Every enterprise runs on contracts. And contracts govern supplier relationships, define service expectations, and quietly shape the financial health of a program. Yet most organisations only look at contracts in isolation – a legal checkpoint before work begins or the only answer during a dispute - rather than as a predictable system of intelligence.
At Mastek, we’ve been asking a different question: what if contract review was not just about legal risk, but about building a real-time picture of business health?
Is there a single correct LLM?
Before diving into how AI in contract management is reshaping contract intelligence, we spent months exploring the landscape of AI tools. Each new iteration promised smarter answers and more nuanced understanding, yet no single approach offered a complete solution for the complexities of business operations around contracts. These trials deepened our appreciation for the strengths and limits of AI, and compelled us to ask a bigger question about contract intelligence.
The rise of Large Language Models (LLMs) has been exciting, but when applied directly to contracts, they show two recurring flaws:
- Inconsistency: Ask the same question multiple times, get different answers.
- Context-blindness: They don’t know your supplier history, operational rules, risk appetite (which is always evolving) or even the operational performance.
Therefore, a well-structured framework (explained in a later section) combined with human intelligence (Legal knowledge), ensures there are strict boundaries within which context is managed.
Instead of treating contracts as isolated legal documents, the real value comes from looking at them through a program profile lens – where vendor management, quality of service, and financial performance are all considered together. It becomes a way to understand how suppliers are performing, where risks may be building, and how obligations connect back to business goals.
It’s that connection between contracts, performance, and business oversight that gives meaning to the program profile lens - and that’s where our in-house tool doc.bot empowers better decisions in the background of AI contract analysis.
Consider this: When we understand the broader landscape, major surveys and studies show us these hard truths – how the financial impact of poor knowledge management is startling:
- Industry-wide, inefficient contract handling is estimated to cost businesses 9.2% of annual revenue, with higher losses - up to 15% - in larger organisations (WCC Study)
- In a survey by Harvard Business Review Analytic Services, nearly all respondents agreed that supplier management was critical, while only 21% reported having strong data-analysis capabilities for supplier management.
- From a broader corporate intelligence standpoint, inefficiency in managing knowledge - which includes contracts - can cost companies around 25% of their annual revenue, undermining productivity and decision-making.
There’s no doubt in believing that contracts are more than paperwork. And by managing contracts better, with the help of AI in contract management, we’re safeguarding strategic outcomes.
The Shift: From Clause Checking to Program Profiling
Traditional review asks: is this clause acceptable?
A program-level approach asks: what does this contract tell me about the health of my supplier ecosystem?
- Are renewal timelines stacking up in Q4, creating operational risk?
- Where is the highest risk exposure?
- Do our service agreements align with actual delivery metrics?
- Is the supplier delivering as per contractual asks?
Contracts are your business. And in business, there’s no time for reactive decision-making. Executives see a dashboard of contractual health, tied directly to supplier performance and financial exposure.
Imagine your contracts transformed into living documents.
Making Contract Review Consistent
The framework is simple but powerful:
1. Streamline review steps for clarity and efficiency.
2. Define precise risk aspects per clause, grounded in industry and client-specific needs.
3. Check one risk per pass, so results are repeatable and auditable.
4. Aggregate into a dashboard, where all stakeholders see the same picture, turning text into actionable insights.
The Business Case
Let’s put numbers to it.
- Let’s assume a single Legal resource spends 2-3 hours on a thorough review of a 20-page contract.
- For an enterprise reviewing even 1,500 supplier contracts annually, that effort quickly scales up.
- With the help of a legal AI tool, reviews would be faster, helping resources gain time back - and more importantly, time freed for strategic decision making.
But the harder-to-measure benefits are where the real value lies:
- Avoiding operational risk by spotting renewal bottlenecks early.
- Improving supplier negotiations with comparative analytics.
- Strengthening governance by making contractual health visible at program scale.
- Holding suppliers to non-financial performance/commitments.
Looking Ahead
Contracts are not meant to be just a legal exercise. That’s why we spend hours manually reviewing them and reading between the lines. Technology has made this exercise effective – acting as a business enabler. Our Legal AI tool is part of that vision: that transforms fragmented agreements into a living profile of supplier and program health.
The challenge ahead is less about technology and more about choosing the right questions to ask. With smarter insights and a proactive approach powered by AI in contract management, legal teams and business leaders alike can drive better outcomes and lasting value.
So, to spark your own thinking:
If you could track one leading indicator of supplier performance hidden in contracts, what would it be?
