4. Designing for intelligent interaction—turning AI ambition into execution

Design is a leadership act

Design in the AI era isn’t about interfaces or touchpoints. It’s about how leaders enable their organizations to develop intelligent, customer-centric solutions—whether that’s an interaction, a functionality, a concept, or a long-term capability. Design is not a siloed function, but a way of working: structured, scalable, and anchored in value.

As AI deepens personalization and reshapes expectations, traditional design approaches no longer suffice. They don’t address the complexity of intelligent interaction or the orchestration it requires. What’s needed is a leadership-led shift—starting from the individual customer and building outward with intent and structure.

This is the third step in the ICI System: moving from ambition to design. Not design as an outcome, but as an enabling discipline—where intelligent interaction becomes possible because the way of working makes it inevitable.

Start from the individual—always

Customer-centric design begins with the individual—not with segments, tools, or features. Every initiative should start by asking: what experience are we trying to create, and for whom?

This goes beyond targeting or persona work. It means recognizing customer intent, behavior, emotional state, and context. If we expect systems to respond intelligently, our logic, data, and structure must revolve around the individual.

This logic applies to everything—whether designing a service, onboarding flow, or product feature. When you start from individual relevance, intelligent design follows.

Build flexibility into your design logic from the start

Once customer relevance is the starting point, design becomes about enabling flexibility. Not just interaction flows, but the content, rules, and decision logic that systems need to respond dynamically—based on who the customer is, what they’re doing, and where they are in the process.

Every interaction becomes customer-specific through modular content, activated in real time by algorithms—driven by intent, behavior, and context.

This requires more than a journey map. It requires modular content, consistent metadata, and business rules that allow real-time orchestration across touchpoints and systems. Business logic becomes an integrated part of the design process.

The result? Context-aware, high-value interaction: from proactive messages to predictive recommendations. And each moment stems from design work done upstream—in structure, not style. 

This is where leadership invests: not only in smarter tools, but in a scalable way of working—and the underlying content, data infrastructure, and algorithms that enable personalization at scale.

Use Working Backwards User Stories to design what matters—now and in the future

Designing from the individual means starting with clarity about the value you want to deliver—and then mapping back what must be in place to make that possible. This is what the Working Backwards method enables. It doesn’t begin with what’s feasible today, but with what matters most to your customer.

Every Working Backwards story captures a desired interaction, the business value behind it, and the technical and organizational dependencies required to deliver it. It links customer relevance to internal action.

It also forces long-term thinking. Each story must reflect both what the customer should experience in the next two years—and how that interaction should evolve over five years. What can we already do today? What needs to mature or align to scale this intelligently?

In doing so, it becomes a design method, a roadmap tool, and a valuable source to continuously improve performance and strategic alignment. Used consistently, Working Backwards brings ambition into motion. It empowers teams not only with what to build, and why—but ensures their work contributes to broader goals.

Differentiate based on relationship depth and context

Intelligent interaction isn’t one-size-fits-all. Some relationships are transactional, others strategic or emotional. The way we design should reflect that.

Working Backwards helps surface this variation. For example: a first-time customer buying a product needs a different interaction than a returning or loyal customer—within the same flow. One expects reassurance, another values speed, and a third seeks recognition.

The base interaction remains the same; what changes is the content, tone, and logic—dynamically tailored by algorithms based on behavior, context, and emotional nuance.

Designing for this requires a content infrastructure that supports variation, and a rule system that enables those differences to be triggered in real-time—without building endless journeys or custom paths.

This is how you avoid complexity and enable hyper-personalization at scale. Leaders must ensure teams are equipped to think in gradients—understanding that relationship context, not channel volume, drives relevance.

Orchestrate through the Gearwheel—connect what needs to work together

As you work backwards from desired interactions, a pattern emerges: no department can deliver this alone. Intelligent interaction is inherently cross-functional. It touches systems, data, content, timing, compliance, and customer experience. This is where orchestration becomes essential—and where the Gearwheel becomes indispensable. 

The Gearwheel is not just a model you implement. It’s a way of working that leadership uses to structure cross-functional collaboration around intelligent interaction. Each new user story exposes contributions needed from six organizational domains: Content & Intent, IT & Data Intelligence, Platforms & Value Chain, Legal & Compliance, Organization & Orchestration, and Business Models.

The ICI Gearwheel structures interdepartmental collaboration to develop holistic, customer-centric concepts, functionalities  and interactions.

The Gearwheel shows how these functions interlock. It doesn’t centralize control, but provides shared structure. It turns a user story into a shared agenda—where content creators, compliance experts, product leads, and data architects work together to make one customer experience real.
It helps the involved departments understand not just what to deliver, but how their timelines and investments relate to each other. It turns isolated development into coordinated design.

 The Gearwheel enables leadership to empower their teams, not control them. It embeds coherence into complexity and prevents disconnected AI pilots or one-off solutions. It turns strategy into execution—by aligning every part of the organization around a shared outcome.

Build organizational readiness and enable continuous design

To deliver intelligent interaction at scale, organizations must be capable of designing and evolving continuously. That requires more than funding or tools—it takes a new rhythm of working.

Not every domain is equally mature. Some teams may already deliver modular content; others may still be aligning on data access or compliance logic. That’s normal. The design step surfaces these gaps—not to solve them all at once, but to sequence progress realistically and build readiness over time.

This is where leadership plays its most critical role: not by micromanaging, but by setting clarity of ambition, enabling shared frameworks, and empowering teams to collaborate with less friction.

The Gearwheel supports this process by offering a structure—so that collaboration doesn’t rely on personal initiative, but becomes part of how things get done. When design becomes an organizational rhythm, AI can scale with intent.

Conclusion — Design is how leadership shapes what becomes real

Design isn’t a phase or a function—it’s how leadership builds the conditions for AI powered intelligent interaction to emerge and scale. It turns strategic ambition into execution logic.

By starting from the individual, designing adaptive content and logic, working backwards with intent, and aligning teams through the Gearwheel, organizations don’t just design solutions—they build the capability to deliver, evolve, and put the promise of AI to work..

This is where Intelligent Customer Interaction becomes a reality—not just for one department, but for the organization as a whole.

What’s next?

In the next article, we explore how to measure the impact of this AI powered reality—through intelligent KPI’s that reflect not only commercial performance, but progress in relevance, engagement, and long-term customer value both at the individual and overall customer level.