AI on Steroids: Will GPT Store supercharge AI adoption?

The OpenAI GPT store is officially open to ChatGPT Plus, Team and Enterprise users, who now have access to over 3 million versions of ChatGPT created by the GPT Builder community. This staggering library of offerings outshines what mobile giants, Apple and Google started their mobile app stores with — 5001 and 16 thousand2 applications respectively.  

Each GPT in the store has been custom designed to solve a unique problem with special built-in knowledge and prompt-based instructions. For instance, AllTrails is custom GPT for users to find suitable trails for their next hike, ride or run while SellMeThisPen can create second-hand marketplace listings just by analyzing user uploaded pictures.

Since its launch in November 2023, the GPT Builder community has been using the GPT builder tool to customize GPTs using a conversational interface by simply telling it what to do – suggest dinner places, recommend weekend plans, or even help decide what to wear to the office. Tech-savvy folks even have an advanced option to manually tweak and optimise GPTs for hyper-personalised performance.

With a complementary revenue sharing program, individual GPT creators will be paid a percentage of revenue generated based on user engagement. And to build awareness, the store is split into different categories including DALL-E, writing, research, programming, education, lifestyle, and more. It won’t be surprising to see categories like productivity and writing take the early lead in adoption as knowledge workers take full advantage of customised tools for work.  

Rise of AI Marketplaces  

This custom AI store concept is potentially the next big trend — think of a Shopee or Amazon for AI products like chatbots, navigation systems, recommendation algorithms, etc.

It could spur exciting competition against established ecosystem like Apple’s App Store and Google’s Play Store. App Store developers, for instance, generated $1.1 trillion in billings and sales in 20223, which meant even with the recent reduction in App Store fees, Apple was estimated to gross between $70 - $85 billion4.  

While growth is slowing, the opportunity around application marketplaces is largely lucrative and custom AI application marketplaces like the GPT Store hold the potential to disrupt this market, capturing a significant share of the value. With edge AI and 5G's growing reach propelling front-facing AI applications directly onto user devices, the GPT Store and other custom AI platforms are poised to democratize the development and monetization of these powerful tools, unlocking a vast, untapped market.

It could further incentivize an entirely new generation of gig workers and developers who earn a living from sculpting personalized AI companions and training problem-solvers for every facet of our lives. Imagine juggling a custom language tutor, a real-time financial advisor bot, and an AI-powered therapist in a single day – the possibilities are limitless. We can only expect the number of custom GPTs to grow and will increasingly interact with multiple GPTs in a single day, each solving a different task in our lives.  

Startups could also greatly benefit from this marketplace, assembling customised AI solutions to support early operations — automating tasks, analyzing data, and tailoring marketing efforts — all at a fraction of the usual in-house cost. A growing number of startups could also emerge to focus on building domain-specific marketplaces and niche AI chatbots to solve specific business challenges, reshaping the startup landscape as we know it.

Enterprises are increasingly turning to AI marketplace model to democratise AI applications within their teams. Allganize in Japan have an LLM App market serving over 200 corporations with customisable workflow templates powered by LLM. Similarly, AT&T built an AI Feature Store, jointly developed with to distribute development features that data scientists, developers, and engineers need to build and deploy AI models faster.  

Globally, companies are actively exploring how AI can augment their core operations, unlock new growth potential and transform its people capabilities. However, challenges like data bias and lack of explainability loom large when it comes to scaling AI initiatives. Perhaps, future versions of custom GPTs could play a crucial role in tackling these roadblocks, ensuring ethical and responsible AI adoption at scale — the question is who will be the first to build this custom version of an AI for Good GPT?




3Analysis Group