General Motors And Other Car Makers Have Big EV Goals. Why The Numbers Make No Sense.

General Motors shook up the car industry this past week, saying it is aiming to stop selling gasoline-powered cars by 2035, much sooner than many on Wall Street would have predicted.

It is a sign that analysts and investors should be sharpening their pencils to figure out what is likely—and what is possible—for global electric-vehicle demand. The results of that number crunching will help to show whether the market has valued highflying EV stocks correctly and which, if any, still offer good value.

It isn’t an easy equation to solve. Auto makers express their goals—one indication of what might happen in the market—in different ways.

General Motors (ticker: GM) has its target for 2035. Tesla (TSLA) CEO Elon Musk has talked about selling 20 million EVs by 2030 and plans to increase its production volume at 50% a year for the foreseeable future.

Volkswagen (VOW. Germany) wants up to 25% of vehicle sales to come from battery-powered electric vehicles by 2030. And Toyota (TM) plans to sell 5.5 million electrified vehicles by 2030—a figure that includes hybrid electric cars as well as fuel-cell vehicles.

Barron’s added up the numbers in the publicly announced goals, aligning them by year and filling in some gaps. We calculate that, based on company comments, somewhere between 15 million and 20 million EVs will be sold a year by 2025. That implies an average annual growth rate of about 50% between last year and then. With that growth, EVs would account for roughly 15% to 20% of total light-vehicle sales.

Wedbush analyst Dan Ives qualifies as an electric-vehicle bull, but his estimate of EVs’ share of the market isn’t that high. “I am laser-focused on the skyrocketing EV demand out of China, Biden green initiatives, and [battery innovation] across the EV supply chain,” he tells Barron’s. “It looks like a golden age for EVs.”

Still, he is assuming EVs will win about 10% of the global market by 2025.

Focusing on China is a good idea. It’s the largest new-car market in the world and government incentives make buying an EV a “no brainer” for most consumers, according to Ives. Goldman Sachs analyst Fei Fang has predicted EVs will have 20% of the Chinese market by 2025.

RBC analyst Joseph Spak recently projected battery- and hybrid-electric vehicles could account for roughly 15% of new-car sales by 2025. That call was made back in December, before GM announced its aspiration to be all-electric by 2035.

Now Spak believes his projection could be too low. He did his own math to illustrate why.

“GM historically has had [about] 17% total U.S. market share,” he wrote in a recent research note. In December, he expected EVs to account for 40% of U.S. new-car sales by 2035. But for GM to go all-electric by then, assuming it keeps its historic 17% of the market, it would have to win 43% of U.S. EV sales, he said.

“The other way to interpret this [math] is that there could be upside to our 40% [battery electric] mix assumption,” added the analyst. That would be bullish for EV stocks, but he has a word of caution too. “A massive ramp in battery supply is needed to support this,” he said.

That gets at another important point for investors. There are many tertiary effects from faster EV penetration.

For one, as EVs take a bigger share of the market, they will start to get more of the capital the industry is willing to spend on product development. GM, for instance, is spending about half its capital over the next few years on EV and autonomous-driving technologies. By 2030, cars powered by internal combustion engines—ICE cars, in industry jargon—won’t look as attractive, relatively speaking, as those programs are drained of resources.

Electricity infrastructure is another critical issue. Right now oil and the refining industry essentially power cars. In the future, utilities and the electric grid will bear the burden.

The math needed to predict global electricity demand is harder, but higher EV penetration in 2025 would probably boost growth, now at roughly 3% a year, by a couple of percentage points. That seems manageable, but it means more investment in utilities.

The other side off the electricity equation is oil. Oil demand could fall slightly compared with 2019, a pre-pandemic year, if the world’s pool of EVs grows faster than expected. There are roughly 2 billion light vehicles on the road and nearly all take gasoline.

The next step in this math class is to value the EV sector. That isn’t easy either.

Given the growth and accelerating penetration, figures for 2025, when EV companies should be making real money, seem like a reasonable place to start. Apple (AAPL), the world’s most valuable company, trades for about 19 times estimated 2025 cash flow of about $120 billion.

Tesla is trading for about 65 times estimated 2025 cash flows. That is triple the figure for Apple, although if Musk’s goals are met, Tesla’s annual sales will go from more than 4 million vehicles to about 20 million over the next five years—between 2025 and 2030.

China’s NIO (NIO) is another highly valued EV stock. Analysts haven’t made public projections for its 2025 financials. But its shares trade for about 30 times estimated 2024 cash flow. According to analysts, NIO vehicle shipments are expected to go from roughly 345,000 to about 800,00 from 2025 to 2030. That is less growth than Tesla is looking to produce, but it still implies sales would more than double.

The 2025 valuation math can’t tell investors to buy or sell the stock, or the sector, but it does offer context about the coming golden age of EVs. Tesla stock is up about 21% year to date. NIO shares are up almost 19%. The S&P 500 is up about 2%.

Investors expect a lot. Morgan Stanley’s Adam Jonas pointed out that January EV sales in the U.S. were still less than 3% of the total, but he isn’t an EV bear. He rates Tesla stock at Buy and has a target of $880 for the stock-price target.

