Mrunmayee Shende @MrunmayeeShende
Building the trust layer for AI in legal, finance and industrial. Co-founder, COO & CMO @NugenAI. Taking deeptech to regulated markets across APJ and EMEA. nugen.in Joined March 2023-
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The infrastructure inside it runs on Nvidia hardware. Sovereignty here describes where data stays and who governs the deployment. The hardware's origin is a separate question, one that gets less attention than the word implies.
Deutsche Telekom and Nvidia brought an Industrial AI Cloud online in Germany in early 2026, described as a sovereign, enterprise grade platform for domestic industry.
The failure will occur when this AI, which you have not spent on, is asked to make a decision leading to real world consequences.
The implication of the two statements above is clear. The numbers given are contradictory to each other. You cannot have low spending and high maturity at the same time.
A survey of 150 financial services firms found 61% say AI fell short of the ROI they expected.
Ninety percent is not a model that is occasionally wrong. If the number is right, the appeal process, not the model, was doing the actual work of getting the decision right.
A federal class action against UnitedHealth and naviHealth centers on nH Predict, an algorithm used to guide post acute care coverage decisions. Plaintiffs allege a 90 percent reversal rate on appealed denials.
This is what inspired us to build Nugen. Because once AI begins shaping decisions that impact individuals, reliability becomes the most important capability it can have.
The firm has more review capacity than most legal teams will ever have. The review step assumed citations were the least likely part of the filing to be wrong, an assumption that held for decades until AI took over the task.
In April 2026, Sullivan and Cromwell apologized to a federal bankruptcy judge over an emergency motion containing roughly 28 erroneous AI generated citations.
The number measures a rate of adoption more than a rare failure. It reflects how often a professional read the output and decided it was safe to file. That is the part the sanctions rarely capture.
A public database tracking court cases involving AI generated hallucinations, fabricated citations, invented quotes, has grown from roughly 200 cases in mid-2025 to 1,598 by June 2026.
The interesting part was not the failure rate. Most of those pilots were still called successful internally,because success had been defined as the model working in a demo, not as an outcome anyone could measure.
MIT's Project NANDA reviewed 300 public generative AI deployments this year. 95 percent produced no measurable effect on profit or loss.
It only moved for one category. Article 50 transparency obligations, the rules on disclosing AI generated content,still take effect August 2, 2026, exactly as scheduled.
EU negotiators agreed to push the AI Act's high risk obligations from August 2026 to December 2027. Most coverage read that as the deadline moving.
Defining the outcome before the technology means picking the metric that will still matter once the pilot ends, not the one easiest to produce on day one.
Hours saved was always the easiest number to produce. It was also the least connected to whether the work got better.
Time saved is about to stop being a metric that means anything in legal AI procurement.
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