The Time Lag of Growth: How Consumer Brands Should Embrace AI

Consumers start to write their uncategorizable daily lives into a dialog box.

"Limited budget, for parents, hope it is practical and can convey my care." The selection of a gift can start from the description of several such phrases. Before the product name even appears, consumers first provide their budget, recipient, scenario and emotional expectations, and then AI helps them compare, filter and gradually find the right choice.

Screening, comparison and sorting, this mental work that used to be completed by consumers themselves, is now partially handed over. For brands, this is an unfamiliar position. Exposure can be purchased, but "why a product is worth recommending" requires more specific explanations.

What is more subtle is another level of mismatch. AI has been deployed in many positions of consumer goods enterprises: writing scripts, generating images, editing materials, and the efficiency improvement is visible to the naked eye. However, partial efficiency improvement does not equal the growth of the whole business. Many people have a different perception: AI seems to be everywhere, but growth is still stagnant. The problem lies not only in the tools, but also in whether the data is connected, whether the process is rearranged, and whether the organization collaborates around the new decision-making chain.

When consumers make decisions in a new way, enterprises also need to run their business in a new way. From competing for attention to understanding intentions, from relying on human experience for scheduling to involving AI in analysis and execution, both sides are moving at the same time. Between technological progress and business performance, there is a gap separated by data, processes and organizations. This gap is the time difference of growth.

How to convert technological progress into business growth? This is also the question that 2026 CAEG Ocean Engine Consumer Goods AI Growth Summit on September 17 tries to answer.

Consumers Start to Ask Questions, Brands Need More Specific Answers

The way the public obtains information is changing.

"Scrolling" allows content to arouse interests, "searching" enables people to actively compare and verify, while "asking" accommodates unformed demands, allowing consumers to directly ask AI for judgment.

The three ways coexist and follow one after another in a single consumption process. Consumers can first be attracted by a video, then search for products, or turn to AI for help when they are hesitant.

Ocean Engine summarizes this change as shifting from "people looking for information" to "AI doing the work for people". Public data shows that the total consumption duration of AI applications has increased by 100%, photo search and voice search have increased by 175% and 338% respectively. In particular, 83% of users use AI search to assist consumption decision-making. This means that users are spending more time on AI, and demand expression is also expanding to forms such as images and voice.

AI affects how products are discovered, and also participates in the formation of consumers' purchase reasons.

A broad crowd label cannot explain a specific individual. Budget, usage and emotional expectations together constitute the purchase intention, while product parameters, materials, applicable scenarios and service descriptions provide the basis for judgment. Only when brands explain this information more accurately and completely, can AI have the conditions to match products with specific demands.

Merchants are also in the middle of this change. According to public survey data, 91% of interviewed retail and consumer goods enterprises said they are using or evaluating AI. From product selection, shelf management, to content generation, customer service and store operation, AI has entered multiple scenarios of the consumer and retail industry, covering the daily work of supply, sales and services.

The wide application of AI is already visible, but the business benefits still need to be verified one by one. However, can the saved time bring more transactions? Can faster decision-making bring better profits? Brands need to open up the path from efficiency to revenue, so that the huge return potential of AI can be turned into measurable business results.

Opportunities Unfold in Content, Transactions and Real Life

A product is getting more reasons to be needed.

Price sensitivity and value sensitivity can coexist in the same person. People calculate the unit price of daily necessities, and are willing to pay a premium for interests, emotions and experiences, which can also be choices in the same shopping list. Ocean Engine summarizes this trade-off as "the coexistence of cost-effectiveness and passion".

The value of products is also hidden in small life concerns. Take the currently popular 255ml mini beer as an example, it meets the demand of young women who want to have a light drink but worry that the alcohol content of beer is too high and a large bottle cannot be finished. This new specification combines low-alcohol slight intoxication and lightweight packaging.

A product in a mature category thus corresponds to more specific life needs.

New Demands Also Grow in Content

Some new demands are generated from content. The recent popular trends on Douyin such as "pastel makeup" and "cooling makeup" usually first present a state that the public wants to have, and then bring out the products to achieve it. Consumers pay for the color number and texture, and also choose for the temperament and feeling they bring.

