The AI Bubble: How to Invest for Value, Not Hype

Published on
October 10, 2025
The AI Bubble: How to Invest for Value, Not Hype
Is your business at risk of the AI bubble? Discover the key mistakes to avoid and get a clear roadmap for investing in AI that actually generates revenue.

"We're either going to have a dot-com bubble–style collapse or an absolute revolution." "AI is the biggest bubble in history." "95% of AI pilots are failing." "AI will save us." "AI will destroy us all."

The chatter around artificial intelligence is louder than ever, fueled by headlines that swing between utopian promises and dystopian warnings. Everyone seems to have an opinion, from Wall Street analysts and venture capitalists to tech CEOs and futurists. The conversation is dominated by whether AI is a fleeting hype cycle or the dawn of a new era.

But while everyone is busy debating if the AI bubble will pop, few are talking about something more important for businesses: how to make sure you're not in it even if it does exist. This article is for those who want to move beyond the noise. We'll explore how companies can avoid the trap of speculative investment and instead, build an AI strategy that delivers real, measurable value.

What is this “AI Bubble” and are we already there?

Bubbles are not a new phenomenon: from 17th-century Dutch Tulip Mania to the 19th-century Railway Mania in the UK, and more recently, the dot-com bubble of the late 1990s. And nowadays, when a new promising advancement comes up every month, and everyone blindly believes that this is going to be the best thing since sliced bread, getting into a bubble is much easier. But what do we mean by those bubbles?

‘Allegory on Tulipmania’ by Jan Brueghel, 1640

So, as a phenomenon, a bubble, or better to say an economic or financial bubble, is a period of time when companies and individuals invest in an asset more than the objective value of that asset is. 

Therefore, what is believed to be an AI bubble means that businesses are overinvesting in AI, when the real impact of those investments is yet to be proved. This theory of AI being a bubble was mainly supported by a recent MIT study, where we could witness a heartbreaking statistics: 95% of generative AI pilots fail

Additionally, famous tech voices such as Jeff Bezos and OpenAI CEO Sam Altman have also raised their concerns about the AI sector experiencing a bubble. 

"
When bubbles happen, smart people get overexcited about a kernel of truth. Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes.
"
Andrew Amann
Sam Altman
CEO of OpenAI

So, while the real existence of the AI bubble is a subject of discussion, there is still a risk for anyone to invest in AI and get zero ROI. 

Why should the AI bubble concern businesses?

As an AI agency that works with companies that want AI in their products or processes, and see AI as a strategic asset, rather than a financial one, the topic we want to cover here is how and why the AI bubble may affect our clients and their businesses. 

So, instead of discussing financial literacy and stock markets, we’ll take a look at this phenomenon from the perspective of those enterprises and startups that see how all their competitors rush into AI, and rush there as well. 

Here is what puts their business into a risk of living and failing inside the AI bubble:

  • Losing focus on the problem: Many companies jump into AI projects driven by hype rather than a specific business need. This can lead to building a flashy but ultimately useless "vibe-coded hackathon solution" that fails to solve any core problems or integrate with existing workflows. The goal is to solve a business problem, not to simply use AI for its own sake.
  • Wasting resources on unclear goals: Without clear success metrics and a defined end goal, AI projects can quickly spiral out of control in terms of cost and timeline. Teams get bogged down by technical challenges, such as handling edge cases, and stakeholders can't agree on what "correct" looks like.
  • Failing to manage expectations: The "GPT fallacy" leads companies to believe that a simple query will solve a complex problem. This creates a false sense of security and leads to unrealistic expectations. When the AI doesn't perform perfectly or the latest model isn't the "AGI" they were hoping for, they might abandon the project entirely, believing the technology isn't ready.
  • Ignoring the importance of specialization: Generic AI models like ChatGPT are not a one-size-fits-all solution for businesses. The real value lies in building specialized models tailored to specific industries or company functions. Not taking this into account can result in high costs and poor performance.
  • Using the wrong talent: A major reason AI projects fail is a lack of the right expertise. Companies may try to build a complex tool with an inexperienced internal team, leading to avoidable mistakes and project failure. Hiring an agency that specializes in AI implementation can provide the necessary knowledge and guidance, ensuring a more successful and efficient outcome.
  • Facing financial instability: In an AI bubble, overinvestment can lead to a market correction. This can result in funding drying up, increasing prices for AI tools and services, and a general withdrawal of investment from the sector. Businesses that have not secured ROI-positive projects will be in a vulnerable position.
"
I see too many AI projects coming to us for a “second try” after burning $50k for completely avoidable reasons. There are agencies using horrible engineering practices while charging $40k to vibe code. Not solving for edge cases from the onset, just building the “golden path” without worrying about variations of the systems. It’s avoidable, if you start by asking the right questions.
"
Andrew Amann
Andrew Amann
CEO and Co-Founder at NineTwoThree

