a16z Year-End Review: In Consumer AI, the Winner Takes All. The Opportunities in 2026 Lie in These 3 Areas

In 2025, consumer-grade AI witnessed unprecedented popularity.

OpenAI updated its products dozens of times a year, turning ChatGPT into a super entry point: integrating functions like dialogue, image generation, group chat, and Sora video all into one app. Google, Anthropic, and Grok are also vying for entry points, while Nano Banana and Veo have been trending on the internet.

However, an investor from a16z pointed out the reality with one sentence:

There are many product releases, but few can truly change users' habits.

Let's look at the data: ChatGPT has 800 - 900 million weekly active users, while Gemini only reaches 30% - 40% of that figure; less than 10% of users have visited multiple platforms, and only 9% are willing to pay for multiple services. Most people only use one AI tool, indicating a winner-takes-all situation.

Does this mean there's no opportunity for AI startups in 2026? a16z says no. The key lies not in the model but in these three aspects.

Create successful products: popular styles and multi-modal approaches;

Attract users: target professional users in niche markets;

Avoid competition with tech giants: bypass computing power constraints and organizational blind spots.

Each aspect doesn't rely on model capabilities but on products that understand users better.

Aspect 1 | Lower the creation threshold with popular styles

ChatGPT secured its entry point through dialogue, but what users are truly addicted to is not chatting but creation.

Justine Moore, a partner at a16z, recalled 2025 and said that the most viral AI products this year were not new models but certain images or videos that inspired people to create their own.

She mentioned two examples: OpenAI's Ghibli-style images and Google's Nano Banana. Their common feature is a distinct style that allows users to create something instantly.

This type of product doesn't make you think about what you can create but gives you a starting point. All you need to do is click in, change a name or a character, and you can post it on social media the next second.

a16z investors call this "lowering the threshold with templates": relying on good design styles rather than model capabilities to eliminate the need for users to figure out where to start. For example:

ChatGPT's image page no longer shows a blank input box but actively displays examples such as holiday cards, sketch portraits, and animal costumes;

Startups like Krea allow users to save character and style materials for direct reuse next time;

The difficulty of this type of product lies not in technology but in aesthetics, composition, and cultural sense. Another partner, Bryan Kim, summarized it in one sentence:

Styles are more memorable than technology.

This summary deserves attention. Since many startups can't compete in underlying models, if you can create a painting style, video gameplay, or character template that users can use right away before ChatGPT, you can capture users' attention.

This type of popular template style is also becoming more intelligent.

Nano Banana Pro can watch a video and automatically generate infographics, market maps, and even match appropriate icons and color schemes; Claude also uses the artifacts function to allow users to edit the style and structure of the generated content, rather than just viewing the results, but participating in the improvement process.

Therefore, they predict that the next step for image/video models is not to be more realistic but to allow users to freely change styles. It's not about replacing creation but redefining how to start creating.

Aspect 2 | Connect creation paths with multi-modal capabilities

AI functions such as image and video generation seem to be just about creating content, but a16z investors see greater potential: when multi-modal capabilities are combined, these functions may restructure the entire creation process and even become new product entry points.

Justine said in a roundtable discussion that half of the content on social media she sees is already AI-generated videos, especially Veo and Sora, which look like real shots and even convey emotions through camera language. These contents went viral because they are no longer simple image-to-image generation.

They can understand story structures, maintain character consistency, and even imitate rhythms and styles.

More importantly, they can interact.

Bryan gave an example: "I uploaded a YouTube video and asked the model to draw an explanatory diagram for me, and it did. When the input is a video, the output is a chart; when the input is a brand website link, the output is a complete advertising proposal."

This is what they call multi-modal, which can process any type of input and generate any type of output.

In the past, AI tools were like assistants answering questions, but now they are becoming creation tools for building products. You can input old photos, web pages, and voice notes and get images, short videos, slides, copywriting, and even ready-to-publish content.

Google's internal experimental product Pamelli is a typical example. It can automatically extract website content, identify brand positioning, consider the tone of advertising, color matching, and target audience, and directly generate three sets of complete marketing materials.

Partner Olivia Moore said: This is not just providing a solution but directly delivering a finished product.

This is the shortest distance between large models and users. When a tool allows users to turn an idea into a finished product without switching between multiple apps, it naturally becomes the starting point of the workflow.

a16z investors also pointed out that this ability is breaking the boundaries of traditional content creation.

Claude has long supported mixed input of images and text, and Sora and Veo are also working on video editing with voice prompts. These are all great, but what ultimately determines whether users will stay is whether AI can help them get things done.

They believe that the highlight in 2026 may not be new models but new combinations.

Whoever can make users worry less, switch less, and get results directly can create a real product.

Aspect 3 | Target professional users in niche markets

a16z investors mentioned an unexpected phenomenon: users of consumer-grade AI products are becoming more willing to spend money as they use the products more.

This means that some users not only subscribe but also actively purchase more features and keep paying.

Who are paying these fees? Not ordinary people trying it out, but those who truly use AI as a tool.

