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

Consumers are starting to write their uncategorizable daily lives into a single dialog box.

"Limited budget, for parents, hope it is useful, and want to show care." The selection of a gift can start with descriptions of several such phrases. Before the product name even appears, consumers first present their budget, recipient, scenario and emotional expectations, and AI will help them compare, eliminate unsuitable options and gradually find the right choice.

Screening, comparison and ranking, the mental work that used to be completed by consumers themselves, is now being 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.

There is another more subtle mismatch. AI has been applied 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 AI participating in analysis and execution, both ends are shifting at the same time. Between the progress of technology and the progress of operation, there are gaps in data, process and organization. This gap is the time difference of growth.

How to convert the progress of technology into the progress of business? This is also the question that the 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 interest, "searching" enables people to take the initiative to compare and verify, and "inquiring" accommodates unformed demands, allowing consumers to directly ask AI for judgment.

The three ways exist at the same time, and follow one after another in a single consumption process. Consumers can first be impressed 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". 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 will use AI search to assist consumption decisions. This means that users are spending more time on AI, and demand expression is also extending 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, use scenario and emotional expectation together constitute the purchase intention, while product parameters, materials, applicable scenarios and service descriptions provide the basis for judgment. Only when brands introduce this information more accurately and completely can AI connect 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, and the operational benefits still need to be verified item by item. However, can the saved time bring more transactions? Can faster decision-making leave better profits? Brands need to open up the path from efficiency to revenue, so as to turn the huge potential return of AI into measurable operational 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 popular 255ml mini beer as an example. It corresponds to the demand of young women who want to drink moderately, but worry that the beer has a high alcohol content and a large bottle cannot be finished. This new specification combines low-alcohol slight intoxication with lightweight packaging.

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

New Demands Are Also Growing in Content

Some new demands are generated from content. Trends such as "pink makeup" and "cooling makeup" that are very popular on Douyin recently often 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 the temperament and feeling they bring.

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

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

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

New Growth Needs to Be Found in Specific Scenarios

In the transaction field, 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 also shows changes of "younger age, higher consumption and more diversity".

During this year's 618 shopping festival, Douyin e-commerce consumption coupons drove the number of merchants with live broadcast transaction volume exceeding 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 with transaction volume exceeding 1 million yuan. The overall market presents an average perception, but the business of brands occurs in more subtle 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 "inquiring, browsing and purchasing" into one. It is worth noting that the relevant data of AI dialogue assistant is gradually connected to the back end of Douyin Store. Behind the same growth figure may be the rearrangement of crowd flow and product structure. AI's understanding and analysis of information is helping merchants understand the changes in the entrances, enabling brands to identify and grasp consumption trends earlier.

Beyond its huge influence on marketing touchpoints, AI can also help merchants on Douyin e-commerce do many things in content interaction and operation. From AI live broadcast 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 staff efficiency.

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

New Scenarios, Experience Catches Unfinished Choices

Beyond the screen, local life services are still changing the completion way of a business. Douyin Local Life summarizes offline shopping as a combination of products, services and emotional experiences. 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 finalized. Makeup videos show makeup looks, while in-store trials help consumers judge the color, texture and use experience. People who originally only wanted to buy a single product may also find new demands in the service process.

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

Opportunities in the three fields ultimately need to be continuously operated in the same business. AI enables demand insight to enter creativity and product selection earlier, so that transaction and in-store feedback can continue to participate in the adjustment of products and services. The changes in these capabilities of understanding demands, shaping value and organizing supply constitute the new quality productivity of consumer brands in the AI era.

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

Cross the Time Difference from Technology to Growth

There is a time difference in the industrial value of technological revolution.

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 reset. Even in projects that have achieved results, the adjustment of operation modes takes up a lot of work.

Crossing this time difference requires reorganizing the operation itself.

In the same advertising campaign, the delivery staff pays attention to the materials and return on investment, the live broadcast team pays attention to the sessions, and the management pays attention to profits and inventory. The data of all parties may be accurate, but they are not enough to support the same decision when combined, so it is necessary to step out of the vision of a single role.

Ocean Engine summarizes this set of requirements as context connection, quality delivery and human-AI responsibility division.

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

The Ocean AI Workbench is designed to solve this problem. With enterprise authorization, 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 standard in each round of collaboration.

In addition to data, knowledge that interprets data is also needed. Industry knowledge graphs and methodologies accumulated 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 business panorama and professional knowledge jointly limit the credible range of a suggestion, and also determine how far the subsequent execution can go.

This set of capabilities is becoming a starting point for the reshaping of brand 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 broadcast operation, advertising delivery and data analysis respectively. They share the context around the same business objective, collaborate on analysis and execution, and then adjust strategies according to the results. In this way, one round of insight can continuously enter the process of creativity, delivery and review.

On this basis, the brand's operation 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 iterate along the business objectives. In addition, the responsibilities of people need to be clarified accordingly. Brands set goals, set boundaries, and check the creative direction and key execution nodes. The Ocean AI Workbench supports localized deployment, key actions require manual confirmation, and capabilities entering operation must also comply with the enterprise's authorization and responsibility division rules.

Therefore, after AI reshapes the operation, brands may need a new account book. Putting investment, transaction and profit into the same account book can provide a measurable scale for AI's contribution to business. Only by tracking specific actions and results can brands judge whether the saved time has been converted into increments and where the growth comes from.

It can be seen that Ocean Engine is organizing these scattered capabilities into AI operation productivity that brands can use directly, helping brands quickly go through the transition period of AI practice. AI begins to reorganize operation and marketing, so that 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 operation and marketing: brands need to deal with more entrances, crowds and scenarios at the same time, and the complexity of 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 eventually be fulfilled in products and services.

The unique value of Ocean Engine lies in this. It integrates 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 into judgment and execution capabilities that brands can call directly.

Facing the increasingly complex business environment, Ocean Engine integrates demand understanding, organization and execution, and revenue verification into the same capability system to support brands to continuously optimize their business. As a result, AI has evolved from an auxiliary tool at individual posts to a productivity that runs through the whole link of 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 the consumer goods industry can turn every breakthrough of technology into real business growth.