The modern boardroom has a new mandatory vocabulary. A few years ago, artificial intelligence was a specialized topic reserved for research labs and the engineering hubs of Mountain View or Seattle. Today, the linguistic contagion has reached the local deli. It is no longer enough for a company to be profitable or efficient; to capture the imagination of the public markets, a business must signal that it is part of the intelligence revolution. This shift is visible not just in marketing slogans, but in the most formal and legally binding documents a company can produce.

The S-1 Signal and the AI Count

Jersey Mike's, the rapidly expanding sandwich franchise, recently signaled its intentions to enter the public market. In the process, the company filed its S-1 registration statement, the critical document used to disclose business models, financial health, and potential risk factors to prospective investors. Upon closer inspection of the text, a striking pattern emerges: the terms artificial intelligence and AI appear exactly 22 times throughout the document. For a company whose primary product is a submarine sandwich, the frequency of these mentions suggests a strategic attempt to align the brand with the current investment zeitgeist.

However, the quantitative presence of the term does not match the qualitative depth of the implementation. While the word AI appears 22 times, the actual technical substance is nearly non-existent. In the risk disclosure section, the company includes a brief, generic statement noting that it has begun to use AI technology in its business. There are no descriptions of specific LLM integrations, no mentions of proprietary machine learning models for supply chain optimization, and no data on how these tools have improved margins. The document treats AI less as a functional tool and more as a necessary keyword to satisfy the appetite of institutional investors who are currently hunting for any exposure to the generative AI wave.

This obsession with the term AI stands in stark contrast to the company's mentions of more traditional digital infrastructure. The S-1 mentions data 112 times and software 52 times. For a franchise headquarters managing a vast network of stores, these numbers are entirely logical. Tracking real-time sales, managing inventory across diverse geographies, and maintaining franchise compliance require robust software and data pipelines. These are the foundational elements of modern retail operations, yet they are treated as background noise compared to the 22 mentions of AI, which serve as the high-visibility lure for the IPO.

The Gap Between Hype and Operational Reality

This discrepancy reveals a growing tension in the corporate world: the difference between operational software and AI hype. When a company mentions data 112 times, it is describing how the business actually functions. When it mentions AI 22 times without explaining the use case, it is describing how it wants the market to perceive its future. The danger arises when companies mistake the label of AI for the utility of the technology. In the food and beverage industry, the margin for error in automation is razor-thin, and the cost of a failed AI implementation can be immediate and physical.

Starbucks provides a cautionary tale in this regard. The coffee giant recently attempted to deploy an AI-driven inventory management tool designed to automate the ordering of milk and coffee beans. The goal was efficiency, but the result was a failure in basic arithmetic. The AI struggled with the fundamental task of counting, leading to systemic errors in stock levels. In a retail environment, an AI that cannot count is not an innovation; it is a liability. Under-ordering leads to out-of-stock crises that alienate customers, while over-ordering leads to massive food waste and eroded margins. Starbucks eventually scrapped the tool, proving that a sophisticated label cannot compensate for a lack of basic reliability.

For Jersey Mike's, the 22 mentions of AI in an IPO filing represent a gamble on perception. By inserting the term into the S-1, the company is attempting to bridge the gap between a traditional brick-and-mortar business and a tech-forward enterprise. But as the Starbucks example demonstrates, the distance between mentioning AI and successfully deploying it is vast. Investors are increasingly beginning to distinguish between companies that use AI to solve a specific, measurable problem and those that use AI as a decorative wrapper to inflate their valuation.

True innovation in the franchise space does not come from the frequency of a keyword in a legal filing, but from the ability to solve the friction of the physical world. Whether it is optimizing the cold chain or predicting foot traffic, the value lies in the result, not the terminology. The current trend of AI-washing in IPO documents creates a bubble of expectation that the actual technology often fails to meet.

The market will eventually stop counting the number of times a company says AI and start counting the actual value the technology creates.