Artificial intelligence (AI) was adopted by many companies globally last year, and we witnessed the emergence of numerous AI startups with attention-grabbing news releases and appealing AI suffixes on their names.
In fact, several analysts hypothesized in the first quarter of 2024 that artificial intelligence might be the piece that closes the profit gap between companies and their goals. This gave the impression of a burgeoning artificial intelligence (AI) market where everyone from Tom to Dick to Harry has figured out how to profit handsomely from their AI investments.
But even industries with a track record of success can burst, and with the hype around AI reaching a fever pitch, maybe there are valid concerns.
Large Investment In AI Startups Despite Low Returns
A wake-up call is being given to the AI industry as well-known businesses are having financial difficulties. Over the past three years, investors have poured $330 billion into over 25,000 AI firms, yet many of these businesses are finding it difficult to close the gap between their expensive costs and meager earnings.
The business is progressively changing as a result of this financial burden; firms such as Stability AI have parted ways with their CEO and laid off 10% of their workforce.
Or take Inflection AI as an example. This business raised more than $1.3 billion in June 2023. The business took great satisfaction in being the first to create a chatbot that provides consumers with emotional assistance. The creators of Inflection AI were recently acquired by Microsoft, and the company’s personalized AI assistant (Pi), which was hailed as ChatGPT’s successor, appears to have no takers.
The $4 billion AI startup Olive announced its closure in November 2023. The unicorn made the decision to wind down the remainder of its activities and sell Waystar and Humata Health its primary businesses.
Some AI stocks are starting to enter a bear market after experiencing periods of bullishness due to the growing uncertainties. SoundHound AI, a voice AI and speech recognition startup, saw a 22% decline in its stock price in June. Even though the business did not release any unfavorable news last year, this decrease nevertheless happened.
S&P Global Market Intelligence’s data reveals a discrepancy between the company’s real performance and the mood of the market at this time.
Why AI Startups Are Facing Such Adversity
When you focus on the difficulties faced by AI businesses in recent years, the tale of OpenAI becomes less and less relevant.
The creator of ChatGPT, possibly the most prosperous AI firm of the past five years, has experienced a steady rise in popularity. We can claim that the corporation is operating from a safe place because of its arm’s-length agreements with Apple and Microsoft, as of late.
What about other AI startups that don’t have the strong support of major corporations? In what way do they attempt to balance the massive expenses incurred in creating and sustaining generative AI systems?
This is a question since generative AI models are expensive to construct and maintain, costing billions of dollars, which makes them unfeasible for startups without the support of large tech companies. Previous advances in AI were based on pre-existing components, such as smartphones.
Time has released statistics that show that the expense of developing sophisticated AI models is doubling roughly every nine months. The cost of just hardware and electricity to construct cutting-edge AI systems could reach billions of dollars by the end of this decade.
The specialized chips required for these systems are expensive and hard to come by, on top of the training costs. Given that Nvidia has virtually singlehandedly taken over the AI chip business, it seems unlikely that the cost of AI processors will decrease very soon.
A number of AI startups are severely hampered by this financial reality as they struggle to compete with industry heavyweights like Google, Microsoft, and Meta.
Beyond Financing, AI Startups Are Also At Fault
Rusty Ralston, co-founder and general partner of Swell VC, contends that many AI firms are to blame for their present funding problems and lack of profitability, in addition to the expense of training, creating, and maintaining AI models.
Ralston contends in an interview with Techopedia that a lot of AI businesses are following trends rather than addressing actual client needs.
“The main reason some AI startups are having trouble is that it’s possible they’re not actually helping customers with their problems.”
Regardless of the technology employed, the VC partner advises businesses to concentrate on identifying and resolving “burning problems” rather than imposing AI into situations where it is not required.
Furthermore, he cautions against relying too much on large language models (LLMs). He claims that “anyone who says LLMs solve everything is wrong” and cites “massive limitations.”
He proposes that employing LLMs alone may not be the most efficient way to solve problems compared to combining them with other AI methods.
Ralston also mentions entrepreneurs that “continuously jump from hot trend to hot trend,” citing instances such as those who go from cryptocurrencies to Web3 to artificial intelligence.
High-caliber founders who have “spent the last several years in their industry, creating value, solving real problems, and having incredible track records” are contrasted with this.
Things To Watch Out For When Investing In AI Startups
The financing frenzy for AI that occurred during the bubble’s zenith last year appears to be winding down. Previously willing to support any bright AI pioneer, venture funders are now more circumspect and are leaving the investment to tech giants, whose resources are frequently concentrated in the hands of a select few.
Finding talented AI founders to support appears to be more of an issue than a shortage of capital.
After speaking with industry experts, Techopedia proposed three things to watch out for as investors.
Outstanding Founders
According to Ralston, exceptional founders are the foundation of each successful startup because they provide vision, resiliency, and the capacity to motivate and guide their staff through difficult situations.
“Investors ought to seek out entrepreneurs that are driven by business and have a track record of building value from the ground up, conquering major challenges, and producing outstanding outcomes.”
Scalable, Lean Startups
Philip Gjørup, the CAIO and co-founder of Nord Comms, highlights the significance of scalability in the absence of significant funds or resources. Gjørup advises concentrating on initiatives that use decentralized construction techniques. With this strategy, startups can expand more effectively and long-term.
The Upcoming Development In AI
Julien Salinas, the founder and CEO of NLP Cloud, stated in a conversation with Techopedia that VC-funded AI firms must turn a profit within a year or risk going out of business. Regretfully, few of them can become successful so rapidly in the current competitive landscape.
From the standpoint of an investor, Salinas suggests taking a “wait and see” stance.
Today, if I were an investor, I would hold off and see. In particular, I would hold off until perhaps new hardware developments like quantum computing or advancements in AI architecture, as generative AI appears to have reached its limit.
The Final Word
In light of the increasing number of AI businesses that are folding because to financial difficulties, it is imperative that aspiring entrepreneurs seek out a sizable market with robust tailwinds. Ralston advises focusing on a sizable and growing market because it’s essential to a startup’s ability to grow and prosper. Businesses that operate in large markets have many options for expansion and dominance, as well as the potential to generate significant revenue.
Joining together with more well-established businesses may potentially be the solution to the finance problems. Anthropic and Open AI, two of the fiercest AI startups, have decided to team up with the very tech behemoths that they may have once aspired to overtake.
They have been able to stay in the game because to this strategy, which has given them access to knowledge and financial resources. Instead of failing, other AI startups with brilliant ideas can imitate that.