Artificial intelligence is increasingly helping companies manage post-execution contract obligations, identify compliance gaps and extract key contractual information, but human intervention will remain critical for final decisions and risk approvals, said Leena Tibrewal, CEO and Co-Founder, my-Contracts.
Speaking on the sidelines of the AI-Powered Legal Transformation Summit 2026, Tibrewal said one of the key challenges for corporates lies in managing contracts after execution, particularly obligation mapping, deviations and associated risk factors.
“AI has come in to help in a large segment, where without human intervention, the AI can pick up obligations — not only company-wide but also those of counterparties,” Tibrewal said.
According to her, AI can identify whether obligations are one-time or recurring, track milestones and flag open obligations to the relevant stakeholders. This can give management a clearer view of outstanding obligations and areas where compliance may be lacking.
Tibrewal said generative AI has now matured sufficiently for several legal use cases, including drafting, extracting key metadata, summarising contracts and conducting analytical or natural-language searches.
“CLMs are offering” these capabilities and adoption is increasing, she said, adding that the next phase is likely to involve agentic AI, although its application in legal workflows is still evolving.
Human oversight remains critical
While AI can provide suggestions and automate parts of legal workflows, Tibrewal stressed that accountability cannot be transferred to the technology.
“Although AI is something which will give you suggestions, final decision and the final risk approvals have to be taken up by a human mind,” she said.
She identified accountability, technology architecture and cybersecurity as areas that organisations need to remain particularly cautious about while deploying AI-enabled legal technology.
Tibrewal also highlighted the distinction between conventional automation and AI. According to her, rule-based systems are sometimes incorrectly characterised as AI, whereas AI systems, particularly generative AI, can work with inputs such as standard templates, playbooks, thresholds and fallback clauses.
Data security and compliance
Tibrewal said technology architecture plays an important role when deploying AI-enabled legal platforms, particularly in ensuring data security and limiting unintended data sharing.
She said my-Contracts focuses on aspects including encryption of data at rest and in transit, audits and compliance requirements. She also pointed to data protection requirements under India’s Digital Personal Data Protection framework when applications involve hosting and processing of data in different jurisdictions.
Customer feedback, she said, has also played an important role in developing legal technology products, as pain points can vary significantly across sectors such as insurance and manufacturing.
“Practical usage-wise, definitely, it gives you a lot of knowledge and understanding of what needs to be changed in the platform or what additional features need to be developed,” Tibrewal said.
‘Foundation has to be strong’
For the next generation of legal professionals, Tibrewal said adoption of AI should be accompanied by a strong understanding of the fundamentals of legal work.
One of her key takeaways from the discussion was the need to leverage AI while ensuring that the foundational skills remain strong, particularly for younger professionals.
“Human intervention is a must,” she said, describing AI as a tool that can support legal teams while human oversight acts as a guardrail.
“AI is good as a very quick and fast legal assistant, but it cannot definitely be a GC,” Tibrewal said.
