Many economists and technology experts have drawn parallels between the dot-com bubble and the AI boom. There are no doubt similarities between the rapid speed of innovation and the incredible spend on these technologies, but the technology industry has changed dramatically in the last 25 years. From the new economic outlook to the transformed investor and startup landscape, there are marked differences between these two eras. It’s in these changes that founders can build on the lessons learned to achieve success in today’s fierce market.
Many people expect that AI will be much bigger than the internet. There are now a multitude of scenarios where AI is enhancing the capabilities of humans for better performance, and as this number continues to increase, the opportunities for founders and AI startups are growing across the board.
Distinguishing the AI revolution from the dot-com bubble
Given today’s competitive funding scene, many people are surprised to learn how “cheap” it was to launch a startup in the late 1990’s and early 2000’s. The growth of the internet back then was less about making financial sense, and more about getting “eyeballs” and new users to your website. Building an AI business today is an expensive venture because of the computing power needed for graphics processing units and to run models. Founders must really weigh the potential for financial profit against the cost of an AI business. Investors are also much more cautious these days, requiring more out of founders before opening their wallets. Data from OMER Ventures shows that venture capitalists (VCs) have changed how they evaluate startups drastically, with nine categories of diligence seeing over a 30% increase in focus including financial analysis, customer diligence, use of fund analysis, go-to-market analysis and more.
Product development involves a higher level of scrutiny today too. For example, investors in the dot-com era used to try determining the minimum viable product (MVP) and then sell it to the market as long as possible before it needed to be updated. Today, we see this a lot less frequently. With the competitive technology landscape, especially in AI innovation, MVP is no longer about validating a novel idea as quickly as possible to get it on the market, but rather the initial stages of product development are used to draw in the early users and gather feedback to improve the product.
Another huge difference that is often overlooked is that the internet was primarily pioneered by startups. Today, companies of all sizes have taken a stake in AI from brand new startups to tech giants. While this competition makes disruption and differentiation more difficult at times, it also provides AI startups with opportunities to grow, go public or exit.
Operating in today’s AI boom
The startups businesses of today are much healthier companies than those in the dot-com era. In fact, a 15-year data analysis of 200,000 founders and employees of the most successful tech companies ever built outlined three areas giving today’s founders more power than ever before. First, years of wisdom have been accumulated by past founders who have built their startups into empires, setting up a playbook for best practices for today’s founders. Second, startup expertise is no longer clustered in the Silicon Valley area but has expanded to a global network of experts located in hubs across the world. And finally, technological innovation has greatly reduced the barrier to entry for new founders, enabling today’s startup teams to accomplish much more possible, and in less time, than before.
On top of a more established startup industry and founders having information at their fingertips for every challenge imaginable, the investment landscape is also much healthier. Despite all this, today’s founders are competing against an increasing number of other AI businesses of all sizes, leaving founders to face more scrutiny from investors, intensifying the need for differentiation in the market. To ensure success beyond the initial AI boom, founders must learn from the past and build toward a sustainable future.
1. Focus on the fundamentals
Founders cannot risk falling flat on business fundamentals, from both a technological and market standpoint. To stay ahead, founders must be an expert on their industry, constantly scanning what is happening in the market and with competitors – and pivoting their strategy when needed.
This starts with product-market fit. Without having a product that satisfies a strong-market demand, a startup won’t be able to amass a consistent customer base or realize its long-term growth strategy, resulting in churn and low user engagement. Understanding the essentials for revenue generation is also critical to the success of a startup. Founders must not only know how to monetize, but you need to have a solid grasp on both cost structure and spend – a skill that lacked during the “growth at all costs” mentality of the dot-com era. And finally, be wary of your own equity being diluted, as more investors take a stake in your business and gain part of that equity.
2. Build only what you need
The market is constantly fluctuating, and overextending as a startup can put you in dangerous waters. From both a product and a people perspective, founders should keep their focus narrow and be smart and strategic. Don’t build anything you don’t need to build, and don’t hire anyone you don’t need to hire.
If you’re able to build your product on top of another large language model, do it. There’s no reason to hire someone to write these algorithms themselves. Without discipline in these areas, startups can often lose a lot of time and money pushing their product forward. And on the employee side, startups today simply don’t need as many people as they used to. Find the right people, and make sure they’re in it for the long haul.
3. Differentiate in the crowded market
Customers are more unpredictable than ever and fewer are signing long-term contracts. To meet customer needs, founders must ensure their AI models are applicable – staying on top of the best, most efficient technology and optimize innovation to constantly scale their infrastructure.
With the ongoing conversations around ethical AI, model hallucinations and data privacy issues, all of which were virtually nonexistent during the dot-com era, this is a prime area to put yourself ahead of competitors. However, no matter where your startup looks to differentiate itself in the AI industry, validating your work consistently is crucial. For every ideation, it should be followed by validation. Figure out what people are willing to pay for from your product, and just keep on reiterating to further develop and sharpen your product.
4. Manage funds carefully
Raising money in today’s funding landscape has grown into, at times, a challenging undertaking. Today, more AI startups are seeing how long they can survive before replenishing their cash reserves. When you are able to secure funding, it is critical to manage those funds carefully and direct them to the most strategic areas of your business.
In addition, diversifying revenue streams is key to creating steady and stable growth. Whether that is through developing new offerings, entering new markets or expanding to new customer segments, ensuring your startup has income flowing from multiple sources could be the difference between surviving tough economic downturns or floundering.
Define your future success by learning from lessons of the past
Compared to the early 2000’s, today’s AI boom is characterized not only by a healthier investor market but also a healthier founder market. This generation of founders are smarter and nimbler than ever, especially with the wealth of knowledge they have at their fingertips. But this doesn’t make achieving success any easier. As AI startups, and founders across any industry, consider how they can succeed, it’s always helpful to look back at history and learn from experiences of the past. Today’s founders can take away lessons from the dot-com era in the same way future founders will learn from the current AI boom.
