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Artificial intelligence is, of course, no longer an urban legend, but it still creates a number of myths about its benefits, dangers and performance. It especially concerns businesses, since implementing AI inside their systems and databases requires confidence in whether and how it will affect the company.
So, to provide the understanding of AI implementation in business, and therefore confidence in decisions around it, we’ve gathered four most common beliefs people have, and will debunk them.
Welcome to the show, and don’t try this at home!
This is an old legend, but even with all the advancement and improvement of AI in 2025, people are still skeptical about whether it can provide any good to the world.
Yes, AI is biased and limited. Yes, it can hallucinate. Yes, AI won’t solve all your problems. And yes, we need to use it wisely not to get low-quality work in the best-case scenario, and endanger anyone in the worst. But so is with any other tool.
And the good news is that the quality of the output AI provides can be managed and improved with the right approach: by defining the problem clearly, providing accurate and relevant data, fine-tuning models for your specific context, and constantly monitoring its performance.
As opposed to those who think that AI can do nothing, many businesses believe that AI will magically start delivering results with minimal effort. Such a misconception often leads to a more “tech-focused” approach, where companies implement AI for the sake of, well, AI.
In such cases, teams don’t try to understand why they need artificial intelligence, who will use it, and, most importantly, how. They don’t iterate, don’t ask for feedback, don’t teach, and are sincerely surprised when just launching wasn’t enough. As a result, they have a fully functional tool that no one actually needs.
In fact, the author of this article has already been fired, and our CEO is just an AI avatar of Ryan Reynolds. Exactly this people expect from AI implementation in business. And it’s a real fear employees have and openly share online.
Yes, we do have cases when company owners rely on AI too much and absolutely diminish humans in the process. But we all know how that ends.
AI can handle simple tasks, automate processes, help with brainstorming and generation, but it will fail when asked to do something complicated, or new, or novel that requires communication, and planning.
“AI party” is ending” with high costs, limited usage quotas, and poor ROI.
Companies often misjudge AI costs by fixating on the price of large, cloud-hosted models. Calculating “API cost × number of calls”, no wonder, makes AI look prohibitively expensive, but it ignores the value side of the equation.
Instead of adopting the biggest or most expensive model, businesses can fine-tune a smaller, domain-specific model and run it locally. In this way they can lower recurring expenses, gain more control over performance, and get a better optimized for their specific workflows model.
So, what’s the real story behind AI in business? It’s not magic. It’s not going to replace everyone’s job tomorrow. And it’s not inherently too expensive or impossible to make work. Most AI failures aren’t surprises. They happen when companies implement AI without a clear problem, without understanding who will use it, or without a plan to make it actually useful.
And specifically to help businesses get this understanding and use AI effectively, NineTwoThree AI Studio exists. We guide companies in defining the right problems, integrating AI where it truly adds value, and ensuring systems are reliable, human-centric, and practical. If you want help implementing AI in a way that actually works, contact us and see your investment deliver real results.
Artificial intelligence is, of course, no longer an urban legend, but it still creates a number of myths about its benefits, dangers and performance. It especially concerns businesses, since implementing AI inside their systems and databases requires confidence in whether and how it will affect the company.
So, to provide the understanding of AI implementation in business, and therefore confidence in decisions around it, we’ve gathered four most common beliefs people have, and will debunk them.
Welcome to the show, and don’t try this at home!
This is an old legend, but even with all the advancement and improvement of AI in 2025, people are still skeptical about whether it can provide any good to the world.
wildling_archer |
Yes, AI is biased and limited. Yes, it can hallucinate. Yes, AI won’t solve all your problems. And yes, we need to use it wisely not to get low-quality work in the best-case scenario, and endanger anyone in the worst. But so is with any other tool.
And the good news is that the quality of the output AI provides can be managed and improved with the right approach: by defining the problem clearly, providing accurate and relevant data, fine-tuning models for your specific context, and constantly monitoring its performance.
As opposed to those who think that AI can do nothing, many businesses believe that AI will magically start delivering results with minimal effort. Such a misconception often leads to a more “tech-focused” approach, where companies implement AI for the sake of, well, AI.
In such cases, teams don’t try to understand why they need artificial intelligence, who will use it, and, most importantly, how. They don’t iterate, don’t ask for feedback, don’t teach, and are sincerely surprised when just launching wasn’t enough. As a result, they have a fully functional tool that no one actually needs.
In fact, the author of this article has already been fired, and our CEO is just an AI avatar of Ryan Reynolds. Exactly this people expect from AI implementation in business. And it’s a real fear employees have and openly share online.
Yes, we do have cases when company owners rely on AI too much and absolutely diminish humans in the process. But we all know how that ends.
AI can handle simple tasks, automate processes, help with brainstorming and generation, but it will fail when asked to do something complicated, or new, or novel that requires communication, and planning.
“AI party” is ending” with high costs, limited usage quotas, and poor ROI.
Companies often misjudge AI costs by fixating on the price of large, cloud-hosted models. Calculating “API cost × number of calls”, no wonder, makes AI look prohibitively expensive, but it ignores the value side of the equation.
Instead of adopting the biggest or most expensive model, businesses can fine-tune a smaller, domain-specific model and run it locally. In this way they can lower recurring expenses, gain more control over performance, and get a better optimized for their specific workflows model.
So, what’s the real story behind AI in business? It’s not magic. It’s not going to replace everyone’s job tomorrow. And it’s not inherently too expensive or impossible to make work. Most AI failures aren’t surprises. They happen when companies implement AI without a clear problem, without understanding who will use it, or without a plan to make it actually useful.
And specifically to help businesses get this understanding and use AI effectively, NineTwoThree AI Studio exists. We guide companies in defining the right problems, integrating AI where it truly adds value, and ensuring systems are reliable, human-centric, and practical. If you want help implementing AI in a way that actually works, contact us and see your investment deliver real results.
wildling_archer |