Today's AI Isn't the Answer Andy Marken October 8, 2026
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Let's say you're telling the truth, and this is all a dream. - Douglas Quaid, Total Recall , Carolo Pictures, 1990
Depending on who you want to believe, we'll spend $650B on the low end or as much as $2.5T this year on AI.
The problem is after plunking down all that money, we'll have the equivalent of a five-year-old who's just learning how to maneuver in the world.
And we're just getting warmed up in terms of investment.
Nvidia - a company and management team we really respect - powers the majority of the GPU engine world and even they are investing in and supporting every start-up organization with AI in their name or business plan.
They're doing it because they know the majority will either fizzle out, be bought out/merged with someone else or become hollow shells and slowly/painfully die of natural causes - money/interest dries up.
They just don't know which ones.
Source - CB Insight
But for Jensen and company that's okay because the survivors will more than cover the losers and just like roulette you have to play the odds.
Companies are projected to increase their investment in LLMs (large language models) by 72 percent this year buying models from anyone who promotes one because they don't want to be locked into one that ends up being a dead end.
There are 100s/1000s proofs-of-concept, applications, tools being developed, rushed to market so AI companies can meet their numbers and keep the investments rolling in.
Do they work, do what they're supposed to do, produce measurable/meaningful results, make life easier/better? No one really knows because you're measuring it against
Oh, sure you can build a spreadsheet in a few minutes, you can create a report in a couple of hours, and our video creation friends can knock out a script in under a day but is that all there is?
AI promised everything - improved efficiency, innovation, accuracy, speed to market, new opportunities, enhanced customer satisfaction, added profit and what the heck life in general.
Has it?
Compared to what?
Source - Carolo Pictures
One of our technically driven friends sees what amounts to an embarrassment of riches with all of the options that are all supposed to deliver immediate results almost across the board.
All you have to do is identify your KPIs (key performance indicators) to measure your progress on meeting critical strategic goals that drive performance, enable you to make data-driven decisions and provide organizational focus all while revolutionizing areas as advertising, marketing, journalism, entertainment, financial management.
Source - Tenor
At the same time another equally astute friend has a slightly different view of our rush to implement AI anywhere, everywhere and magically results will appear for everyone.
He's not opposed (nor are we) to AI and its many flavors but rather that a lot of research, work and testing needs to be done before we reap any real, meaningful benefits.
Organizations - including AI developers/marketers - struggle to find use case studies that can have room for inaccuracies (translation - failure rates are high).
The costs increase exponentially as organizations begin to implement AI to attack complex problems and across the board or said a different way is the cost worth the benefits.
The work may be a masterpiece of execution, but it doesn't consistently produce usable results and benefits it's just an IT masterpiece.
The results could produce as Dario Amodie, president of Anthropic noted a country of yes-men on servers.
Source - Statista
Our cautionary friend - as most of us do - uses his search engine multiple times a day and BAM!! AI-generated results appear at the top of the page and all too many folks accept the results as the definitive answer to their quest.
If his mind questions even parts of the information requested, he will ask the same question multiple times in various ways.
Statista found that only a third of the people surveyed trusted the results, a quarter were less likely to trust them and 40 percent somewhat trusted them.
Far from a wholehearted endorsement.
As with any prescription you take there are side effects in the use of AI when you read the fine print like widespread job displacement particularly entry-level roles and staff culling, loss of control over certain processes while relying on technology and best of all better tracking of staff productivity which can lead to stress and safety risks.
Even though we have over 10,500 AI data centers in the world in operation today and many more scheduled to be online by 2030, they hold, process and use only a sliver of information/data that has been developed and used by humans.
For more than 300,000 plus years since we left central Africa and migrated globally, we have been developing and using information/data but it as recent as 6,000 years ago we finally put down written records and cave art.
Prior to that - and even today - we relied on oral stories passed from one generation to another.
In fact, Socrates wasn't a great fan of the written word saying that the reliance of writing destroys the memory and weakens the mind.
As we expand our reliance on digital data and information we'll have to see.
Source - Cronatec
It wasn't until the 1820s that Charles Babbage developed the forebearer to today's computer, the analytical engine that digitized data became practical.
The machine automatically computed mathematical tables eliminating human errors, but it laid the foundation for today's computers.
In 1946, the world's first programmable, electronic, general-purpose computer (ENIAC) which weighed 30 tons, used 18,000 vacuum tubes and fit in a 1,500 sq ft room.
It was programmed by rewiring cable