How a cosmetic product enters daily life, and how a dressing style expresses oneself, all become perceptible through specific people and experiences, so content participates in the formation of product value.

AI expands the space for creative attempts. Brands can combine product features and crowd preferences to test different expressions, and then adjust according to content feedback. Douyin's emphasis on high-quality creation and creator ecosystem is exactly about this scarcity: real experience, aesthetics and trust determine which content is worth keeping. AI expands the possibilities of expression, but trade-offs still need to understand people's daily lives.

Creation can be accelerated, but trust still needs to be accumulated through specific people, experiences and expressions.

New Growth Needs to Be Found in Specific Scenarios

In the transaction scenario, the emergence of these opportunities will be more obvious.

On the Douyin e-commerce platform, the supply and demand of content and products are growing at an accelerated pace, and the consumer group is also showing changes of "younger age, higher unit price, and more diversified demands".

During this year's 618 shopping festival, Douyin e-commerce consumer coupons drove the number of merchants whose live transaction volume exceeded 1 million yuan to increase by 152% year-on-year, and nearly 30,000 new merchants participated in the 618 promotion for the first time and achieved transaction volume of over 1 million yuan. The overall market presents an average perception, but the business of brands takes place in more detailed places.

The entrances for products to be seen are expanding: Hongguo connects short drama users with products such as clothing and daily necessities; AI dialogue assistant also integrates "asking, browsing and purchasing" into one. It is worth noting that the relevant data of the AI dialogue assistant is gradually connected with the back end of Douyin Store. Behind the same growth figure, there may be a rearrangement of crowd flow and product structure. AI's understanding and analysis of information is helping merchants understand the changes in the entrance, enabling brands to identify and seize consumption trends earlier.

Beyond its huge influence on marketing touchpoints, AI can also help Douyin e-commerce merchants a lot in content interaction and business operation. From AI live background, AI co-host to AI customer service and operation diagnosis, AI tools have gone deep into the whole link of e-commerce operation, intelligently driving the improvement of merchant personnel efficiency.

Douyin e-commerce observes high-quality content, good products, favorable prices and sound business together, turning scattered consumption demands, life preferences, brand favor and other factors into new decodable opportunities for business growth.

New Scenarios, Experience Catches Unfinished Choices

Beyond the screen, local life services are still changing the completion mode of a business. Douyin Local Life summarizes offline shopping as a combination of products, services and emotional experience. The interest brought by online content needs to be fulfilled in physical stores.

After all, when consumers step into the store, their demands are often not yet finalized. Makeup videos show the makeup look, while in-store trial helps consumers judge the color, texture and using experience. People who originally only wanted to buy a single product may also find new demands in the service.

In the business ideas shared by Ocean Engine, high-quality content helps products be seen, search provides basis for active comparison, and online transactions and in-store experience undertake different demands. Search expresses concerns, content reflects interests, and purchase and in-store behaviors test attractiveness. Only by connecting these signals can brands continuously revise their understanding of crowds and products.

The opportunities in the three fields eventually need to be continuously operated in the same business. AI enables demand insight to enter creativity and product selection earlier, and allows transaction and in-store feedback to continue to participate in the adjustment of products and services. The change of these capabilities, including understanding demands, shaping value and organizing supply, constitutes the new quality productivity of consumer brands in the AI era.

This requires the support of internal business operation of the enterprise, which is exactly where the problems start to become more difficult.

Cross the Time Difference from Technology to Growth

The industrial value of technological revolution has a time difference.

After studying previous technological revolutions, Carlota Perez put forward a very interesting judgment: the industrial value of technological revolution usually does not appear in the installation period, but in the deployment period. That is the stage when technology is no longer discussed separately as a novelty, but seeps back into old industries and reorganizes their operation modes.

This rule is still operating in the AI era. The "Enterprise AI Practice Manual" released by Stanford Digital Economy Lab shows that among the most difficult challenges mentioned by respondents, 77% involve change management, data quality and process redesign. Even in projects that have achieved results, the adjustment of business methods takes up a lot of work.

Crossing this time difference requires reorganizing the operation itself.