Am I in the AI bubble? 

A pretty logical question you might ask yourself is whether you’re already there, in a bubble, and have chances to lose your investments with wrong decisions. So, to save you trouble, we’ve created a quiz that would show your chances of being in the AI bubble, and what to pay attention to so you can keep yourself farther from it. 

Am I in the AI Bubble?

A Quiz for Value-Driven Businesses

Answer the following questions to see if your AI decisions are based on solid strategy or a foundation of hype. Choose the answer that best represents your company's approach.

Your Results

How to ensure your AI decisions are not based on AI craze? 

As we've seen, the AI bubble isn't about the technology's potential, but about the risk that businesses will misapply it. To avoid getting swept up in the craze, you must shift your mindset from a speculative rush to a disciplined, strategic approach. This is the difference between an expensive experiment and a high-impact investment.

Here's how to ground your AI decisions in value.

1. Start with the "Why," Not the "What"

Before you even think about a specific tool, model, or a flashy new feature, you must start with a fundamental question: What business problem are we trying to solve?

Many companies jump into AI because they see a cool product and then go looking for a problem to apply it to. This approach is a one-way ticket to the AI graveyard. Instead, conduct a "brutal self-audit" of your operations. Find the most painful, time-consuming, and expensive bottlenecks in your workflow. Your AI journey should begin here, with a clear, quantifiable objective that is more about solving your problems than it is about the technology itself.

And if you need a little help vetting your AI idea, you can always download our AI project map

2. Design for a System, Not a Shortcut

A quick weekend project or a prototype built without a clear plan is almost guaranteed to fail. A successful AI implementation is a carefully engineered system.

  • Define success with numbers: Don't settle for vague goals like "improving efficiency." Instead, set a clear, quantifiable ROI. Your blueprint should include measurable outcomes like "reduce customer support costs by 20%" or "cut manual data entry time in half." If you can't measure it, you can't manage its success.
  • Build with a full roadmap: A simple prototype might work in a demo, but what about the real world? A strategic approach means planning for the messiness of real-life business. Your roadmap must account for all the "edge cases": the exceptions and variations that an off-the-shelf model would miss.
  • Embrace the MVP: A full-scale AI project can be a massive investment. The smart approach is to start small with a Minimum Viable Product (MVP). This lets you prove the concept in a low-risk environment, demonstrate its value to stakeholders, and build the confidence you need for a full rollout.

3. Choose a Partner, Not Just a Vendor

The market is flooded with firms that promise to deliver AI solutions. But not all partners are created equal. A successful AI project requires more than just technical skill; it demands deep, specialized expertise.

Avoid the trap of hiring a large, generic consulting firm or an inexperienced team that will "vibe code" its way to a prototype without a clear business outcome. A true partner will have a proven track record of solving problems in your specific industry. They will ask the tough questions, help you define your goals, and ensure your project stays on a direct path toward a positive ROI.

So, will the AI bubble pop?

For companies that don’t prioritize strategy and value over trends – yes, it will. In this article, we’ve listed what you can do to prevent yourself from getting caught in the AI bubble.

And If you need a partner who can help you build a profitable, value-driven AI solution, you can always contact NineTwoThree AI studio. 

We're an award-winning AI studio with a proven playbook for building custom AI solutions that deliver measurable ROI in months, not years. We’ve successfully launched over 160 projects for clients and built our own startups, proving we understand what it takes to turn an idea into a scalable, profit-producing application.

