Paul Deraval, Cofounder & CEO of NinjaCat, is a software veteran with 20+ years driving innovation in martech, AI and agency growth.getty​Data privacy is a pressing concern for today's digital consumers. According to one analysis, 92% of Americans are “concerned” about their personal information being collected by apps and websites. These worries may be genuine, but, in practice, many of us are much more blasé. We rarely read the terms of service, click past cookie consent banners and willingly trade free experiences in exchange for our valuable personal information.​The artificial intelligence era demands that we rethink this complacency. It’s more than just an individual responsibility. Companies of every size in every sector leveraging this technology must take accountability for the sake of their proprietary intelligence and their customers' trust. Here’s how. 1. Don’t Let Semantics Undersell The Importance Of Your Data “Data” is a big word with little meaning. Businesses strive to be “data-driven”; consumers are reduced to data points; and we’ve all heard about countless, expansive data breaches for years. In every context, data is an abstract, dehumanized commodity. It’s technical, inanimate and corporate, saying a lot without communicating anything in particular. Reframing data as "memories" makes the issue inherently personal and visceral, raising the stakes and accurately reflecting how AI-powered tools collect, store and repurpose this information. ​Conversation by conversation, AI chatbots are building a working model of you that is more than just your search history or demographic profile. According to APA’s 2026 Chatbots and Mental Health Survey, one-third of psychologists say patients are turning to AI as an additional mental health professional. A separate survey found that nearly half of AI users who self-report mental health conditions use the tools for mental health support, including 73% who use it for anxiety management, 63% for personal advice and 60% for depression support. ​Additionally, more than half of respondents in TD Bank’s "2026 U.S. AI Insights Report" are using AI to “aid their financial management decisions,” and KFF reports that approximately one-third of U.S. adults say they’ve used AI chatbots in the past year for health information. ​Business professionals aren’t doing much better. And with 43% of business professionals saying they’ve shared sensitive information, proper AI stewardship just isn’t happening. When you realize that financial and client data is sometimes being shared with AI chatbots, it highlights a growing problem.​Call them data or call them memories, these points all add up to a complete picture of ourselves and our customers. Leaders have to prioritize finding a safe and governed way for the enterprise team to use AI while protecting the data that is so crucial to the customers and the business.2. Count The Cost We want what personalized AI can provide, and many of us are willing to trade personal privacy for access and utility. Many companies are, too. In a rush to gain an efficiency edge, organizations are actively pumping their proprietary intelligence into raw, open AI environments or duplicating it across a Frankenstack of disconnected data warehouses.​For enterprises, agencies managing sensitive client data and organizations working with first-party data that carries real legal and financial weight, the ownership question has consequences that cannot be overstated. Data breaches aren’t just embarrassing. They can be company-destroying, as repair costs, reputational damage and regulatory fines compound to create an insurmountable burden.​The moment your data leaves your control, risk compounds. Every duplicate dataset increases costs, expands vulnerabilities and weakens governance. The companies that win won't be the ones with the most data. They'll be the ones that can create value from their data without surrendering control of it.3. Separate Intelligence From Ownership AI can give us genuinely better answers because it has accumulated a detailed picture of our customers and us. That picture is stored somewhere, and someone controls it. It’s probably not you or your company. Many believe they must relinquish ownership or sacrifice AI's utility. In other words, either keep your data secure or get the benefits of a highly personalized AI.​This is a false dichotomy, and AI vendors shouldn’t be trusted with your memories. IBM’s most recent "Cost of a Data Breach Report" found that 97% of organizations with an AI-related security incident didn’t have appropriate access control in place to manage who could access those AI systems or the data they processed. The technology exists to decouple AI intelligence from data ownership. Rather than handing over the keys to the castle by duplicating your data into an AI vendor's system, businesses need to let the AI come to their data.​With modern zero-copy architecture, you don't have to ship your data off to a vendor. Instead, the AI system simply reads a secure pointer to the information exactly where it sits in your own warehouse. You get the highly customized results you need, but the vendor never actually takes possession of your corporate memories.Architecture Over PolicyAI is changing the way we interact with our technologies, transforming abstract data into digital memories. Our relationship with data privacy needs to change alongside it. Good intentions and user consent banners won’t get us there. Privacy must be solved architecturally.Every company applying this technology should understand the value of its corporate memory, the cost of compromise and the distinction between intelligence and ownership. By ensuring the AI vendor never actually holds your data in the first place, you retain complete ownership of your memory repository and can plug and unplug different AI tools at will.That’s a privacy policy that protects you, your company and your customers by design.Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?