AI Won't Kill the Economy. There's Too Much Work Left to Do.
- Justin Bakst
- Apr 1
- 6 min read
Updated: Apr 14
A provocative thought experiment regarding the effects of Artificial Intelligence has been circulating among investors, economists, bankers, and technologists.
Written as a future fictional analysis in June 2028, it imagines an economy in free fall: the S&P 500 down 38% from its highs, unemployment above 10%, and a deflationary spiral driven by artificial intelligence displacing millions of white-collar workers.
The scenario is well-constructed and the financial implications are carefully outlined. It deserves serious consideration.
But it gets the fundamental question wrong regarding the utility of Artificial Intelligence.
From the Editor
“If you don’t know where you are going, you might end up someplace else.” – Yogi Berra
It’s virtually impossible to watch CNBC or Bloomberg and go ten minutes without some talking head discussing the influence of Artificial Intelligence on the markets and business.
And frankly, there is a wide dispersion of opinions on how significant AI’s impact will ultimately be. From those who simply believe AI is a glorified search engine and the markets are going to ultimately revalue the companies driving growth, to the perceived Illuminati who contend that all of our jobs are going away.
Make no mistake: vast amounts of capital are being deployed to develop the technology and it’s unlikely that anyone really knows the full extent of where these models ultimately “plateau.”
Admittedly, it’s all quite disorienting. Yogi’s quote sums it up perfectly for me: it’s hard to know where we are going, so who really knows where it all ends up.
For those who might be looking for some direction, DCG Executive Director Justin Bakst offers a more optimistic perspective.
In this month’s Bulletin, Justin writes about how AI “won’t kill the economy,” because there is simply “too much work left to do.”
He specifically notes, "...before we model the apocalypse, we should ask a simpler question: Why does a business exist?” He asserts that, “A business exists to solve problems to make a real human being’s life, another company’s operations, or a public institution’s services measurably better.”
And problems aren’t going away because of AI. He contends that AI simply enables humankind to figure out how to solve the problems that need solving.
Justin’s article might not be specific to banking per se, but it is a terrific read for those “who don’t know where they are going” when it comes to predicting the future of AI.
Vinny Clevenger, Managing Director
I have spent my career at the intersection of consulting, banking, finance, and software product development. Over the past several months, I have watched AI systems do things I did not think were possible, radically transforming new product development. I am not dismissing the disruptions that will materialize with AI. They are real, and they are accelerating.
But before we model the apocalypse, we should ask a simpler question: Why does a business exist?
The doomsday scenario treats businesses as employment containers. AI empties the container, wages vanish, spending collapses, the economy spirals.
But businesses do not exist just to employ people.
A business exists to solve problems to make a real human being’s life, another company’s operations, or a public institution’s services measurably better. The jobs, the org charts, the software subscriptions, the office leases – these are the tools that happened to be necessary. However, they are not the purpose of business.
Solving real problems is the purpose.
And the problems are not going away.
We can all think of hundreds of ideas that would improve every business we interact with today. Problems that exist right now that never get fixed because there are not enough hours, people, or budget to address them.
The reports nobody builds. The data analysis that nobody performs. The processes which nobody optimizes. The customer experiences nobody improves. The integrations nobody wires up. Multiply that across every business in the economy and you have an almost incomprehensible amount of work waiting to be done.
If you are worried about AI taking your job, try this exercise. Sit down for one hour with a pen and paper. Write down every problem you can see that needs solving, in your company, your industry, your community, the public institutions you interact with. You will run out of time long before you run out of problems.
The displacement narrative assumes businesses will respond to AI by cutting. This is a failure of imagination dressed up as financial analysis. The companies that win will be the ones that use AI to solve more problems, drive more value, serve more customers, and grow. The challenges have always been there. The promise of AI is what finally makes it possible to attack them.
There is also something the models consistently undervalue: relationships. Businesses are not spreadsheets. They run on trust, built through human connection over time. AI cannot build those relationships. It cannot sit across the table from a CEO and help them see a path forward. It cannot read the room in a difficult board meeting. It cannot earn trust through years of showing up and delivering.
The relational fabric of business is not friction waiting to be optimized away. It is the foundation on which great enterprises are built.
Some of what passes for “relationships” in business is indeed friction with a friendly face. AI will rightly displace those. But genuine relationships, the kind that hold companies together through crises, that attract and retain the best talent, that create the trust required for large and complex transactions, those become more valuable, not less, in a world saturated with machine-generated output.
When anyone can produce competent work with AI, the differentiator is the person you trust to direct it.
Now, let's be honest about who does get hurt. AI is a massive amplifier. It makes the best people dramatically more productive.
But it also exposes those who were coasting.
When AI can do this work instantly, the only thing left to evaluate is judgment, initiative, and the ability to identify real problems worth solving. That is not a recession. It is a resorting. This is a real social challenge worth taking seriously, but it is a very different problem than a deflationary spiral.
The doomsday scenario also treats the economy as a closed loop. But economies are open systems. When a person gets laid off and has access to the same AI tools that displaced them, the barrier to starting a business that solves a real problem drops to nearly zero.
You do not need a team of 20 or a $2 million seed round. You need a laptop, an AI subscription, and the ability to see a problem worth solving. The same technology that causes displacement gives displaced workers unprecedented tools to create new value.
There is something else worth acknowledging. The labor displacement narrative is deeply intertwined with the AI hype cycle. Many companies have over-invested in AI and need to show returns.
The story that AI replaces all your employees is, in part, a sales pitch – one that drives urgency, inflates valuations, and fuels the spending cycle. The incentives to dramatize disruption are enormous.
That does not mean the disruption is not real.
But the framing that it leads inevitably to economic collapse, serves the interests of those selling the infrastructure as much as it reflects reality.
We will solve difficult problems that have plagued industries for decades. There will be lost jobs and there will be new jobs. AI will do many things better than humans currently do. But the universe of unsolved problems is so vast, and the cost of attacking them is dropping so fast, that the constraint will not be “what is there left to do?” It will be “who has the initiative to go do it?”
The advice is simple. Take a deep breath. Learn about these technologies. Be intellectually curious. Build the relationships that machines cannot replicate. Look at your organization and identify every problem and opportunity you can. Then start attacking them with AI as your lever and human judgment as your compass.
There is an enormous amount of work left to do. Ignore the fear. Ignore the hype. Get to work.
For more insights from Darling Consulting Group, click here.
Justin Bakst is the Executive Director of Products & Solutions at Darling Consulting Group. He is passionate about providing education and strategic consultation to financial institutions using DCG’s analytics solutions.
Justin has experience driving value in large public organizations and lean AI startup firms. He has over 25 years of experience in banking, and holds an undergraduate degree from Bentley College and an MBA from Babson College.
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