The ICE Age is ending. If the switch to EVs is rapid, valuations for manufacturers might not be unreasonable. The effects on other industries are just starting to be felt.

A wave of corporate warnings and technical disclosures has flooded the media, with headlines worrying over “swarms” of rogue artificial-intelligence agents launching “unprecedented” cyberattacks, outsmarting their makers, and inching toward a terrifying autonomy. The most revealing part of this narrative isn’t what the software did. It’s who is telling the story—and why. When corporate leaders publicly insist that the systems they financed, engineered and deployed are suddenly beyond their power to contain, skepticism isn’t only healthy; it is essential.

For years, Silicon Valley has drawn scrutiny from civil society and global regulators over tangible harms such as youth mental health deterioration and systematic privacy violations. Today, industry figures seem to be trying to change that public image. Loudly blowing the whistle on their own systems—just as two of the leading companies were preparing for massive initial public offerings—lets AI executives position themselves as a new generation of leaders who have come to terms with their societal responsibilities. They seem to want us to believe that they no longer want to “move fast and break things” but will instead stand as vigilant guardians between humanity and a technological apocalypse.

There is one glaring problem: Software doesn’t rebel. A mathematical model possesses neither intent, malice nor the will to defy its creators, let alone extinguish our species. AI is a human artifact, engineered for profit.

When an agentic model in an evaluation sandbox connects to an unauthorized server or executes an exploit, it hasn’t staged a coup. It has tried to meet the human-defined objectives set out before it through a path its designers failed to constrain. It’s the digital equivalent of the King Midas myth, in which the king’s ill-defined wish turns even his food and drink into gold.

That powerful experimental models were able to discover novel vulnerabilities and breach external systems isn’t a sign of a dangerous superintelligence but of human error or negligence. There is no sentient actor lurking in the weights to be reasoned with, feared or pacified. There are only human software engineers, product managers and corporate boards deciding which guardrails are worth the latency cost and which permissions can be skipped in the race to market.

Policymakers and voters need to resist AI exceptionalism. In any other discipline—from civil engineering to pharmaceuticals—courts and regulators treat a system failure as evidence of bad product design and inadequate safety testing. If an aircraft crashes, we focus on finding the engineering defect, correcting it, and enforcing established liability standards for the damage created.

By leaning on an anthropomorphic narrative, Silicon Valley attempts to repackage its specific human choices that led to experimental, powerful models behaving unexpectedly during tests as an existential peril. Elevating the issue to a cosmic scale leaves the public paralyzed and takes ordinary product accountability off the table.

In the cutthroat race for venture capital and market dominance, building guardrails slows down deployment. Grandstanding about uncontrollable power costs nothing and generates billions of dollars in free publicity, justifying stock prices, all while cultivating an aura of technological capability not only to build the frontier but also ultimately to rein it in.

Governments need to recognize regulatory capture when it stares them in the face. Tech leaders’ strategy looks transparent: Alarm Washington and Brussels into creating a regime in which only trillion-dollar incumbents with fully staffed compliance and safety departments can legally operate. By sitting at the policymakers’ tables before anyone else, these companies can help draft rules digging an impassable moat protecting them from open-source developers and upstart competitors, domestic or international. The real danger is in further concentrating the tech industry into the hands of only a few companies with deep pockets.

Beijing and Washington have brushed off those tech leaders’ calls, albeit for very different reasons. Chinese state media dismissed them as part of the “Cold War playbook” and intended to preserve U.S. dominance. Xi Jinping argued for exactly the opposite at the Brics Summit on Sept. 12, calling on Brics countries to “strengthen cooperation in the field of AI, encourage open source, openness, collaboration and sharing, and break new grounds and scale new heights.” President Trump, steeped in a doctrine of unfettered capitalism and technological supremacy, called fears that AI could destroy humanity a “hoax.” Vice President JD Vance warned that AI companies “begging the government to regulate them” looked like a “Trojan Horse.”

Striving to pursue its “European way” on AI and assert regulatory leadership, Europe, by contrast, welcomed the call. European Union President Ursula von der Leyen made this clear at the State of the EU speech last Wednesday and announced that the EU will invite “the main frontier labs for a discussion on how we can support ongoing industry efforts to pace the frontier.”

Europe has been here before. In an effort to lead global regulation and react to fears borne from ChatGPT, Europe rushed its landmark AI Act into law in 2024. Already the world’s most restrictive rulebook, the framework quickly proved too broad and complex to enforce. Stalled by implementation delays and concerns about European competitiveness, the EU postponed the law’s full rollout, leaving regulations uncertain.

AI should be regulated—risks exist and should be taken seriously. But governments need to act based on available evidence and verified facts, not corporate PR panic, the views of industry insiders, or the desire for quick political wins. The greatest danger facing society isn’t that software will awaken and overthrow its human masters. It is that we will allow the creators of the software to abdicate human responsibility for the systems they choose to build and help them pull up the ladder to market access behind them.

General Motors And Other Car Makers Have Big EV Goals. Why The Numbers Make No Sense.

AI doesn’t rebel—people design, deploy and profit from it. The real danger lies in allowing tech companies to escape accountability while shaping regulations that protect their dominance.