Beyond the tools – where legal AI value actually lives

As legal AI capabilities rapidly expand, Babar Hayat of Konexo explains why real long‑term advantage now lies in proprietary data, institutional knowledge and integrated workflows, not in the tools alone.

There are, depending on who you ask, somewhere between 1,500 and 3,000 legal technology products on the market today that claim to use artificial intelligence. The number has roughly tripled in the last two years. For corporate legal teams trying to make sense of the landscape, the sheer volume of options has become a problem in itself. Not because choice is bad, but because the proliferation of tools has made it genuinely difficult to distinguish signal from noise.

Much of this growth has followed a familiar pattern. A new general-purpose AI model is released. Within weeks, dozens of companies wrap interfaces around it, add contract review or clause extraction and market the result as purpose-built legal AI. In fairness, many of these products work. They can summarise contracts, flag risk, draft correspondence and handle a range of tasks that would have seemed challenging three years ago. The issue is not quality. The issue is differentiation.

THE FLATTENING EFFECT

Legal tech is undergoing a flattening – as foundation models rapidly improve, the gap between standalone legal AI tools and well‑configured general models is narrowing – and that dynamic has only accelerated.

The broader technology ecosystem continues to expand its legal‑relevant AI capabilities. Major productivity platforms are now integrating AI directly into the tools that legal teams already depend on, and others in the market are moving in the same direction. None of these solutions are perfect yet, but the overall direction of travel is clear.

Each model iteration brings improved accuracy, stronger contextual understanding and more reliable handling of nuance. Tasks that required specialist legal AI products eighteen months ago, basic contract review, issue identification, first-pass redlining against playbooks, can increasingly be handled by well-configured general models at a fraction of the cost.

For vendors whose value proposition rests primarily on being a smart interface for a model, this raises a difficult strategic question: what happens when the floor rises to meet you?

The thousand-tool problem

When every vendor claims AI capability and the underlying technology is increasingly commoditised, what should corporate legal teams actually focus on? General counsel and legal operations leaders globally are being approached daily by vendors promising transformative efficiency gains. The fatigue is real but so is the risk of making expensive commitments to tools that may not hold their value as the market evolves.

The uncomfortable truth is that some tools are thin wrappers. They provide a legal-focused interface on top of models available to everyone. Others add genuine value through workflow design, proprietary data, integrations and domain-specific training. Distinguishing between the two requires a level of technical literacy that legal teams have not historically needed.

Where the real value sits

As baseline AI capability rises, value is concentrating in areas that are harder to replicate.

• The first is proprietary data and verification. General models are powerful but they do not own authoritative legal data. Those that have access to well-curated, jurisdiction-specific sources – case law, regulatory databases, legislative histories, local practice commentary are materially more valuable.
• The second is institutional knowledge and legal playbooks. While AI capability is becoming interchangeable, the data and logic you feed it is not. The organisations gaining the most from AI are those that have invested in managing their own data and knowledge like negotiation positions, risk appetite, approval frameworks and precedent libraries. This transforms a general tool into one that reflects the judgement of a specific legal team.
• The third is integration and orchestration. A brilliant standalone tool that sits outside the systems lawyers actually use every day will struggle to gain adoption. The practical value comes from how well AI fits into existing workflows – document management, matter tracking, billing and other organisational systems. This is where ecosystem players have a structural advantage. AI woven into an existing enterprise legal platforms, will generally outperform a point solution that requires lawyers to context-switch into yet another application.

WHAT CORPORATE LEGAL TEAMS SHOULD CONSIDER

For in-house teams evaluating their approach to legal AI, the starting point should be an assessment of where AI can reduce risk, improve speed or free up capacity for higher-value work. That means understanding your own workflows before you start shopping. Map where your team’s time actually goes. Identify the repetitive, high-volume tasks where AI can deliver measurable impact.

Be wary of long-term commitments to tools whose primary value proposition is model access. If the differentiator is the AI itself rather than what surrounds it, that value is likely to erode. Prioritise solutions that bring proprietary data, deep workflow integration or the ability to embed your own institutional knowledge into the system.

Invest in your own readiness. The teams that will extract the most value from AI are those that have organised their own data, documented their own processes and built the internal capability to evaluate and deploy technology. This includes having accessible contract repositories, playbooks and decision frameworks and people within the team who understand enough about the technology to ask the right questions. If your data is scattered across inboxes and shared drives with no consistent structure, meaningful ROI will be difficult to achieve

Finally, resist the pressure to adopt everything at once. The fear of falling behind is real but the organisations best positioned in 1-2 years will not be those that bought the most tools. They will be the ones that understood where the value sits, invested in their own data and expertise and made deliberate choices about where AI fits into how they work.

The legal AI market is moving from experimentation toward consolidation. The thousand-tool landscape will contract. Some vendors will be acquired, some will pivot and some will lose relevance as the platforms they are built upon on surpasses them.

The organisations that do best won’t necessarily be the ones with the most AI products, but the ones that understand their data, codify their expertise and integrate AI into their workflows in a way that actually sticks.

Text by:

Babar Hayat, head of technology and transformation, Konexo