Why Your “AI” Company Isn't Really (and Shouldn’t Be) an AI Company

I’ve met with and advised a myriad of entrepreneurs from around the world who, since the beginning of the year, have been riding the wave of the AI revolution. Many of these entrepreneurs are first-time founders. As they create their product and growth strategies and reach out to investors across the innovation ecosystem, I’ve noticed a major trend. 

When it comes to both investors and their ideal client profiles (ICPs), these entrepreneurs are positioning their companies as AI companies. While such a positioning might be valuable to secure investments, I believe that a myopic focus on AI as the go-to-market strategy is not only misguided, it could actually be damaging when selling to your client/customers.

Who counts as an AI company?

To clarify, I define Artificial Intelligence (AI) as the branch of computer science that focuses on creating systems or machines capable of performing tasks that typically require human intelligence. While these tasks include reasoning, learning, problem-solving, language understanding, and decision-making, they still require a human user to prompt responses to generate content/image/video, note taking, etc. Additionally, creating foundational large language models (LLM) from scratch in order to start a company requires a combination of comprehensive and extensive data, significant computational resources, specialized expertise, and a multi-stage development process. 

In other words, most companies that are leveraging AI, instead of building one from scratch, are relying on an underlying model for their LLM needs. The biggest players in the LLM market include Google, ChatGPT, Microsoft, and Meta, while smaller regional players provide services and models for startups looking to build tools off their foundational models. I would argue that only those companies that are supplying LLM work are true AI companies.

Public perceptions of technology and AI in the USA

Sure, you can position yourself and your company as an AI company for investors, but here is why positioning yourself solely as an AI company could backfire when you’re going to market. After all, knowing how AI is perceived in the United States is fundamental for understanding your customers' needs. (For those who aren’t interested in facts and figures and want to understand what this means, the TLDR is: Americans don’t really understand technology in the best of times. When it comes to AI, most Americans are absolutely clueless and actually may be scared of how it may affect their jobs and economic security.

For Silicon Valley, the features of AI are hailed as promising, advantageous, and value driven. By contrast, outside demographic sectors are not fully apprised of AI’s potential benefits, and the vast majority of Americans do not stay abreast of AI. Thus, in the eyes of the general public, AI might appear opulent at best or an existential threat at worst. Let’s consider the likely underlying contexts for postulating this disparity in AI proficiency between Silicon Valley and the rest of the country. 

First, the findings of a 2023 survey on U.S. adult skills conducted by the Organisation for Economic Co-operation and Development (OECD) provide insights on the predominant literacy and numeracy competencies of the American public :

• Average literacy score: 258 (close to OECD average)
• Average numeracy score: 249 (below OECD average)
• 28% of U.S. adults scored at Level 1 or below in literacy (OECD average: 26%)
• 34% of U.S. adults scored at Level 1 or below in numeracy (OECD average: 25%)

Normally, these figures are used for understanding how a population comprehends written information and how they are able to solve complex tasks using numbers. Given that computer literacy involves both reading and writing comprehension and arithmetic cognitive skills, we can extrapolate these findings to conclude that, while most adults perform moderately in basic literacy tasks, the figures suggest a lag in numeracy and adaptive problem solving, including digital/problem-solving skills.

Indeed, this 2019 Pew Research Center survey on American digital literacy found that, among U.S. adults who completed a ten-question digital-knowledge quiz, the median number of correct answers was 4. Only 20% answered 7 or more questions correctly, and just 2% achieved a perfect score. Most technology users in the United States do not comprehensively know how computers (or technology) functions. Rather, their knowledge is sufficient enough to use technology as a tool to help them in their job. It is also important to note that these metrics aren’t representative of all dimensions of computer literacy.

While the United States is still the cradle of tech innovation, the innovation economy prevails within a highly sequestered segment of the economy and is also geographically circumscribed to cities and states with the highest GDP in the U.S. Thus, American literacy and numeracy competencies, alongside digital literacy, are just one factor among others.

Viability and execution are additional nuances for founders to consider as they’re creating their go-to-market strategy. For example, the majority of businesses that could greatly benefit from AI would inevitably also encounter some of the biggest challenges regarding technological adoption because they themselves are not tech companies. To put this into context, the sector with the largest share of U.S. output last year was manufacturing, accounting for 14.2% of total output in 2024. According to the same report, the private health care & social assistance sector employed about 22,527,400 people, retail trade approximately 15,532,000 people, and accommodation and food services employed roughly 14,195,800 people in 2024. Collectively, these industries comprise 29.8% of U.S. labor, and all are mostly small-or medium-sized businesses that probably do not have discernment over how precisely AI could help improve their businesses.