Don’t get stuck in a pilot program that goes nowhere. Talk to us and find out how AI solutions can deliver positive ROI for your business.

"We're either going to have a dot-com bubble–style collapse or an absolute revolution." "AI is the biggest bubble in history." "95% of AI pilots are failing." "AI will save us." "AI will destroy us all."

The chatter around artificial intelligence is louder than ever, fueled by headlines that swing between utopian promises and dystopian warnings. Everyone seems to have an opinion, from Wall Street analysts and venture capitalists to tech CEOs and futurists. The conversation is dominated by whether AI is a fleeting hype cycle or the dawn of a new era.

But while everyone is busy debating if the AI bubble will pop, few are talking about something more important for businesses: how to make sure you're not in it even if it does exist. This article is for those who want to move beyond the noise. We'll explore how companies can avoid the trap of speculative investment and instead, build an AI strategy that delivers real, measurable value.

What is this “AI Bubble” and are we already there?

Bubbles are not a new phenomenon: from 17th-century Dutch Tulip Mania to the 19th-century Railway Mania in the UK, and more recently, the dot-com bubble of the late 1990s. And nowadays, when a new promising advancement comes up every month, and everyone blindly believes that this is going to be the best thing since sliced bread, getting into a bubble is much easier. But what do we mean by those bubbles?

‘Allegory on Tulipmania’ by Jan Brueghel, 1640

So, as a phenomenon, a bubble, or better to say an economic or financial bubble, is a period of time when companies and individuals invest in an asset more than the objective value of that asset is. 

Therefore, what is believed to be an AI bubble means that businesses are overinvesting in AI, when the real impact of those investments is yet to be proved. This theory of AI being a bubble was mainly supported by a recent MIT study, where we could witness a heartbreaking statistics: 95% of generative AI pilots fail

Additionally, famous tech voices such as Jeff Bezos and OpenAI CEO Sam Altman have also raised their concerns about the AI sector experiencing a bubble. 

"
When bubbles happen, smart people get overexcited about a kernel of truth. Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes. Is AI the most important thing to happen in a very long time? My opinion is also yes.
"
Andrew Amann
Sam Altman
CEO of OpenAI

So, while the real existence of the AI bubble is a subject of discussion, there is still a risk for anyone to invest in AI and get zero ROI. 

Why should the AI bubble concern businesses?

As an AI agency that works with companies that want AI in their products or processes, and see AI as a strategic asset, rather than a financial one, the topic we want to cover here is how and why the AI bubble may affect our clients and their businesses. 

So, instead of discussing financial literacy and stock markets, we’ll take a look at this phenomenon from the perspective of those enterprises and startups that see how all their competitors rush into AI, and rush there as well. 

Here is what puts their business into a risk of living and failing inside the AI bubble:

  • Losing focus on the problem: Many companies jump into AI projects driven by hype rather than a specific business need. This can lead to building a flashy but ultimately useless "vibe-coded hackathon solution" that fails to solve any core problems or integrate with existing workflows. The goal is to solve a business problem, not to simply use AI for its own sake.
  • Wasting resources on unclear goals: Without clear success metrics and a defined end goal, AI projects can quickly spiral out of control in terms of cost and timeline. Teams get bogged down by technical challenges, such as handling edge cases, and stakeholders can't agree on what "correct" looks like.
  • Failing to manage expectations: The "GPT fallacy" leads companies to believe that a simple query will solve a complex problem. This creates a false sense of security and leads to unrealistic expectations. When the AI doesn't perform perfectly or the latest model isn't the "AGI" they were hoping for, they might abandon the project entirely, believing the technology isn't ready.
  • Ignoring the importance of specialization: Generic AI models like ChatGPT are not a one-size-fits-all solution for businesses. The real value lies in building specialized models tailored to specific industries or company functions. Not taking this into account can result in high costs and poor performance.
  • Using the wrong talent: A major reason AI projects fail is a lack of the right expertise. Companies may try to build a complex tool with an inexperienced internal team, leading to avoidable mistakes and project failure. Hiring an agency that specializes in AI implementation can provide the necessary knowledge and guidance, ensuring a more successful and efficient outcome.
  • Facing financial instability: In an AI bubble, overinvestment can lead to a market correction. This can result in funding drying up, increasing prices for AI tools and services, and a general withdrawal of investment from the sector. Businesses that have not secured ROI-positive projects will be in a vulnerable position.
"
I see too many AI projects coming to us for a “second try” after burning $50k for completely avoidable reasons. There are agencies using horrible engineering practices while charging $40k to vibe code. Not solving for edge cases from the onset, just building the “golden path” without worrying about variations of the systems. It’s avoidable, if you start by asking the right questions.
"
Andrew Amann
Andrew Amann
CEO and Co-Founder at NineTwoThree

Am I in the AI bubble? 

