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Managing AI Adoption Risk with Visibility and Control

netskope
06/09/2026
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what AI is going to do to the business. I think it's quite topical, hot topic, but I think they're also really keen to ensure that we're providing the foundational technologies and experience to allow our people to do our jobs. I think there's probably two or three key considerations with the adoption of AI internally. One is, I suppose, the initial bit is making sure that you're using the right models and so on. So shadow IT, if you like, restricting access to only tools that you're aware of so you can actually have visibility and control over that. The next bit is around accuracy, governance and output. A lot of people will not check results correctly. If someone comes to us and asks something or wants to do something that's out of the norm, we will look at how we can support that and kind of put the technologies and controls in place to do it. The beauty is the way we've architected our technology stack now through systems like NextSope and others like CrowdStrike, we do have a multifaceted approach and ability to support these requests in very many different ways now.

TL;DR

  • Leadership's top priority is understanding how AI will transform the business while ensuring foundational technologies support workforce needs.
  • Key AI governance considerations include restricting access to approved tools to prevent shadow IT and maintaining visibility and control over AI usage.
  • A flexible security architecture using platforms like Netskope and CrowdStrike enables the organization to support diverse AI use cases while maintaining governance and control.

Summary

This brief interview captures an IT leader discussing their organization's approach to AI adoption and governance. The speaker outlines three key priorities: ensuring AI tools align with business strategy, providing foundational technologies that enable workforce productivity, and managing the security and compliance risks inherent in AI usage. The discussion emphasizes the importance of visibility into AI tool usage to prevent shadow IT, the need for accuracy and governance controls around AI outputs, and the value of a flexible security architecture that can accommodate new use cases while maintaining control. The speaker highlights how their technology stack, including Netskope and CrowdStrike, enables a multifaceted approach to supporting AI adoption requests while maintaining security posture.

Chapters

0:00 - AI as Strategic Priority
0:27 - Shadow IT and Model Control
0:44 - Governance and Output Accuracy
0:56 - Flexible Security Architecture

Key Quotes

0:00 "The CEO or management partner would say that number one priority is looking ahead around what AI is going to do to the business."
0:33 "One is, I suppose, the initial bit is making sure that you're using the right models and so on. So shadow IT, if you like, restricting access to only tools that you're aware of so you can actually have visibility and control over that."
1:07 "The beauty is the way we've architected our technology stack now through systems like NextSope and others like CrowdStrike, we do have a multifaceted approach and ability to support these requests in very many different ways now."
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  • » Webinar Library » Netskope
  • » Cybersecurity » Cloud Security
  • » Data Protection
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  • AI & Machine Learning
  • Cloud Security
  • Security Operations
  • Best Practices
  • AI governance
  • shadow IT prevention
  • security architecture
  • AI model management
  • output validation
  • workforce enablement
  • technology stack integration
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