Both Olivia and Bryan mentioned that this group of professional consumers has been the fastest-growing group in the past year. They are not researchers or engineers but those who are willing to use AI in their daily workflows: operators, editors, freelancers, and creators.

These users are using AI to work. What they commonly use is not the basic version of ChatGPT but:

Perplexity's Comet browser: while searching for information, it allows AI to automatically organize it into notes or charts;

11 Labs Reader: converts articles you want to read into voice, enabling you to consume information during your commute;

Granola: automatically records meetings and organizes historical content to prepare for the next meeting;

Cursor: directly invokes AI in the code editor and debugs the code right after writing;

Gamma: directly generates slides from documents, allowing you to modify and adjust them repeatedly without opening PPT.

The common feature of these tools is that they have memory. AI will look at what you've said and done in the past and then continue to work.

Olivia mentioned that she tried ChatGPT's connector function, which allows the model to read calendars, emails, and files, automatically find useful materials within a certain period, summarize ideas, and provide suggestions. Although it's not stable yet, she believes that once this type of product runs smoothly, users won't want to switch to other AIs.

This scenario has a key feature: It's used every day.

Bryan said that he currently uses ChatGPT about 24 times a week on average, which means three to four times a day. In contrast, most tool users only open the app 1 - 2 times a week. Daily use indicates that it has truly become part of the workflow.

Therefore, they believe that competing for this group of professional users is the key battlefield for consumer AI in the next stage. The goal of products is no longer to get more downloads but to keep users, making them high-frequency, in-depth, and continuous-paying users.

Once this group of professional users becomes dependent on a tool, the switching cost is extremely high.

Section 4 | Tech giants are faster, while startups are bolder

Since it's so difficult to attract professional users and they have high stickiness, who has more opportunities, tech giants or startups?

This year, tech giants have been updating their products rapidly and releasing more products.

OpenAI launched Sora, group chat, Pulse, image tools, the browser Atlas, and an app store;

Google launched a large number of experimental features among Gemini, Labs, and AI Studio;

Anthropic launched three development paths for Claude: artifacts, skills, and Claude Code.

Justine said: Big companies have tried dozens of directions in the consumer market, but few products have survived.

On the contrary, some AI startups, although with simple functions, have high user recognition.

The most typical example is the Comet browser, whose daily active users and retention rate are higher than ChatGPT's Atlas. It was repeatedly used by early users even when its functions were incomplete. Another example is Lovable, which focuses on generating applications. It doesn't try to do everything but specializes in a few common applications, making each one very user-friendly.

These products have a common feature: they focus on a specific scenario and go deep and specific.

The reason is simple: Tech giants are competing for entry points, while startups are competing for directions. The former need to serve hundreds of millions of users, ensure compliance, and balance the platform; the latter only want to capture a high-frequency small scenario and perfect it.

Moreover, big companies have an invisible burden: computing power allocation.

Justine mentioned that companies like OpenAI and Google have to constantly balance between training new models and supporting user usage. Once an image application becomes too popular, the inference resources in the background will be quickly consumed, which may delay the training plan for the next-generation large model.

Startups don't have this problem. They can flexibly choose Claude, GPT, Gemini, or even local models to serve one goal: Give users what they want at this moment.

Bryan said:

"The more you focus on the application layer, the less you need to confront tech giants head-on. As long as you create a truly useful product, users will naturally stay."

This is why a16z is particularly optimistic about the new generation of entrepreneurial opportunities in consumer AI: not to recreate another ChatGPT but to create a set of front-end products that can be implemented, reused, and have user stickiness on the premise that model capabilities are sufficient.

Instead of trying to be the next ChatGPT, it's better to do something that ChatGPT can't do well.

Conclusion | In 2026, who can create products users can't live without?

ChatGPT has secured its entry point, and model capabilities are sufficient.

Next, the real opportunity lies not in who has a stronger model but in who can create products that users can't live without.

a16z investors have given three directions:

Provide ready-made styles so that users don't have to start from a blank page;

Connect creation paths so that users can turn ideas into finished products without switching between multiple tools;

Go deep enough to make professional users use the product every day and keep paying.

Tech giants are competing for entry points, while startups can compete for directions. Focus on a specific scenario, go deep and specific. The models belong to tech giants, but it's still uncertain who will own the users.

The product doesn't have to be large but accurate. Now is the time for entrepreneurs to take action.

📮 References:

https://www.youtube.com/watch?v=p4-7x6QiYr0&t=62s

https://a16z.com/state-of-consumer-ai-2025-product-hits-misses-and-whats-next/

https://techcrunch.com/2025/10/06/sam-altman-says-chatgpt-has-hit-800m-weekly-active-users/?utm_source=chatgpt.com

https://a16z.com/state-of-consumer-ai-2025-product-hits-misses-and-whats-next/

https://ir.similarweb.com/news-events/press-releases/detail/138/ai-discovery-surges-similarwebs-2025-generative-ai-report-says?utm_source=chatgpt.com

This article is from the WeChat official account "AI Deep Researcher", author: AI Deep Researcher, published by 36Kr with authorization.