Building Consensual Digital Products in the Age of AI

The “Simple Prompt” Problem

Picture this: Your customer picks up their phone and says to their AI agent, "Buy two tickets to the Bad Bunny concert in July 2026, add it to my calendar, and let my friends know in our group chat."

One simple prompt. Two seconds. Done.

Except it's not done. Not even close.

Because behind that seemingly simple prompt sits a web of permissions that needs to be orchestrated: payment credentials, calendar access, contact data, cross-platform authentication, third-party API integrations. Each one a potential point of friction, or a spectacular failure of trust.

Here's what’s been keeping me up at night: the simpler AI makes the ask, the more complex the consent architecture becomes. And right now, most of us (brands and users alike) are seriously underestimating this gap.

Your Product Just Got a New User

For years, we've designed for humans. We've optimized for their attention spans, their cognitive limits, their delight. We've built frameworks to make sure our products are Usable, Valuable, Viable, and Feasible. At Umain, this model has guided everything we build, and it works.

But something fundamental has shifted, and our frameworks haven't caught up yet.

Your product now has a new middle layer: the AI agent. But make no mistake, the relationship that matters is still between you and the human. The agent is just the messenger, the executor, the interface. The trust bond? That's still human-to-brand. It always has been, and it always will be.

What's changed is that now you need to maintain that trust through a layer you don't fully control. And that changes everything about how you design for consent.

Why This Is About Trust, Not Compliance

Let me be clear: this isn't about checking a legal box or adding another privacy modal that nobody reads. This is about preserving and strengthening the trust relationship with your actual user (the human) in a world where an AI agent is acting as their proxy.

Here's the challenge: when an agent handles a transaction on someone's behalf, the human isn't in the driver's seat moment-to-moment. They're not clicking through each step, reading each confirmation, seeing each data handoff. The complexity is abstracted away, which is exactly what makes AI agents so powerful and so risky.

This is why user awareness matters more now, not less. Your customers need to understand what's happening with their data, who has access to it, and what guardrails are in place. They need to feel safe. And "feel safe" isn't about clever UX that hides complexity. It's about genuine transparency, control, security, and traceability built into how your product works.

When users trust you with their AI agent's access, they're trusting you at a deeper level than they ever did when they were clicking buttons themselves. Because now they're trusting you with delegated authority. That's not a small thing.

So we need to add a fifth pillar to our framework. We need our products to be Consensual.

The Perception Gap We're Not Talking About

There's a critical disconnect happening right now, and it's going to bite us if we don't address it.

Users think this is easy. They see the ads, they hear the marketing, they watch the demos. "Just ask your AI to do it." The promise is frictionless automation, and honestly, that promise is intoxicating. Who wouldn't want their AI agent to handle the tedious parts of life?

But the reality behind that promise? It requires navigating a Byzantine maze of data permissions, each with its own security model, each with different standards for what "consent" even means.

Let me break down what's actually happening when your customer asks their agent to buy those concert tickets:

The agent needs to authenticate their identity across multiple platforms. It needs explicit permission to access payment information (not just once, but in a way that's scoped, auditable, and revocable). It needs calendar write access. It needs to read contact data to identify "friends in our group chat." It needs to post to a third-party messaging platform, which has its own permission model. And ideally, it needs to do all of this while maintaining a clear trail of what it did, why, and on whose authority.

That's not one simple prompt and two seconds. That's a complex orchestration of trust handshakes.

And here's the gap: users don't understand this complexity. They shouldn't have to understand every technical detail (that's not their job). But they do need to understand what they're authorizing and why it matters. And brands (us), we need to stop treating consent as an afterthought and start treating it as core product architecture.

We need to raise awareness on both sides. Users need to know what's happening with their data in clear, comprehensible terms. And brands need to build systems that make that transparency possible.

What "Consensual" Actually Means

So what does it mean for a product to be Consensual in the age of AI agents?

It means your users (the humans) actually understand what's happening with their data and feel confident in how you're handling it. Not because you buried the details in fine print, but because you've made the complex comprehensible.

Consensual products are built on four pillars:

Transparency: Users can see what data their agent is accessing on their behalf, who it's being shared with, and why. This isn't about overwhelming people with technical details. It's about clear, honest communication about what's happening behind the scenes.

Controllability: Users can set boundaries, revoke access, and adjust permissions as their comfort level evolves. They're not locked into decisions they made months ago when they didn't fully understand the implications.

Security: The technical infrastructure protecting their data is robust, auditable, and designed with their safety in mind (not just regulatory compliance).

Traceability: There's a clear record of what happened, when, and on whose authority. If something goes wrong or feels off, users can see exactly what their agent did and understand why.

These aren't nice-to-haves. They're the foundation of sustainable trust in an AI-mediated world.

The Competitive Advantage of Getting This Right

Here's what makes this a strategic imperative, not just an ethical one: trustworthiness is about to become your strongest differentiation factor.

Not just trustworthy protocols (though those matter). I'm talking about something bigger: end users genuinely feeling safe with your brand. Feeling like you see them as humans, not just data sources. Feeling like you're on their side even when an algorithm is doing the work.

Think about the concert ticket scenario again. Imagine two competing ticketing platforms. Both have similar inventory, similar pricing, similar features. But one has built a reputation for transparent consent. Users know exactly what data their agent needs, they can see the audit trail, they can revoke access granularly. The other has opaque permission flows and a history of "we'll handle it, don't worry about it."

Which one do you think users will authorize their agents to access?

Get this right, and you're not just compliant. You're preferred. You're the brand people feel good about giving access to. You're the one that wins when trust becomes a deciding factor.

Get it wrong, and you're shut out (not by regulation, but by users who simply choose the brand that makes them feel safer).

What This Means for Product Strategy

So what do you actually do with this? How does "Consensual" translate into product decisions?

Rethink your onboarding and permission flows. Stop asking for all permissions upfront. Build progressive consent that matches the user's journey and understanding. Explain why you need what you need, in language that respects their intelligence.

Audit your partner ecosystem. Your consent architecture is only as strong as your weakest integration. When you connect to third-party services, you're asking users to extend trust to those partners too. Choose carefully. Vet thoroughly.

Build transparency into your UX, not just your privacy policy. Create dashboards where users can see what their agent has accessed, when, and why. Make audit trails accessible and understandable. Don't hide this information. Surface it as a feature.

Design for revocability. Users should be able to withdraw consent as easily as they gave it. And when they do, your system should gracefully handle that without breaking their experience or punishing them for changing their mind.

Invest in education. Part of building consensual products is helping users understand what they're consenting to. This isn't about overwhelming them with legal jargon. It's about empowering them with clarity.

The Call: Building for the AI-Agent Economy

The companies that recognize this shift (that treat consent as core product architecture, not a compliance afterthought) are the ones that will define the next era of digital products.

This isn't about slowing down innovation. It's about building innovation that lasts. Because trust, once broken in an AI-agent world, is nearly impossible to rebuild. Users won't just leave your platform. They'll instruct their agents to avoid you entirely.

But earn that trust? Build products where users genuinely feel safe, informed, and in control? That's when you become indispensable.

The promise of AI agents is frictionless automation. The reality is that friction-free only works when it's built on a foundation of genuine consent. That's the work ahead of us.