How can brand strategy guide a company's choice of AI use cases?

Define the business problem before comparing technical solutions

When companies prepare to introduce AI, they often receive suggestions ranging from content generation and customer service to knowledge retrieval and data analysis. Each technology may be useful, but teams still need to determine whether it supports the customer's current task, aligns with the brand promise and produces outputs the company can maintain.

Public discussions about AI and creativity at CES 2025 addressed technology and human involvement. Building on that topic, this article proposes a working approach for companies selecting use cases. It does not certify any specific product or outcome.

First, clearly describe what customers or employees need to accomplish, where they encounter difficulties and what verification steps exist in the current process. Then decide whether AI is needed. A problem with finding information may first require outdated documents to be organized, rather than immediately adding automated answers.

Use the brand promise to define essential requirements

Translate the brand promise into requirements that can be checked. For example, a company that wants customers to receive accurate product information should confirm document versions, conditions of use and a review process involving technical staff. If collaborative service is a priority, explain how the system and human teams will hand work over to each other.

These requirements must be tied to existing capabilities and named owners; they cannot be inferred by a generative tool. Services, regional support or product features that are not yet available should be marked as areas for development, rather than presented as current promises.

Separately listing facts that must remain consistent, wording that can be adapted by channel and questions that require escalation for confirmation helps departments work from a shared basis when using new tools.

Compare the value, information and responsibilities of each use case

For each potential task, record the intended audience, input materials, expected output, business owner and steps requiring human confirmation. Assess whether the required information is reliable, whether it may be used for that purpose, what an incorrect output could affect and whether customers can find help.

For example, when a content team compiles public product introductions, the product owner still needs to verify model numbers and conditions of use. When customer service answers questions about specific operating conditions, it may need to refer them to engineering staff. The depth of verification should reflect the actual impact of each task; a single approach cannot be applied across the board.

Without validated data on cost, speed or effectiveness, do not promise specific benefits in advance. Add these questions to the pilot validation checklist, and define how they will be assessed and who will make the decisions.

The evaluation team should also document existing alternatives: how customers currently obtain information, which steps involve waiting and which checks already work well. A new solution must be compared within specific tasks to determine whether it actually solves the problem. Demonstration speed alone should not be taken as evidence that the entire business process has improved.

Use a limited pilot to check the full process

Choose one task with relatively complete information and clear responsibilities, such as helping customers find the latest product documents. Compare the current process with the new solution. Check whether users understand where to start, can find sources and know how to proceed when the system is uncertain, and establish who is responsible for keeping information in sync after updates.

The company's responsible personnel should confirm the data, user information and access permissions used in testing against applicable requirements. Simulated examples should be labeled and must not be presented as actual customer results.

Keep records of the test environment, participants' tasks, issues and conditions that were not covered. A small number of observations reflects only specific circumstances and cannot directly support a conclusion that all customers will have the same experience.

Carry the findings into ongoing maintenance

After the pilot, document confirmed capabilities, unresolved issues, relevant pages, information versions and responsible owners. If the company decides to expand use, first confirm the respective update responsibilities of the product, customer service, brand and technology teams. Steps that are unsuitable for automation can remain manual.

When product versions or service terms change, check that the website, sales materials and knowledge base remain consistent. Qingmei Future can assist with brand assessments and digital experience planning. Technical implementation, data processing and final service commitments must be confirmed by the company's relevant responsible personnel.

When communicating about the pilot externally, distinguish between features already available and ideas awaiting validation. The respective responsibilities of partners, technology providers and internal teams should also be confirmed for each project, so that brand communications do not make service commitments beyond what current conditions support.

Discussion Background and Scope

CES · AI & Creativity: Navigating the New Frontier in Advertising · 2025-01-09. Official page date: 2025-01-09. The source discusses ai, marketing creativity and human involvement. 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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