Event Details

Why Your AI Isn’t Being Used and How to Design AI Workflows That Work

Wed, Jul 22, 2026 | 11:00 AM to 11:45 AM ET

Most organizations have made the investment. The tools are deployed. The licenses are purchased. Leadership has mandated adoption. And yet, across industries, the same pattern repeats: enterprise AI sits at 20–30% weekly usage of the seats businesses are paying for while the rest of the workforce quietly works around it.

The assumption is that this is a training problem. Or a change management problem. Or a generational problem.

It isn't.

It's a design problem.

AI tools built for the budget approver — not the person doing the work — will always fail at scale. When your AI doesn't understand who is using it, what they're trying to accomplish, or how their day actually works, it creates friction instead of removing it. And friction kills adoption faster than any competing priority.

Meanwhile, a growing cohort of AI-native employees inside your organization has already moved on. They're building their own workflows, using their own tools, and creating the shadow AI ecosystem that your governance teams haven't caught up with yet.

The organizations pulling ahead aren't the ones who bought more AI. They're the ones who designed better AI experiences — built around real human roles, real workflows, and real business outcomes.

Who Should Attend

This session is designed for leaders who own both the AI investment decision and the people who are supposed to benefit from it.

Chief Marketing Officers and VP Marketing who have deployed AI creative and content tools and are frustrated by inconsistent adoption and brand governance challenges across teams and business units.

Chief Operating Officers and Operations Leaders who are responsible for workforce productivity and are trying to understand why AI efficiency gains aren't showing up in their performance numbers.

Chief Digital Officers and Chief Technology Officers who are accountable for enterprise AI strategy and need a practical framework for designing agentic systems that scale beyond early adopters.

HR and People Leaders who are navigating workforce transformation conversations and need a more honest framework than "AI won't replace your job."

What You Will Learn

In this session, Michael Mayton, EVP and Head of Strategy and Experience at Bounteous, will walk through the specific design principles that separate AI implementations with 70%+ adoption from those stuck below 30% — drawing on real deployments across Global 2000 organizations.

You will leave with a clear understanding of why the shift from prompt-based AI to intent-aware AI changes everything about how you deploy and design for your workforce. You will see what a human-centered agentic system actually looks like in production — not in theory. And you will walk away with a practical starting framework your organization can apply immediately, regardless of which AI platforms you have already invested in.

What We Will Demo

We will demo Bounteous's AI experience built for a multi-brand creative organization — showing how an intent-aware system replaces the prompt box with a role-specific, context-aware interface that understands what the user needs before they have to ask.

The demo covers three integrated agents working as a system: the orchestration layer that routes work to the right specialists, the governed library that persists institutional memory across teams and devices, and the insights layer that closes the loop between creative decisions and business outcomes.

This is not a product pitch. It is a live illustration of what human-centered agentic design looks like when applied to a real enterprise workflow — and the specific design decisions that drive adoption.

Key Takeaways

• By the end of this session, you will be able to diagnose whether your current AI implementations have an adoption problem rooted in design rather than training or change management.
• A clear understanding of the three-agent architecture that underpins scalable agentic systems — and how to apply it to your own organization's priority use cases across marketing, operations, and program management.
• A practical framework for evaluating AI tools and implementations through the lens of your actual workforce — not the idealized user those tools were designed for.
• And a concrete understanding of what separates organizations compounding AI advantage quarter over quarter from those that are stalled — and the specific first steps to move from one category to the other.