As a Chief Information Officer, I’ve always believed technology should enable progress—not compromise it. And yet, as AI adoption accelerates at an unprecedented pace, I find myself standing at a complex intersection: customers demand innovation through AI, but they also demand something else—privacy, control, and trust.
We are not alone in facing this tension. Companies across the globe are racing to implement AI into their products and operations. According to McKinsey, 92% of organizations plan to increase their AI investments over the next three years, but only 1% feel mature in their AI practices. Many of us are still figuring it out—especially when it comes to navigating the murky waters of data protection and regulatory compliance.
In my world, the complexity is compounded by a dual reality: some of our customers expect us to use AI to enhance our offerings—make them faster, smarter, and more responsive. Others—often in the same industries—explicitly prohibit us from using any of their data in AI tools unless we have their written consent. These aren’t just preferences; these are contractual requirements rooted in legitimate data protection concerns.
And I don’t blame them.
We’re living in a time where data breaches, surveillance fears, and questions about AI ethics dominate headlines. Generative AI tools, while powerful, introduce real risks—data leakage, hallucinations, bias, and even misuse of sensitive content. As Dentons highlighted in their 2025 AI Trends report, the rise of AI-driven cyberattacks and misuse of personal data is pushing regulators to take a harder stance on privacy enforcement and ethical AI design.
This regulatory pressure is growing—and growing fast. It seems like every week brings a new law, rule, or framework from a different region of the world. From the EU’s GDPR and AI Act to evolving U.S. state-level regulations like CCPA, businesses are expected to keep pace with requirements that are often conflicting and rarely harmonized. The Future of Privacy Forum (FPF) recently noted that international data transfers and cross-border privacy standards will be a key flashpoint in 2025 and beyond.
So how do we responsibly move forward?
For me, it starts with this guiding principle: data protection must be embedded into the DNA of AI development. Privacy-by-design is no longer a nice-to-have—it’s an imperative. We must ensure our AI strategies incorporate transparency, consent, data minimization, and secure data processing from the outset.
Equally important, we need boundaries.
That’s why I believe our industry must come together—technology leaders, policymakers, and innovators—to define a common framework for AI governance that balances innovation with privacy. One that:
- Respects data ownership and consent
- Differentiates between data used for AI model training vs. AI-enabled features
- Enforces strong access controls and encryption
- Supports certifications that validate AI and data protection readiness
- Allows customers to opt in or opt out of AI participation without penalty
Until we create this shared foundation, we risk moving too fast, breaking trust, and losing the very people we’re trying to serve. Our customers need confidence that AI won’t become a backdoor to their data. Our regulators need assurance that we’re doing more than just talking about compliance. And we, as technology leaders, need clarity and alignment in a world that’s moving too quickly for trial-and-error.
AI’s promise is real. So are the risks. And finding that balance is not someone else’s job—it’s ours.
Let’s lead with responsibility, together.
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