How can AI customer experience projects identify the real problems to solve?

Start with the specific difficulties customers face

When a business wants to use AI to improve customer experience, it should first explain what task customers need to complete, in what context, and where they currently encounter difficulties. Long waits, difficulty finding information, and unclear handoff responsibilities may require different approaches. They should not all be treated as a need for a single AI-powered entry point.

The public conference overview for CES 2026 covers AI and enterprise technology. Building on that direction, this article discusses how customer experience projects can define problems; specific outcomes need to be validated in actual service settings.

Observe the existing journey and the roles involved

Choose a representative task, such as a customer checking whether a product meets their requirements and contacting the technical team. Record where the customer starts, what information they need, whom they communicate with, when they receive confirmation, and how exceptions are handled.

Sales, customer service, technical, and delivery teams may each hold different information. Collect work records and feedback with appropriate permission, and distinguish observed problems from team assumptions. Where samples or scenarios are insufficient, explicitly mark findings as requiring validation. A small number of opinions should not be presented as a conclusion shared by all customers.

Also examine barriers related to mobile devices, network conditions, language, and users with different abilities. Research participation methods, privacy arrangements, and the use of materials should be explained in advance and confirmed by the business.

Distinguish content, process, and technology issues

If customers cannot find the latest specifications, the information access points and versions may need to be organized. If answers differ across channels, authoritative sources and responsibility for updates may need to be clarified. If complex questions cannot be resolved automatically, a handoff to staff needs to be designed. Identify the source of the problem before deciding whether to introduce AI.

For each proposed solution, specify the inputs, outputs, supporting sources, human review, and error handling. Product models, service scope, and contract terms require confirmation from the relevant people responsible. The model must not fill gaps in the available information with definitive conclusions.

When customer information or third-party services are involved, the business's relevant specialists should confirm data purposes, access permissions, and actual processing practices. Permission notices in design mockups should match the real system.

When discussing customer problems, also consider visits that begin directly on deeper pages. A visitor may arrive at a product document through search without having seen the homepage introduction. In that case, the page should identify the model, version, and conditions the document applies to, and show the customer how to find further help.

Define a pilot scope that can be tested

Select one task with relatively complete supporting materials and clear responsibilities. Define the pilot participants, work steps, conditions requiring confirmation, and paths for exiting or transferring to staff. When comparing the pilot with the existing process, record the test environment and findings rather than promising time savings or increased sales in advance.

Ask participants to try finding information, understanding system feedback, and contacting the people responsible. Observe whether they know what to do next, can check the sources behind results, and can continue after a failure. Leave scenarios not covered by testing marked as requiring validation.

Simulated interfaces and sample materials should be clearly labeled. They must not display unauthorized customer information or fabricated project results.

Hand over findings to the responsible teams for ongoing maintenance

Document confirmed customer tasks, causes of problems, material versions, owners, and action items. Product, customer service, content, and technical teams should jointly decide which changes to include in the current phase and which require further research. After launch, review them when the business or systems change.

Ensure customers can find a feedback channel, and establish how issues enter the handling queue. Qingmei Future can assist with customer journey and digital experience design. Data processing, technical implementation, and service commitments must be confirmed by the relevant people responsible within the business.

If the needs of different customer roles conflict, document the disagreements in the project materials, explaining the tasks each role needs to complete and the available evidence. The business owner authorized to determine scope should lead decisions on trade-offs. Tools should not automatically merge differing views into a single, unconfirmed conclusion.

Discussion Background and Scope

CES · What Not To Miss at CES® 2026 · 2026-01-02. Official page date: 2026-01-02. The source discusses ces 2026 event plans and technology themes. It is background reading, not evidence for each practical recommendation in this article. The recommendations are Qingmei Future’s independent analysis.

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