Your AI strategy has a trust problem

The headline says it plainly: your AI strategy has a trust problem. That’s not a branding issue. It’s an operational one. People don’t use AI tools when they don’t trust them. And trust isn’t built by adding more features or lowering prices. It’s built by showing how the tool works, who benefits, and what goes wrong when it doesn’t.

The author, writing on Substack, frames this as a product strategy issue. The advice is practical. Don’t hide behind jargon. Don’t promise magic. Show the inputs, show the outputs, show the limits. Let people test it themselves. Let them see the seams. Trust comes from transparency, not from hype.

This hits hard for small business owners, freelancers, and community organizers who are already being pushed to adopt AI tools by consultants or vendors. If the tool doesn’t explain itself, people won’t use it. Period. And that’s a problem for anyone trying to build a real product, not a demo.

The post doesn’t give a step-by-step guide. It’s more of a wake-up call. But the point is clear: trust is the bottleneck. Not cost. Not speed. Trust. And trust is earned by being honest about what the tool can and can’t do.

Why this matters for us: When we try to use AI to help our businesses or our communities, we need tools we can trust — not flashy demos that vanish when the novelty wears off.