Why organizations that redesign buyer journeys earlier than implementing AI will outperform those who don’t
Over the previous 12 months, AI has produced a sequence of high-profile buyer expertise failures. Pizza Hut is being sued for $100 million after a franchisee alleged an AI-powered supply optimization system elevated delays and harm buyer satisfaction somewhat than enhancing it. Air Canada was held accountable after its automated AI agent supplied prospects with incorrect details about bereavement fares. In each circumstances, the expertise carried out because it had been deployed, however there have been crucial failures in how AI was designed into the shopper expertise.
For many years, organizations have chased expertise platforms as a solution to progress and effectivity. The sample is acquainted: a compelling functionality emerges, leaders transfer quick to undertake it, and the expertise will get layered onto journeys and workflows that had been by no means redesigned to assist it. AI magnifies this downside. In contrast to many applied sciences, AI brokers don’t sit inside one system or one workforce, they affect your complete journey, from how prospects uncover and purchase to how they obtain service and stay loyal. Each AI interplay is now a buyer expertise choice, and each buyer expertise choice has business penalties.
The crucial query all enterprise leaders should ask is the place AI belongs and the place AI doesn’t belong. The standard of these design choices will decide whether or not AI turns into a progress engine, an costly operational burden, or the catalyst for enterprise and model worth destruction.
Don’t Create Worse Buyer Experiences Utilizing AI
There may be extraordinarily excessive stress to implement AI brokers, actually, greater than 90% of servicing leaders report govt urgency to implement AI. On the identical time, the margin for error has by no means been decrease – it’s by no means been simpler to change manufacturers, and 80% of shoppers stated they’ve switched manufacturers due to poor buyer experiences. This equation needs to be scary for enterprise leaders. Most leaders are responding by transferring quick, piloting brokers throughout buyer touchpoints, and hoping effectivity beneficial properties will comply with. This is similar sample organizations skilled chasing expertise to reply progress and effectivity challenges.
When AI is launched into journeys that had been already fragmented, it accelerates the fragmentation. Clients encounter inconsistent solutions throughout channels, context disappears between digital and human interactions, staff hesitate to behave on suggestions that battle with their expertise, and escalations enhance at the same time as automation expands.
The enterprise affect can quietly compound, decision instances slowing as a consequence of rework, cost-to-serve growing as folks compensate for poorly designed automation with extra outreach, or dramatically enhance, if buyer belief is eroded and prospects determine to go away en masse. Finally, prospects will go away if their experiences are poor.
The danger lives within the deployment of expertise. How, the place, and why AI will get deployed are the important thing questions leaders have to reply, and that is solely answered with a considerate and pragmatic AI design technique.
4 Design Selections Leaders Must Make
The organizations positioned to win with AI are transferring intentionally. Earlier than deploying brokers, they’re doing one thing that sounds easy however requires actual self-discipline: quantifying which experiences justify AI funding after which designing how AI, folks, information, and workflows ought to work collectively to ship experiences prospects will belief.
This deliberate motion is what we name Agentic by Design. It’s not a maturity mannequin or a deployment guidelines, Agentic By Design is a strategic working lens constructed round 4 elements that have to be addressed collectively earlier than AI brokers are built-in into buyer experiences: choice design, workflow orchestration, human and machine roles, and worth realization.
- Choice design. Which choices form the shopper expertise and who ought to make them? Not each choice needs to be automated. The organizations creating probably the most worth with AI intentionally outline the place AI acts, the place folks lead, and the place human judgment stays important.
- Workflow orchestration. How does work transfer throughout folks, programs, and AI with out breaking the expertise? It’s an outdated buyer expertise adage – prospects don’t expertise capabilities; they expertise journeys. The most important failures in agentic AI aren’t the fashions themselves, however the handoffs the place context, accountability, and continuity are misplaced.
- Human and machine roles. When ought to AI act autonomously, when ought to it help, and when ought to folks step in? Clear function definition builds belief, improves adoption, and ensures AI augments staff somewhat than creating new operational friction.
- Worth realization. Which expertise enhancements justify the funding? AI needs to be evaluated like all strategic funding with a transparent connection between buyer expertise, operational efficiency, and enterprise outcomes. With out that connection, organizations wrestle to prioritize investments, show ROI, or scale what works.
These 4 elements are interdependent. When addressed collectively, they create the situations for AI to speed up worth; when addressed in isolation, or by no means, they’re the place AI investments stall or trigger public-facing model and buyer worth crises.
The Finest Time To Design Is Earlier than You Construct
Not each group begins in the identical place, and never each buyer journey wants autonomy. Some organizations want to cut back operational friction earlier than introducing AI, others are able to orchestrate work throughout folks, programs, and AI. A smaller group is ready to ship proactive, extremely customized, extremely autonomous experiences. The target isn’t to climb a maturity ladder, however somewhat, to begin the place buyer expertise, belief, and economics intersect most sharply.
Virgin Voyages took this method. Reasonably than deploying a chatbot to cut back name quantity, the workforce first recognized the service interactions creating the very best buyer effort and cost-to-serve. They found AI was creating work somewhat than decreasing it. By redesigning AI-to-human handoffs, clarifying choice possession, and defining the place human judgment remained important, the group diminished name middle escalations by greater than 20% at launch.
Buyer-facing AI is basically a design problem. Most organizations can deploy expertise, however far fewer can decide the place AI belongs, how work ought to change round it, and the way worth might be created due to it.
Agentic By Design is centrally targeted on intent. Intent, not the mannequin, the finances, or the variety of brokers in manufacturing, is the differentiator. Organizations that design intentionally earlier than they deploy will create compounding worth. Those who don’t will spend years unwinding the price of transferring too shortly.
