{"id":338597,"date":"2026-05-21T23:40:13","date_gmt":"2026-05-21T18:10:13","guid":{"rendered":"https:\/\/ebiztoday.news\/?p=338597"},"modified":"2026-05-21T23:40:13","modified_gmt":"2026-05-21T18:10:13","slug":"enterprise-ai-governance-critical-as-ai-scales","status":"publish","type":"post","link":"https:\/\/ebiztoday.news\/index.php\/2026\/05\/21\/enterprise-ai-governance-critical-as-ai-scales\/","title":{"rendered":"Enterprise AI governance critical as AI scales"},"content":{"rendered":"
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Enterprise AI governance is becoming increasingly necessary as organizations race toward ROI, demanding AI systems which can be scalable, predictable and built to deliver measurable business outcomes<\/a>.<\/p>\n<\/div>\n<\/div>\n

With research estimating that two-thirds of AI pilots stall before reaching production scale<\/a>, most organizations are clearly not only behind on AI \u2014 they\u2019re stuck on the starting line. Still, at the same time as different corporations take different approaches to AI, interoperability and governance have emerged as clear cornerstones, based on Murali Swaminathan<\/a> (pictured), chief technology officer of Freshworks Inc.<\/p>\n

\u201cThere\u2019s quite a lot of change that has happened within the AI world. There\u2019s a lot proliferation of AI-native tools [and] third-party products. Everybody is doing AI differently,\u201d Swaminathan said. \u201cThere\u2019s no one-size-fits-all \u2014 every little thing needs to attach together. We’d like to interoperate with other AI systems, and that\u2019s the training lesson here.\u201d<\/p>\n

Swaminathan spoke with theCUBE\u2019s Bob Laliberte<\/a> on the\u00a0Freshworks Refresh<\/a>\u00a0event, during an exclusive broadcast on theCUBE, SiliconANGLE Media\u2019s livestreaming studio. They discussed enterprise AI governance in addition to the shift from human-assisted workflows toward more autonomous AI-driven operations. (* Disclosure below.)<\/em><\/p>\n

The importance of enterprise AI governance<\/h3>\n

Together with interoperability, trust has emerged as a foundational requirement for any\u00a0successful AI adoption, especially as organizations begin delegating more work to automated systems<\/a>. To construct confidence in AI-driven outcomes, enterprises need visibility and assurance that the technology is working as intended, based on Swaminathan.<\/p>\n

\u201c[You need] trust in the way you arrange the AI, the way you arrange the controls, the way it performs, how you’ll be able to trace what\u2019s happening after which how we will report on what it did and what it didn’t do,\u201d Swaminathan said. \u201cTrust is there in lots of layers, and that\u2019s what we imagine in constructing the product or providing the tools so that you can set it up the proper way.\u201d<\/p>\n

Trust in AI requires layered governance, and Freshworks approaches that through controls built at every level of the stack \u2014 from LLM guardrails that outline what\u2019s permitted, to agent-level boundaries that keep automated systems focused on their intended tasks,\u00a0Swaminathan explained. Data anonymization and sovereignty policies add further guardrails, ensuring personal information is protected and that data stays inside designated regions. Organizations are increasingly focused on these sorts of safeguards to make sure AI systems operate securely in a way that feels invisible to the user and indispensable to the administrator.<\/p>\n

\u201cWe deal with data sovereignty \u2014 we make certain that the information stays within the zone and doesn\u2019t go outside,\u201c he said. \u201cSo far as the user is anxious, it doesn\u2019t matter to them, but behind the scenes, the people who find themselves governing it have to know that it\u2019s working the proper way.\u201d<\/p>\n

Here\u2019s the entire video interview, a part of SiliconANGLE\u2019s and theCUBE\u2019s coverage of the\u00a0Freshworks Refresh<\/a>\u00a0event:<\/p>\n