The most useful question about an AI product is what it helps a customer do. A better interaction, a task that needs less attention or an easier way to get something done is more meaningful than the technology label.
Several announcements around CES and NRF in January 2026 make that question concrete. They were demonstrations and rollout plans at different stages, so they should be evaluated on their own terms.
Help with the job the customer already has
Samsung’s CES announcement described a Bespoke AI Jet Bot Steam Ultra with enhanced object and liquid recognition. The customer job is floor cleaning: identifying what is in the way and responding appropriately.
The useful evaluation is how reliably the product handles an actual home. Recognition features and demonstration footage can explain the intended capability. They are not substitutes for testing the conditions in which a customer will use it.
Make the interaction easier
BMW’s January 5 announcement described adding Amazon Alexa+ to its Intelligent Personal Assistant, beginning with the new iX3. The stated rollout started with Germany and the United States in the second half of 2026.
The intended benefit is more natural conversation about vehicle functions and other information. That is a different claim from autonomous driving. The question is whether a person can get useful help with less effort and fewer interruptions.
For other product teams, the lesson is to look at the interaction itself. Where does a customer have to learn an awkward command, repeat context or navigate a sequence that could be made clearer?
Remove friction in an existing service
Papa Johns’ NRF announcement described work with Google Cloud’s Food Ordering agent on a unified voice and text ordering experience. At the January event, the company described demonstrations and a plan to reach customers nationwide by the end of 2026.
The customer task remains ordering a meal. The technology needs to handle that task accurately and make it easier to complete. A demonstration does not establish the final rollout’s performance, availability or commercial result.
Keep the product promise specific
These examples share a useful direction: begin with a recognizable customer need, then decide how AI can help deliver it. They do not establish that an AI feature automatically improves retention or creates an advantage competitors can’t copy.
Ask what changes for the customer and how you will test it. Define the conditions under which the feature works, what happens when it can’t help and how a person can complete the task another way.
What to do this week.
Choose one recurring point of friction in your customer experience. Watch how people handle it today. Identify the information, judgment and action needed to improve it.
Then build a small test around the outcome. Does the customer complete the task more easily? Is the result accurate? Do they understand what happened? Where does the product still need a person?
That is the standard I would use. The customer should be able to explain why the product is better without needing to explain the model behind it.
From the portfolio
Board of Innovation helps enterprise leaders redesign the business around what AI now makes possible, then move from a promising experiment to an operating model that can scale.
Would customers still value the experience if you removed every mention of AI?
