is handled, auditability, security, and how outcomes can be explained and challenged.

If 2024–2025 were about experimenting with what AI can do, 2026 will be about building the conditions where AI actually delivers. Because transformation isn’t a fireworks show. It’s architecture. And in 2026, legal and compliance teams will go back to the blueprint.