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Walter Haydock

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Amazon and Samsung didn't assess their AI-related risk properly, and got burned. The weakest link? Lack of processes and guardrails. - "There's no governance in place, not even an AI policy." - "We're moving at Mach 7" when it comes to AI products. - "We're rolling out dozens, if not hundreds, of AI-powered tools." Sound familiar? These are all things security leaders have said to me. What they - and you - desperately need is a comprehensive and structured approach to managing the resulting risk. While revolutionary - and critical to any business that wants to survive - artificial intelligence can create cybersecurity, compliance, and privacy headaches. You need the right tools to navigate these competing demands. Dealing with internal and external stakeholders can be even more demanding, requiring not just an understanding of the issues but the ability to communicate them effectively and quickly. Here's what your plan should look like: 1. Identify the business needs. Successfully automating your operations with AI will probably be the difference between your company's success and failure, so you'll need to look throughout your organization to understand where to deploy these tools, and in what priority. 2. Analyze the security, privacy, and compliance risks. How is your SaaS vendor managing your data? Are you subject to the GDPR, CCPA, or any other data privacy obligations (hint: you probably are)? What frameworks (SOC 2, ISO 27001, FedRAMP) do you need to comply with? You'll need to know these things before heading to the next step. 3. Apply controls. This includes making sure you have a company-wide policy, creating a structured framework for risk decisions, and deploying the right technical safeguards to your AI systems. You'll need to train up your team on all of these things as well. So, if you're a CXO or VP in tech, healthcare, and financial services who wants to launch AI-enabled products without fear, it’s time to look at your AI-related risk NOW. Need an assessment? DM me.

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