In the same advertising campaign, the delivery specialist pays attention to materials and return on investment, the live streaming team pays attention to the number of sessions, and the management pays attention to profit and inventory. The data of all parties may be accurate, but combined they may not be enough to support the same decision, which requires stepping out of the vision of a single role.

Ocean Engine summarizes this set of requirements as context connectivity, quality delivery and man-machine responsibility division.

The first problem to be solved is the context of operation and marketing. AI needs to know what the enterprise is pursuing and what constraints it is facing, so that its judgment can be practical.

The Ocean AI Workbench is designed to solve this problem. With the authorization of the enterprise, business objectives, business facts, marketing actions and internal knowledge are connected into the same continuously updated context. AI can see the origin and boundary of each action, and the team does not need to re-explain the background and check the caliber in each round of collaboration.

Apart from data, knowledge that interprets data is also needed. Industry knowledge graphs and methodologies precipitated by service providers bring category rules, creative experience and delivery intuition into judgment; they enter the workbench in the form of Skills, becoming capabilities that can be called in daily operations.

The full panorama of business and professional knowledge together limit the credible range of a suggestion, and also determine how far the subsequent execution can go.

This set of capabilities is becoming an entry point for brands to reshape their business operation links.

The first batch of co-built customers with Ocean Engine have applied this set of capabilities to product opportunity insight. One of the enterprises shortened the output time of opportunity reports from 7 days of manual work to 20 minutes.

Opportunity insight is only one part of it. The Ocean AI Workbench is coordinated by "Ocean Partner" with five experts, who are responsible for opportunity insight, creative production, live streaming operation, advertising delivery and data analysis respectively. They share the same context around the same business goal, collaborate on analysis and execution, and then adjust strategies according to the results. One insight can then continuously enter the process of creativity, delivery and review.

On this basis, the brand's business records and practical experience will also be continuously precipitated, becoming the basis for the next round of judgment and execution.

The creative end also follows a similar direction. Ocean Engine positions Jichuang as "AIGC creative production and delivery platform". Jichuang 2.0 links opportunity discovery, material generation, Agent video production and review & delivery, and continuously optimizes production by using brand materials and effect feedback. Therefore, creativity can be iterated along the business objectives. In addition, the responsibilities of people need to be clarified accordingly. Brands set goals, define boundaries, and check the creative direction and key execution nodes. The Ocean AI Workbench supports localized deployment, key actions require manual confirmation, and the capabilities integrated into business operation also comply with the enterprise's authorization and responsibility division rules.

Therefore, after AI reshapes business operations, brands may need a new account book. Putting input, transaction and profit into the same account book makes the help of AI to business verifiable. Only by tracking specific actions and results can brands judge whether the saved time has been converted into incremental growth and where the growth comes from.

It can be seen that Ocean Engine is organizing these scattered capabilities into AI business productivity that brands can directly use, helping brands quickly go through the transformation period of AI practice. When AI starts to reorganize business operation and marketing, the time difference between technology and growth can be shortened.

Shift Moment

The time difference will eventually be eliminated — it only gives some people the time to start earlier.

When consumers make decisions in a new way, enterprises must also run their business in a new way. AI is reshaping the organization mode of business operation and marketing: brands need to deal with more entrances, crowds and scenarios at the same time, and the complexity of business operation has risen to an unprecedented level.

But the essence has never changed — when consumers type their demands in the dialog box, every promise in the answer must finally be fulfilled in products and services.

The unique value of Ocean Engine lies in this. It connects Douyin's content ecosystem, e-commerce transactions and local life service scenarios with large models, data capabilities, industry knowledge graphs and reusable application skills, and finally precipitates them into judgment and execution capabilities that brands can directly call.

Facing the increasingly complex business environment, Ocean Engine integrates demand understanding, organization and execution, and benefit verification into the same capability system to support brands to continuously optimize their business. As a result, AI has evolved from an auxiliary tool for individual positions to a productivity that runs through the whole link of business operation and marketing — this not only opens up a new growth path for consumer brands, but also brings the value judgment of AI back to the business itself.

This is exactly the core proposition put forward by the 2026 CAEG Ocean Engine Consumer Goods AI Growth Summit: when AI crosses the qualitative change point, how can the consumer goods industry turn every technological breakthrough into tangible business growth.