A pretty logical question you might ask yourself is whether you’re already there, in a bubble, and have chances to lose your investments with wrong decisions. So, to save you trouble, we’ve created a quiz that would show your chances of being in the AI bubble, and what to pay attention to so you can keep yourself farther from it. 

Am I in the AI Bubble?

A Quiz for Value-Driven Businesses

Answer the following questions to see if your AI decisions are based on solid strategy or a foundation of hype. Choose the answer that best represents your company's approach.

Your Results

How to ensure your AI decisions are not based on AI craze? 

As we've seen, the AI bubble isn't about the technology's potential, but about the risk that businesses will misapply it. To avoid getting swept up in the craze, you must shift your mindset from a speculative rush to a disciplined, strategic approach. This is the difference between an expensive experiment and a high-impact investment.

Here's how to ground your AI decisions in value.

1. Start with the "Why," Not the "What"

Before you even think about a specific tool, model, or a flashy new feature, you must start with a fundamental question: What business problem are we trying to solve?

Many companies jump into AI because they see a cool product and then go looking for a problem to apply it to. This approach is a one-way ticket to the AI graveyard. Instead, conduct a "brutal self-audit" of your operations. Find the most painful, time-consuming, and expensive bottlenecks in your workflow. Your AI journey should begin here, with a clear, quantifiable objective that is more about solving your problems than it is about the technology itself.

And if you need a little help vetting your AI idea, you can always download our AI project map

2. Design for a System, Not a Shortcut

A quick weekend project or a prototype built without a clear plan is almost guaranteed to fail. A successful AI implementation is a carefully engineered system.

  • Define success with numbers: Don't settle for vague goals like "improving efficiency." Instead, set a clear, quantifiable ROI. Your blueprint should include measurable outcomes like "reduce customer support costs by 20%" or "cut manual data entry time in half." If you can't measure it, you can't manage its success.
  • Build with a full roadmap: A simple prototype might work in a demo, but what about the real world? A strategic approach means planning for the messiness of real-life business. Your roadmap must account for all the "edge cases": the exceptions and variations that an off-the-shelf model would miss.
  • Embrace the MVP: A full-scale AI project can be a massive investment. The smart approach is to start small with a Minimum Viable Product (MVP). This lets you prove the concept in a low-risk environment, demonstrate its value to stakeholders, and build the confidence you need for a full rollout.

3. Choose a Partner, Not Just a Vendor

The market is flooded with firms that promise to deliver AI solutions. But not all partners are created equal. A successful AI project requires more than just technical skill; it demands deep, specialized expertise.

Avoid the trap of hiring a large, generic consulting firm or an inexperienced team that will "vibe code" its way to a prototype without a clear business outcome. A true partner will have a proven track record of solving problems in your specific industry. They will ask the tough questions, help you define your goals, and ensure your project stays on a direct path toward a positive ROI.

So, will the AI bubble pop?

For companies that don’t prioritize strategy and value over trends – yes, it will. In this article, we’ve listed what you can do to prevent yourself from getting caught in the AI bubble.

And If you need a partner who can help you build a profitable, value-driven AI solution, you can always contact NineTwoThree AI studio. 

We're an award-winning AI studio with a proven playbook for building custom AI solutions that deliver measurable ROI in months, not years. We’ve successfully launched over 160 projects for clients and built our own startups, proving we understand what it takes to turn an idea into a scalable, profit-producing application.

Don’t get stuck in a pilot program that goes nowhere. Talk to us and find out how AI solutions can deliver positive ROI for your business.

Alina Dolbenska
Alina Dolbenska
color-rectangles

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