What’s happening to AI startups after the 2024 boom?

Just a year ago, it seemed like the world of artificial intelligence was experiencing a golden age. Dozens of new AI startups were emerging every week: some promised to forever change office work, others — to rewrite the rules of business, and some — to simplify life for every person on the planet. It felt like simply adding the word "AI" to a project could instantly attract millions of dollars in investment.
But the beginning of 2025 painted a very different picture. Somewhere between the headlines about new models and polished presentations, reality started to falter. The flow of money slowed. Startups began shutting down. Investors became more cautious.
What happened? And what lies ahead for AI startups?

It all started with a gold rush

Understanding the situation begins with what happened in 2024.
It truly was a year of madness. Huge language models became available to everyone. Companies raced to integrate neural networks into their products. Ambitious plans were announced at the governmental level: from national AI development programs to integrating the technology into courts, hospitals, and schools.
This wave gave rise to hundreds of new projects. Often they were driven by talented people. Sometimes — by those who simply knew how to catch the moment.
But alongside this excitement, another reality emerged: many startups hastily built solutions without checking whether the market actually needed their technology. Some created yet another tool for writing emails; others — assistants for resume building. There were too many such products, and users quickly grew tired.
When the novelty wore off, it turned out that not every AI application was truly necessary.

Image from kitrum.com

When technology outpaced reality

In 2025, what was bound to happen sooner or later finally did: the market started cooling down. Investors who, just half a year earlier, were signing checks without fully reading pitch decks, began asking uncomfortable questions: How many real customers do you have? How are you planning to make money? What is the cost of implementation?
It turned out that creating a prototype based on ready-made models was one thing, but building a sustainable business model was quite another. AI products demanded constant updates, investments in infrastructure, and solutions to legal issues related to data.
Some startups folded without even reaching a second product version. Others quietly sold off for modest sums or went underground, trying to find a new niche.

But to say that the market is dead would be a huge mistake.
Amid the chaos, another trend began to emerge: those who had been building technologies to solve real problems — not just to ride the hype — started to survive.
Companies like Anthropic, which focused on system safety, became especially in demand among financial and healthcare clients.
Perplexity AI proved that high-quality information search is far from a solved problem — it's a vast field for innovation.
Young teams working on open models, such as Mistral AI, attracted a whole community of developers eager to grow new products together.
The surviving AI startups became quieter. Less buzz, more real-world cases. They focused on narrow tasks: automating specific processes, smart data handling, and building efficient personal assistants for specific industries.

How the rules changed for investors

Investors evolved too.
They no longer want stories about how a startup will "change everything forever." They are looking for projects that can demonstrate tangible results — even if it's small but steady growth.
It became fashionable not to promise revolutions, but to calmly say, "We automate accounting data processing for small businesses and earned $500,000 in six months."
Those who can deal with reality became easier to spot. These are the startups now getting funded, hiring people, and growing — perhaps not at the dizzying speeds of last year, but much more confidently.

New trends are emerging on the horizon

Universal AI products are giving way to niche solutions: for healthcare, legal services, construction. There is growing demand for systems that can act independently — not just respond to questions but truly perform tasks from start to finish.
Finally, the issue of regulation is becoming more pressing. Businesses now understand that solutions must be built with data protection, ethics, and algorithm transparency in mind. Those who ignore this quickly lose client trust.

What awaits AI in 2025: New trends

While some startups are shutting down, others are adapting to the new market expectations. And in 2025, clear trends are already visible that will shape the future of AI.

1. The Era of AI Agents
   The main trend of 2025 is the shift from "smart assistants" to autonomous AI agents.
   These are no longer just chatbots or text generators. Agents can plan tasks, make decisions, and execute them from start to finish without human intervention. And not just in experimental settings, but in real business operations — like marketing, CRM management, or internal process automation.
   (You can read more about AI agents' potential in the latest review by The Cymes: What Are AI Agents and How They Are Changing Business Processes.)
2. A Shift from "Text and Images" to Actions
   It's no longer enough just to generate text, images, or code. In 2025, there’s a growing demand for AI solutions that can act: manage workflows, take initiative, and interact with systems without constant user prompts.
3. Specialization Over Universality
   Universal models are moving to the background. Startups offering narrow but deep solutions for specific industries — healthcare, finance, logistics, law — are winning.
   This allows them to quickly demonstrate real product value — and makes it easier to attract and retain customers.
4. The Growing Importance of Trust and Ethics
   Issues of privacy, data reliability, and algorithm transparency are no longer just about reputation — they are becoming critical business factors.
   Companies are increasingly choosing solutions that proactively address ethical standards and offer data security guarantees.

Image by Pexels

What’s next?

The AI market is not disappearing.
The early years’ naivety — the belief that neural networks would solve all humanity’s problems — is fading. A new philosophy is taking hold: AI is just a tool. A powerful, promising tool — but one that requires conscious, careful use.
For startups, this means one thing: it’s no longer enough to win with hype alone. Those who can identify real problems and build simple, reliable solutions for them will succeed.
And perhaps, that’s the best thing that could have happened to the industry after the 2024 boom.