When the generative AI model ChatGPT was released to the public last year, it sent shock waves through the industry. 

After years of theorizing about how AI would change society, the cat was finally out of the bag. AI was no longer a future “what if” but a present reality that investors and entrepreneurs were eager to capitalize on.

Startups raced to build their companies on the back of large language models. Established tech enterprises like Google rushed to incorporate generative AI into their product roadmaps. Entire business models shifted as executives realized the need to have an “AI strategy” to remain relevant. VCs poured money into AI startups at an unprecedented rate. The public markets bid up the valuations of any company even remotely associated with AI to dizzying heights.

And while we’ve certainly seen some notable successes so far (mostly from the big tech companies, with a smattering of smaller players achieving unicorn status) the initial reality hasn’t quite lived up to the hype. Here at Stage, we’ve seen a sharp increase in the number of companies who are struggling to find their footing in the market after having overhauled their business model or started net-new businesses in the wake of ChatGPT. 

The realization is setting in that simply tacking on a generative AI model does not automatically make a product or service better or more valuable to the public. It turns out, integrating these powerful (but finicky) models in a way that genuinely enhances user experiences and solves new problems for businesses is much more difficult than originally anticipated.

Tip: Ask yourself if your idea needs to be an entirely business or a feature. This will help you better allocate resources and avoid unnecessary risk to ensure that your project has the best chance of success.

The result has been a painful correction in generative AI markets. Startups have had to sharply rein in their ambitions, lay off staff, and struggle to gain traction. Public companies have had to scale back their AI initiatives in the face of disappointed investors and customers. Across the board, experiments that only six months ago were heralded as “the next big thing” are being ruthlessly curtailed or scrapped altogether.

Added to that are the many challenges posed by AI, like the fact that language models often make stuff up, display strong biases, and can easily be hacked. Companies will need to have a plan to deal with these issues to scale successfully.

Tip: Focus on integrating the advancements in AI with the core strengths of your existing business. You have the advantage of knowing your business; the rest of the world does not. Use AI to augment your existing efforts instead of replacing them.

But as with every trend in the market, there is an opportunity to be had for those willing to see past appearances and look for the value in unexpected places. At Stage Fund, our bread and butter is in seeking out and investing in distressed technology companies who are unable to secure funding. 

The correction in the generative AI market presents a compelling opportunity for us and the investors we work with. While less experienced VCs may panic and flee the space at the first sign of a “bust,” we are actively scouting for the most promising generative AI companies and technologies to which we can provide smart capital and operational expertise.

Tip: Actively seek opportunities to invest or partner with companies where the existing business offering is strong. Then become laser-focused on developing a sustainable operating model that balances customer acquisition costs with long-term profitability.

We know from experience that transformative technologies often follow the classic “hype cycle” pattern—after an initial peak of over-excitement, there is a trough of disillusionment before real-world adoption and value creation finally takes off. The businesses that are able to survive that trough and iterate intelligently are the ones that inevitably win big once the market acceleration hits.

This can clearly be seen in the dot-com bust, when companies pursued rapid growth—expecting the novelty of a disruptive new technology to sustain them—and neglected to develop a viable, long-term business strategy. These companies indulged in a glut of investor funding without charting a clear course towards financial self-sufficiency.

Tip: Be wary of overexpansion. Take the cautionary tale of Webvan, an early internet company that showed exceptional promise but poured all their efforts into expanding in multiple cities before finding a successful operating model in any one market. The result was them burning through $800M+ in funding. If they had taken the time to prove out their model before expanding, things may have turned out differently.

Simply having powerful AI models is not enough. The winning companies will be those who find thoughtful ways to enhance real-world software applications, workflows, and business use cases with generative AI capabilities. 

Throwing caution to the wind and neglecting to consider the basics like revenue generation and market demand won’t pay off in the long run.  But taking the time to understand your market and develop a sustainable operating model will position you to survive and thrive during and after the AI gold rush.

If you are a generative AI startup going through challenging times, Stage Fund represents a port of stability and a pathway back to realizing your technology’s immense potential. We have the vision, resources, and experience to help your company thrive so you are perfectly poised to experience exponential growth.