The Room Went Silent: Why 90% of AI Strategies are Burning Cash

[AnisEverRise]

The Room Went Silent: Why 90% of AI Strategies are Burning Cash

A lesson in "Tool-First" vs. "Problem-First" thinking.

Last month, I sat through a strategy meeting that had been running for three weeks.
The team had built a spreadsheet with 47 criteria. Color-coded tabs.
Deep dives into Microsoft vs. OpenAI vs. Anthropic.

I asked one question that killed the vibe:

"What problem are we actually trying to solve?"

The "Shiny Object" Pattern:

• Companies buy the tool first. Hunt for a problem later.
• Launch pilots with zero success criteria (Excitement > Planning).
• Six months later: "AI didn't work for us."
  

The Illusion of Progress
Tools feel like progress.
Problems feel like homework.

The Reality of ROI:
The companies actually seeing results start with the "boring" questions:

• What is fundamentally broken?
• What is eating our budget?
• Why do our best people want to quit?

Problem-first is slower. It’s less exciting. It’s harder to get a budget for.
But it’s the only thing that actually works.

Most will keep buying tools and wondering why nothing changes.
The smart ones? They already know the answer.


Insights from a QHSE (Quality, Health, Safety, Environment) perspective :)because you don't buy a sensor before you find the leak.

[_act_]

I do not think I really understand what you are saying. Are you saying that you used an AI tool for buying bitcoin since six months ago but you are in losses now because the AI suggested that you should buy?

Hope it is not an altcoin but bitcoin that you DCA? If it is bitcoin that you have been buying since six months ago, just be very patient and continue to buy instead. The market will later change for good. But if it is an altcoin, I do not know what will happen.

[Yamane_Keto]

The fact that these tools do not generate good returns for buyers does not mean that they do not generate profits for developers or investors. They profit from selling these tools, even if they are bad or do not generate any profits.

[Rex1971]

I completely agree with you. Neural networks and any AI tools by themselves don’t solve problems — their effectiveness always depends on context. To achieve real results, AI needs to be combined with a range of other factors:
Analysis of business processes and bottlenecks;
High-quality data and domain expertise;
Internal and external KPIs;
Organizational and human factors;
Clear goal setting and success criteria.
Otherwise, any “trendy” model is just a shiny tool that creates the illusion of progress but delivers no real ROI. The true power of AI only emerges when it’s embedded into a comprehensive decision-making system, rather than used as a standalone solution.

[AnisEverRise]

​

I completely agree with you. Neural networks and any AI tools by themselves don't solve problems... Effectiveness always depends on context.

​Spot on! You hit the nail on the head. From my perspective in QHSE (Quality, Health, Safety, Environment), we often analyze the gap between "Work as Imagined" and "Work as Done". Most companies throw AI at the "Imagined" part without looking at the actual bottlenecks or human factors you mentioned. It’s like installing a hightech sensor in a room with no ventilation, you’re just monitoring the disaster more efficiently.
​

The fact that these tools do not generate good returns for buyers does not mean that they do not generate profits for developers or investors.

​Exactly, and that's the "Gold Rush" paradox. While the miners are struggling, the ones selling the shovels are making a fortune. In the AI world, the "shovels" are the subscription fees and hype driven investments. For the sellers, the "Illusion of Progress" is a very profitable business model, even if the end user ROI is zero.
​

Are you saying that you used an AI tool for buying bitcoin since six months ago but you are in losses now...?

​To clarify, I wasn't talking about a personal investment or a trading bot! I was using a corporate strategy meeting as a metaphor for how organizations waste resources on "AI for the sake of AI" without a clear problem to solve. My background is in QHSE management, so I see this pattern often: people buying the "tool" before they even find the "leak".
​However, your point on DCA and patience is universal   it applies to both Bitcoin and long-term business strategies!

[Darker45]

It's probably a common mistake everywhere. People prefer to take short cuts. Rather than understanding the problem more, or thinking deeper whether what they're dealing with is in fact a problem, they ended up hurriedly looking for solutions right away.

In relation to AI, many mindlessly seek refuge in it because they've been taking the wrong positions in trading, not profitable in gambling, losing in altcoin investments, wrongly picked the shitcoin or scamcoin that quickly grows 1,000 times, and so on.

[AnisEverRise]

It's probably a common mistake everywhere. People prefer to take short cuts. Rather than understanding the problem more, or thinking deeper whether what they're dealing with is in fact a problem, they ended up hurriedly looking for solutions right away.

In relation to AI, many mindlessly seek refuge in it because they've been taking the wrong positions in trading, not profitable in gambling, losing in altcoin investments, wrongly picked the shitcoin or scamcoin that quickly grows 1,000 times, and so on.

Spot on, Darker45. This 'shortcut culture' is a classic case of Technological Solutionism: applying a tool before diagnosing the root cause.

​In my QHSE management experience, AI is often used as a 'miracle pill' to mask structural flaws. But technology is merely a force multiplier; if your process is broken, you simply accelerate your failure at a premium cost.

​Whether in crypto or industry, trying to decouple Wealth from Discipline leads to the same result: expensive noise. True Alpha remains in the 'boring' work of DCA and fundamental analysis that most try to bypass

[PX-Z]

...Are you saying that you used an AI tool for buying bitcoin since six months ago but you are in losses now because the AI suggested that you should buy?

Well, if i asked an AI about buying bitcoin 6 months ago then bought some, i'll be very annoyed and regretful checking the the results in my portfolio now knowing bitcoin was +$110k price 6 months ago compared to now where we at range of $67k. Well, unless you sold some when it was going down.
Talking about AI and its predictions about an assets price, i will never agree or believe to it, id better follow my instincts instead (even theres none) than regretting later and blame it someone else's decision lmao.

[AnisEverRise]

...Are you saying that you used an AI tool for buying bitcoin since six months ago but you are in losses now because the AI suggested that you should buy?

Well, if i asked an AI about buying bitcoin 6 months ago then bought some, i'll be very annoyed and regretful checking the the results in my portfolio now knowing bitcoin was +$110k price 6 months ago compared to now where we at range of $67k. Well, unless you sold some when it was going down.
Talking about AI and its predictions about an assets price, i will never agree or believe to it, id better follow my instincts instead (even theres none) than regretting later and blame it someone else's decision lmao.

Exactly my point, @PX-Z Using AI for price prediction is the ultimate example of a Tool-First failure.

In my field of Quality & Safety (QHSE), we rely on data, but we never ignore the Human Factor. Markets, like complex industrial systems, are driven by human psychology : something AI often fails to model because it looks at the past to predict an unpredictable future.

As you said, checking a portfolio and seeing it drop from $110k to $67k based on an 'AI suggestion' is a failure of Risk Management. The 'Problem' people try to solve is 'How to get rich fast', and they think the 'Tool' (AI) is a magic wand. But they forget the most basic quality principle: Garbage In, Garbage Out.

I'd rather trust a human instinct (even a flawed one) because at least there is Accountability. An AI won't take responsibility for a 40% drawdown. In a high-stakes environment, whether it's a factory floor or a volatile market, the human 'in the loop' is the only one who can truly manage the Uncertainty.

AI is a great Assistant for sorting data, but a terrible 'Manager' for making final decisions