Furthermore, many workers in the aforementioned industries see AI as a threat to their job security. This October was the worst October for layoff announcements since 2003, as reported by Challenger, Gray, & Christmas. The report cites AI adoption as one of the reasons for the layoffs. Alongside the precarities posed by the current presidential administration’s economic policies, companies are forced to reassess employment roles and general spending to put cash back in the coffers. For industries that struggle with labor shortages, Artificial Intelligence that replaces workers could be beneficial. However, for certain American workers, the fear of being stripped of one’s job by AI is very real.

The best summary about U.S. public perceptions of AI is outlined in this recent Pew Research Center study, conducted in September of this year. 95% of adults said that they have heard just “a little” about AI versus only 47% who said “a lot.” When these same respondents were asked whether AI’s effects on society will be positive or negative, only 26% of respondents said that the impacts would be positive. A staggering 47% of respondents thought that AI would have detrimental effects. Thus, it’s no wonder why there is a gap in AI proficiency as well as negative perceptions of AI when comparing the wider public to Silicon Valley.

Cool, so why does this matter to me or my company?

Understanding and empathizing with your customers is foundational in any go-to-market strategy. By placing the client/customer first, aspiring entrepreneurs can make better decisions for their businesses when positioning their products and services when going to market. Tailored messaging built with empathy, after all, is often the difference between a positive and negative outcome when you’re selling a product.

As a case study, I recently met with a company developing a scribe for the automotive repair industry. SMBs in this sector typically have to do a walk-around with a customer, take down their concerns, and create an invoice outlining the suggested repairs without having to type a single word. This particular company uses customized LLMs and has a keen understanding of the vehicle repair process in the US. However, the product is simply a synthesis of an automatic invoicer and note taker. 

Pushing AI as the cornerstone feature of this product may fall on deaf ears within the automotive repair industry. I have no doubt that, as this company takes this idea to market and the product becomes entrenched within the automotive industry, it will develop product features such as CRM integration, automatic diagnostics, and other very powerful features. Yet, the primary value added for a product like this is not simply “AI.” Rather, it is something more valuable, temporal capital, not just for the car customer but for the automotive technician/mechanic evaluating the car repairs.

My advice for this company: “do not refer to yourselves as an AI company when creating your go-to-market strategy. Instead, design marketing materials and outreach that distinguishes your efficiency.”

Working hand in hand with the team, I implemented this human-centered messaging, and the results have been like night and day, especially in parts of the country in which the tech industry is not always well-received. Re-positioning the company as an invoicing and customer-intake application helped the sales team achieve 50% more leads, and many more automotive repair stations adopted their products from organic referrals. The company still has significant room for growth, but the early results of this revamped campaign are certainly promising and A/B testing on messaging is ongoing to ensure the most resonant market positioning is identified.

The legacy of human-centered design

It is easy for those of us who work in the innovation economy to assume that most people understand the complexities and subtleties of the products we create. However, a surgeon, just like a car mechanic, has built their career tailoring resolutions to problems that are unique to his or her patients or customers. If your professional training is specialized, the biggest value-add to your profession are ones that allow your business to run more smoothly—whether that be in the form of efficiency or temporal capital.

The only way to identify the best approaches to sell to these types of clients is by taking a step back, understanding their pain points, and demonstrating how your company can solve that problem, and solve it with empathy. Computers, LLMs, and software can make our lives easier by lowering the inherent friction within our services. What distinguishes a great experience from a mediocre one is the human connection that companies create.

Advertising a product or service as being more efficient solely because of its AI features is not just lazy; it deprives the company of the opportunity to build a human connection and really understand exactly how a potential ICP can gain value from said company’s product. Moreover, the “AI” moniker may not even be as impactful—if at all—as those who are ingrained in the tech industry tend to perceive it to be. 

As such, I think that early-stage founders can do a better job in recognizing that their go-to-market plan should be more than just, for example, “we’re AI for the automotive industry.” Putting in effort and being perspicacious about your go-to-market strategy can mean the difference between a “solution in search of a problem” vs. a successful sales meeting.

Learn how to grow your business and be empowered, schedule a meeting today!