5 Reasons Why You Should NOT Start a ChatGPT-Based Startup

Author(s): Massimiliano Costacurta

Originally published on Towards AI.

Ever since December 2022, it’s been one non-stop AI party with ChatGPT playing the role of the rockstar DJ, spinning beats that everyone can’t help but groove to. If you’re an entrepreneur, a founder, or even just someone with a dream and a spark of ambition, you’ve likely found yourself thinking: “I HAVE to get in on this action!” And honestly, who can blame you? We’re teetering on the brink of a massive tech revolution, one that has the potential to not only reshape existing markets but possibly birth entirely new ones.

When a disruptive force like this enters the scene, it’s only natural for everyone to want a piece of the pie, even when the tech at play is as complex as it is transformative. The allure of opportunity often drowns out the quieter, yet equally important, questions about the implications of the technology and its market impact.

The result of all this hype? We’re seeing a flood of new AI tools and businesses. But let’s be honest, most of the time, these are just new wrappers around this cool new tech (ChatGPT or its image or audio equivalent). They often lack something special to ensure they’ll stick around for the long haul. Now, I’m not here to dampen your enthusiasm about diving into this revolutionary technology. I firmly believe that “trying and doing” is always the best path. Even if you stumble, you’ll pick up valuable lessons for your next venture.

However, sometimes, it’s smart to hit the pause button and take a closer look at your plans. It’s important to make sure your great idea stands a chance in the real world. So, let’s dive into the five most common traps you should try to avoid when planning your ChatGPT/AI startup adventure.

1. You don’t have a use case

This one’s a nightmare for any founder (or product manager). I’ve talked about this before in another article: it’s so easy to fall head over heels in love with cool tech. There’s this quote from Abraham Maslow that pretty much nails it: “When the only tool you have is a hammer, every problem begins to resemble a nail.” Basically, if you’re too focused on the shiny new tool (ChatGPT, in this case), you might start seeing it as the answer to everything. You might even think it can solve problems that aren’t really problems at all!

We’ve seen it happening in the past already. Take the Juicero startup, for example. They made this snazzy high-tech juicer and their own special juice packets. They thought they were about to shake up the world of fresh juice drinking. But they were so excited about their slick $400 juicer, they didn’t stop to ask: “Are we actually solving a real problem here?” Turns out, people were pretty okay with the old way of making fresh juice and didn’t want to pay big bucks for Juicero’s solution. And that was the end of their story.

And remember those startups from the early 2010s that were all about QR codes? They had a tough time because, to be honest, there were quicker and easier ways to get things done. Yes, QR codes made a comeback during the pandemic thanks to the need for no-touch interactions. But honestly, banking on a worldwide crisis to save your business isn’t exactly the brightest plan.

When it comes to startups using ChatGPT, it’s crucial to make sure you’re solving an actual problem. Or are you just dazzled by the idea of AI and natural language processing? Are you building a customer service chatbot because your customers are begging for better service, or just because you think AI chatbots are nifty? Your honest answer to that question could be a make-or-break deal for your business.

2. You don’t have data

Let’s get real here: any AI system, ChatGPT included, is only as smart as the data it’s trained on. So if you don’t have any special data to teach your model with, well, your business idea might not be that much better than anyone else’s. Unique data that others can’t easily copy or get their hands on can really make your startup stand out from the crowd.

Let’s say you want to create a GPT-based tool for financial whizzes. How good this tool is going to heavily depend on its understanding of all the finance stuff: stock market data, financial reports, news, and all the finance lingo. Now, if you can amass that sort of data, you’re onto something truly valuable. That sounds like a fantastic idea, right?

Turns out, someone’s already beaten you to it. And that someone is none other than Bloomberg, one of the big kahunas in the world of finance. In a recent research paper, Bloomberg spilled the beans about its own version of GPT, trained specifically on a wide range of financial data. They’ve got an archive full of financial documents going back 40 years, which comes to a whopping 363 billion token dataset. Add to this a 345 billion token public dataset and you’ve got a training set that’s over 700 billion tokens strong. That’s some serious firepower. And definitely a strong moat.

The big question here isn’t just whether your startup can build a GPT-based tool, but whether it has access to unique, industry-specific data to train the tool effectively. Without this, you might find it hard to make your product stand out from the crowd of AI tools or those built by companies with exclusive data. In other words, data isn’t just an ingredient for your startup — it might be your secret sauce. A smart data strategy can make all the difference and build a solid wall to keep the competition out.

