Editorial
Research Report
Your Reputation Is On the (Phone) Line
The Gist
- Most AI pilots fail to scale because context is missing. Despite strong belief in AI’s impact, organizations stall when ideas aren’t tied to real customer pain points, clear value, or change management plans.
- Customer journey mapping is the starting line for AI in commerce. Mapping end-to-end journeys helps leaders spot friction, uncover white space, and prioritize AI use cases like guided selling and personalized discovery.
- Discipline beats experimentation theater. AI ideas must be qualified on growth, efficiency, readiness, and scalability — then piloted with a clear plan to scale or stop, not linger.
Despite the promise of AI in digital commerce, many organizations struggle to move beyond underwhelming pilots. According to Gartner research, while 86% of CMOs believe AI will positively impact marketing, fewer than half of AI pilots are successfully scaled.
The main culprits? Lack of capabilities and insufficient demonstration of value caused by a lack of idea qualification and change management to drive adoption. For digital commerce leaders, the path to AI success starts with a strategic, customer-centric approach grounded in journey mapping to identify ideas to address pain points and opportunities.
Table of Contents
- Identify AI Ideas with Customer Journey Mapping
- Implement Pilots With a Plan to Scale or Stop
- Measure and Optimize for Sustainable AI Success
Identify AI Ideas with Customer Journey Mapping
Too often, AI initiatives are launched without clear business context, resulting in solutions that miss the mark. The antidote: customer journey mapping. By visualizing the end-to-end digital commerce experience, leaders can pinpoint pain points, like limited personalization or inefficient post-purchase offers, and uncover "white space" opportunities for AI to add value such as agentic guided selling.
Instruct your teams to review journey maps, focusing on friction points and untapped opportunities. For example, use generative AI to create personalized ads, or implement AI-powered buying assistants to guide self-service discovery. Evaluate whether your existing platforms offer the necessary AI capabilities, or if a custom solution is required.
Related Article: Not Your Grandparents' Customer Journey
Qualifying AI Ideas Before They Scale
This scoring framework helps digital commerce leaders evaluate which AI initiatives are worth piloting — and which should wait — based on business impact and organizational readiness.
| Dimension | What It Measures | High | Medium | Low |
|---|---|---|---|---|
| Growth | Anticipated revenue or profitability increase | Exceeds 20% | Between 5% and 20% | Less than 5% |
| Efficiency | Expected cost optimization or time savings | Exceeds 20% | Between 5% and 20% | Less than 5% |
| Readiness | Speed at which the business can launch | Less than 3 months | 3 to 6 months | More than 6 months |
| Scalability | Ability to expand across channels, audiences, and markets | 10 or more use cases or markets | 5 to 10 use cases or markets | Up to 5 use cases or markets |
Digital commerce leaders should justify each score with evidence grounded in business and market context. Advancing only the top two or three ideas to implementation helps maintain focus and prevents resources from being spread too thin.
Implement Pilots With a Plan to Scale or Stop
A successful pilot is only the beginning. To ensure long-term impact, approach each AI pilot with clear intent to scale and embed, or decisively stop if results fall short. Develop a "pilot on a page" outlining:
- Scope: What's included and excluded?
- Success Criteria: Milestones for growth, efficiency, readiness and scalability.
- Scenario Pathways: Actions to take if the pilot succeeds, needs more time or fails.
Establish robust governance for pilots, focusing on decision rights and transparent communication. Regularly review progress against the pilot plan, and be prepared to pivot or terminate projects that do not deliver.
Measure and Optimize for Sustainable AI Success
CMOs must oversee the entire AI journey from idea identification to qualification and implementation. Success should be measured by the percentage of pilots that evolve into fully scaled, embedded solutions. Aim for at least 60% of AI ideas to reach this stage by setting realistic goals and maintaining disciplined oversight.
Use journey mapping and qualification frameworks as ongoing tools, not one-off exercises. Continually refine your approach based on pilot outcomes and leverage customer journey analytics to track changing market dynamics.
In a crowded digital commerce landscape, AI can be a powerful differentiator, but only when deployed with discipline and business context. By focusing on personalization through journey mapping, rigorous qualification and structured pilot implementation, digital commerce leaders can maximize the value of AI investments and drive sustainable growth.
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