TSLA345.130-5.99%
GM86.1501.19%
F14.005-0.495%
RIVN16.0100.28%
CYD38.710-4.73%
HMC32.6000.69%
TM192.2403.46%
CVNA71.5861.146%
PAG216.550-1.31%
LAD370.670-0.84%
AN200.090-0.43%
GPI263.820-0.05%
ABG215.3702.43%
SAH77.780-1.08%
TSLA345.130-5.99%
GM86.1501.19%
F14.005-0.495%
RIVN16.0100.28%
CYD38.710-4.73%
HMC32.6000.69%
TM192.2403.46%
CVNA71.5861.146%
PAG216.550-1.31%
LAD370.670-0.84%
AN200.090-0.43%
GPI263.820-0.05%
ABG215.3702.43%
SAH77.780-1.08%
TSLA345.130-5.99%
GM86.1501.19%
F14.005-0.495%
RIVN16.0100.28%
CYD38.710-4.73%
HMC32.6000.69%
TM192.2403.46%
CVNA71.5861.146%
PAG216.550-1.31%
LAD370.670-0.84%
AN200.090-0.43%
GPI263.820-0.05%
ABG215.3702.43%
SAH77.780-1.08%


Could AI break the economy before it fails?

Welcome back to the latest episode of The Future of Automotive on CBT News, where we put recent automotive and mobility news into the context of the broader themes impacting the industry. 

I’m Steve Greenfield from Automotive Ventures, and I’m glad that you could join us.

This week on The Future of Automotive, we reflect back on a pair of recent warnings from the worlds of technology and finance — both asking the same unsettling question: what if artificial intelligence doesn’t fail… but succeeds so quickly that it begins to destabilize the economy itself?

One widely discussed essay from Citrini Research imagines a near-future scenario where AI drives massive gains in productivity and corporate profits — while simultaneously eliminating large numbers of white-collar jobs. The result, the authors argue, could be something they call ‘Ghost GDP’ — economic growth that shows up in the data, but doesn’t translate into real spending power because fewer people are earning wages.

In that scenario, companies use AI to cut costs, reinvest those savings into more AI, and trigger a feedback loop of further job displacement — a cycle that could push unemployment higher even as output rises.

But a second, equally provocative idea from investor Chamath Palihapitiya is now gaining traction in investor circles — and it goes even deeper.

 What if AI doesn’t just disrupt jobs… but breaks the very way we value companies?

A new thought experiment argues that modern markets depend on a simple assumption: that competitive advantages last. That companies can build ‘moats’ — durable edges that allow profits to grow for years, even decades.

But if AI dramatically lowers the cost of disruption — and speeds up innovation — those moats may no longer hold.

In that world, no company can confidently predict its earnings even five or ten years out, because by then, it may already have been disrupted by a faster, cheaper, AI-driven competitor.

And if the future becomes that uncertain, markets may simply stop paying for it.

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Instead of valuing companies based on long-term growth, investors could begin pricing them based only on what they earn right now — treating businesses less like enduring franchises… and more like assets with a short shelf life.

We’ve seen versions of this before. Newspapers, retail chains, even taxi medallions — all once-profitable businesses that were rapidly repriced when markets realized their future cash flows had an endpoint.

But this time, the argument is that AI could apply that same logic — not to one sector at a time — but to the entire economy, all at once.

The implications are enormous.

Growth investing — the idea of sacrificing profits today for dominance tomorrow — could break down. Venture capital could shrink dramatically. And trillions of dollars in market value, much of it tied to long-term expectations, could simply evaporate.

At the same time, capital might shift away from technology and into physical assets — things like energy infrastructure, farmland, or commodities — areas seen as less vulnerable to digital disruption.

 And there’s a deeper paradox here.

The companies building AI are investing hundreds of billions of dollars into long-term infrastructure — bets that only make sense if future profits are predictable.

But if markets stop believing in that future, those investments themselves could become harder to finance… potentially slowing the very AI boom that caused the disruption in the first place.

Now, to be clear — both of these are thought experiments, not forecasts.

But together, they highlight a growing concern across Wall Street and Silicon Valley: that AI may not just reshape industries… it may challenge the underlying assumptions about how economies grow, how companies compete, and how markets assign value.

And that raises the question at the center of all of this:

If the future becomes harder to predict… harder to trust… and harder to price…

What happens to a system built on believing in it?

So, with that, let’s transition to Our Companies to Watch.

Every week we highlight interesting companies in the automotive technology space to keep an eye on. If you read my weekly Intel Report, we showcase a company to watch, and take the opportunity here on this segment each week to share that company with you.

Today, our new company to watch is SparkServ.

SparkServ’s Service BDC Hub and AI-Agent empower automotive dealers to boost net profits, increase CSI, and ensure that their service bays are always full. 

Dealers can optimize their BDC with a data-driven approach that provides actionable insights and AI-powered support.

Spark’s product offerings can alleviate pain points for your BDC agents and customers, increasing volume and retention in your service drive.

If you’d like to learn more about SparkServ, you can check them out at www.SparkServ.com


So that’s it for this week’s Future of Automotive segment. 

If you’re an AutoTech entrepreneur working on a solution that helps car dealerships, we want to hear from you. We are actively investing out of our new Mobility Fund.

Don’t forget to check out my two books, The Future of Automotive Retail and The Future of Mobility, both available on Amazon.com.

Thanks (as always) for your ongoing support and for tuning into CBT News for this week’s Future of Automotive segment. We’ll see you next week!


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