3. You don’t have a market

Getting your GPT-based startup’s unique use case nailed down is super important, but that’s just one side of the coin. The other equally important side is making sure there’s a big enough market out there that’s ready and willing to pay for your product. Even if your product or service is the most innovative thing since sliced bread, without a market willing to fork over cash for it, your startup might have a hard time staying afloat.

There are tons of examples in the tech industry that show how important understanding the market is. But hey, if you don’t get the market quite right, don’t sweat it — you’re in good company. Take Google’s attempt at social media, Google+, for example. They built it to go toe-to-toe with platforms like Facebook, offering a unique and tech-savvy social media experience. The issue was, it wasn’t so much Google’s answer to a clear gap in the market as it was Google’s attempt to crash the social media party. In the end, it couldn’t stand against the network effect that was solidifying its competitors. The network effect — where a platform becomes more valuable the more people use it — had already turned Facebook into the king of social media. People didn’t want to switch platforms because everyone they knew was already on Facebook. On top of that, switching over to a new platform and convincing everyone else to do the same would’ve been a huge pain. So, despite Google having resources coming out of their ears, Google+ didn’t pull in enough users and eventually got shut down because of low user engagement.

So validating your market doesn’t just mean understanding that there are potential customers out there. It also means understanding the dynamics at play in your market. Things like the network effect and switching costs can seriously affect how your product is received. It’s not just about creating an innovative GPT-based product, but also about understanding the lay of the land in your market and making sure there’s a big enough, accessible, and willing market to keep your business growing.

4. You don’t have permission

The world of AI technology is transforming at breakneck speed, and regulations are quickly trying to catch up. Any budding AI startup has to make sure its product is in line with all the rules around privacy and data protection. The market you’re aiming for could define the regulatory challenges you’ll face, and this might abruptly stall your startup’s momentum. It can happen in the blink of an eye.

Just ask the folks in Italy. They were the first Western country to put a stop to ChatGPT because of privacy worries. And that happened overnight. Italy’s data protection authority wondered if OpenAI was playing by the rules of the General Data Protection Regulation (GDPR) and even kicked off an investigation. Eventually, on April 30th, after they addressed all the issues that were raised, OpenAI was able to bring ChatGPT back to Italy. This incident shows how crucial it is for an AI startup to get their heads around the regulatory scene and be ready to adjust to any unexpected shifts.

And there’s no shortage of cases where a change in regulation quickly reshaped the landscape a business was operating in. Look at what happened to the drone industry, for instance. A bunch of drone startups was flying high with pretty laid-back regulations until the Federal Aviation Administration (FAA) in the U.S. tightened things up in 2015. The new rules said pilots had to keep drones in their line of sight, which put a serious damper on drone delivery startups’ plans. All of a sudden, something that was totally legal had a bunch of new restrictions, which threw a curveball at these startups’ business models.

This underlines just how key it is to understand and follow the regulatory environment your startup is operating. It’s super important to get legal advice and be ready to steer your way through the intricate world of regulatory compliance. Ignoring these risks can have serious fallout, like big fines, disruptions to your service, or even your startup going under.

5. You don’t have sustainable differentiation

Building a startup on the backbone of ChatGPT might seem like a hot idea, but it comes with its share of roadblocks when it comes to standing out from the crowd and going the distance. The thing is, ChatGPT is a free game for any entrepreneur or company around the world, which makes it tough to stake your claim to a unique edge. Plus, the field of AI research is moving at lightning speed, so today’s groundbreaking innovation might just be tomorrow’s old news. This all adds up to the need for a solid edge that will stand the test of time.

Furthermore, big tech players like Microsoft, Google, and Meta have deep pockets and they’re not afraid to dig into them to get in on technologies like ChatGPT. They also command considerable influence in the market, and their moves can reshape industry dynamics overnight. So, if your startup’s business model is heavily dependent on leveraging ChatGPT for a particular use case, remember that you’re potentially a single press release away from being rendered irrelevant if one of these tech giants decides to step into your niche. This drives home the importance of securing a defensible edge that extends beyond mere ChatGPT usage. This advantage could take the form of proprietary data, a groundbreaking business model, robust customer relationships, or a unique application of the technology that is hard for others to replicate.

Establishing a durable startup in the AI sphere requires more than merely capitalizing on cutting-edge technologies. You must also identify unique methods of providing value, distinguishing your product, and securing a substantial market share. The key lies in developing an offering that is distinctive, valuable, and challenging to replicate. This will equip your startup to withstand rapid technological advancements and potential threats from the tech giants.

Do you know of any recent AI startups that seem to be on track to build a business that could go the distance? I’d love to hear about them in the comments!

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Published via Towards AI