AI, foresight, and the question of trust: Are you in control?

The world of foresight is built on anticipation—on seeing what’s next before it happens. But what if the very tools designed to help you navigate the future also introduce new risks you didn’t anticipate?

AI is transforming strategic foresight, making it faster and more efficient than ever. But as organizations as well as individual foresight practitioners have rushed to integrate AI into their workflows, a fundamental question has emerged: Can you truly trust AI-powered tools with your foresight work?

The double-edged sword of AI in foresight

There’s no doubt that AI can supercharge foresight work. It can help spot weak signals faster and wider, summarize vast amounts of information, surface connections that might otherwise go unnoticed, and help you produce deliverables at an unprecedented scale.

But foresight isn’t just about processing information—it’s about strategic control. What happens when the data you feed into an AI system is no longer entirely yours?

What if the AI tool you rely on today is training someone else’s model tomorrow—one that competitors, regulators, or even unknown third parties could access? Or what if it is leaking data as we speak?

This isn’t speculation. It has happened before.

The risks: Who really owns your intelligence?

Recent AI security breaches have raised serious concerns about data privacy and control:

• OmniGPT alleged data breach – A hacker allegedly put massive amounts of stolen AI-generated data up for sale on the dark web, raising questions about where your data really goes. (Read more)

• DeepSeek data leak exposes 1 million sensitive records – Even AI platforms designed with security in mind can have vulnerabilities, and when sensitive foresight data is exposed, the consequences can be far-reaching. (Read more)

• Nearly 1 in 10 of employee AI prompts may contain sensitive information – Organizations may not even realize the extent to which their teams are feeding confidential data into AI systems they don’t control. (Read more)

While foresight data doesn't usually contain sensitive information that would fall under regulation such as GDPR or CCPA, it certainly can contain proprietary information and business secrets that are not supposed to be disclosed outside the organization.

AI-powered tools promise efficiency, but who controls the information once it’s entered? Are you still the owner of your own foresight and futures intelligence?

Foresight without control isn’t foresight

AI shouldn’t replace human expertise—it should enhance it. But for that to happen, organizations need to be deliberate about how they use AI in foresight work.

Before integrating AI into your strategic foresight process, ask:

• Where does the AI process my data? If it’s sent to an external model or even multiple different models, do I know how it’s stored and used?
• Does the AI learn from my inputs? Am I contributing to a dataset that others might access? Will it regurgitate information fed by me to other users in the future?
• Who controls the insights AI generates? Are these uniquely mine, or is my intelligence shaping a broader model that benefits competitors too?

At FIBRES, we’ve always believed that foresight belongs to those who build it. That’s why, in developing AI-powered capabilities, we have always made one thing clear: Your proprietary data never leaves our cloud platform for AI processing and AI-powered foresight should serve you—not extract value from you.

If you’re curious about how we build and continuously improve AI capabilities while keeping data security at the core, you can read more here.

AI has an undeniable place in the future of foresight. The future of AI-powered foresight isn’t just about using the latest tools—it’s about choosing the right ones.