2026 Set for Intense Competition in AI Token Market

As artificial intelligence (AI) continues to evolve, experts predict that 2026 will witness significant competition among AI token providers. This year could mark a pivotal transition as companies vie for market share in an industry that has thus far seen rapid growth without substantial rivalry. Insights from Mike Finley, Co-Founder of StellarIQ, shed light on this emerging landscape, where the fundamental units of AI processing—tokens—will play a crucial role.

Understanding AI Tokens and Their Impact

A token in the AI context refers to a unit of data used for processing and generating outputs. Input tokens serve as the basis for processing, while output tokens, which are typically priced at about four times the cost of input tokens, represent the generated data. The size of a text token can vary significantly, from a single character to an entire word, influenced by the specific language model and its training.

Finley emphasizes that tracking token usage may offer clearer insights into AI demand than traditional revenue metrics. He foresees a shift where major AI providers, having enjoyed substantial funding and high valuations, will now focus on capturing market share. “The demand for their services has grown exponentially so far, but 2026 will see providers catch up and begin competing for share rather than growing freely into green-fields,” Finley stated. This competitive landscape will require companies to differentiate their offerings to survive.

Emerging Opportunities in AI Modalities

As AI technology advances, Finley identifies a significant opportunity in non-text modalities, such as audio and video, particularly for real-time applications. He notes, “This is a massive opportunity that, so far, is owned by OpenAI. Unlike text, these modalities replace human time second-for-second, making ROI instantly clear when it works.” The ability to interact through voice in real time, as opposed to simply reading text, highlights the potential for AI applications in everyday scenarios.

Companies like Microsoft are also enhancing integration capabilities, making it easier for developers to adopt AI solutions across various software platforms. This trend aims to ensure that token utilization expands across more applications, driving further adoption.

Finley also discusses the anticipated growth of AI on smaller devices. With a shift towards edge computing, AI applications will require lower power consumption and reduced latency. He predicts, “Next year, we’ll see booming use of AI on smaller devices, demanding far lower power than AI on larger form factors.” This transition will likely lead to significant device replacements over the next five years, affecting everything from televisions to home appliances.

While the potential for smaller, more efficient AI is exciting, Finley cautions that this does not imply a reduction in the costs associated with developing advanced models. The creation of sophisticated AI systems will still require extensive resources, which will then be adapted for use in edge devices.

Finley envisions a future where everyday items are equipped with advanced AI capabilities. He posits, “Cars coming out in 2027 will be able to talk to EMS when they’re in a wreck. Washing machines will analyze what’s in the load and set themselves. Ring doorbells will chat with visitors to determine who they are and what they’re up to.”

The competitive landscape in AI tokens is poised for transformation as companies adapt to these trends. As providers refine their offerings and explore new modalities, the race for market dominance will intensify, paving the way for innovative applications that could redefine how we interact with technology.