Financial, Operational Disappointments More Likely To Slow AI Than Politics

The growing public opposition to AI generally and to the data centers that power them have understandably garnered most of the attention around technology now. 

But it is the financial and operational questions which remain unanswered that are most likely to slow AI's growth in the near term. The poll results on the left from a survey of CIO (Chief Information Officer) magazine reveal how 'aspirational' - to put it politely - those hoped-for outcomes remain after four years. The strain on tech companies' financials, the bond market melt-down and the 'murky' return on investment from historically extraordinary infrastructure and AI implementation investments all point to the growing demand for a pause until the uncertainty which business abhors becomes a more well-defined path to profitability. JL

Asa Fitch reports in the Wall Street Journal:

There is some chance that political forces could slow AI’s development. Anti-AI sentiment is becoming increasingly serious, and moratoria on data-center development in the U.S. are growing. Even so, the prospect of political action that actually holds back the development of AI seems distant at best. The more likely scenario is that the natural forces of the boom slow it. AI is putting major strains on the U.S. power grid and raising electricity prices. AI spending is encountering more resistance. Some big tech companies that have fueled the boom are free-cash-flow negative because of their AI outlays. Prices of corporate bonds linked to AI are falling as tech companies raise more debt to grow their infrastructure. And returns on AI spending are still murky nearly four years into the boom. Development will have to slow if it becomes clearer that companies can’t make back what they are spending.

Concerns about AI’s social impact have been growing since the boom began. As real as those are, physical and financial limits are more likely to slow AI’s march.

Warnings against job losses and other social ills have intensified lately. Anthropic in June suggested AI labs consider slowing down development efforts over social-impact concerns. Old-guard tech billionaire Bill Gates wrote in a long essay last week that AI was moving faster than society could adjust to job displacement and other problems it creates.

“I believe we need time to prepare for the period of social, political, and economic upheaval we are about to enter,” he wrote, proposing a tax on robots and AI tokens.

Yet the leading AI labs and Big Tech AI spenders have big incentives keep pushing forward.

Sure, they are concerned enough about cybersecurity threats posed by some of their most advanced models to slow down and adjust. But Anthropic and OpenAI are racing toward IPOs. They are gambling billions of dollars of investors’ money on the notion that AI isn’t only socially transformative, but is a viable, profitable business. Big-tech companies like Alphabet and Meta Platforms also have too much staked on AI to step back.

There is some chance that political forces could slow AI’s development. Anti-AI sentiment is becoming increasingly serious, and moratoria on data-center development in the U.S. are growing.

At the Federal level, a bill introduced in Congress in July would give the government the power to shut down rogue AI models. Other bills have proposed studying AI’s impact on jobs.

Even so, the prospect of political action that actually holds back the development of leading AI models seems distant at best. President Trump this week took to social media to blast people who resist data centers, placing his administration firmly on the pro-development side. That is significant given the largest data-center project in the world is set to be built on Federal land.

China acts as another deterrent for any AI slowdown. China wouldn’t take its foot off the gas if the U.S. held its companies back. As long as AI continues to be a crux of geopolitical competition, giving Chinese companies time to catch up in the AI race isn’t a palatable option for the U.S.

Circumstances, of course, could change in ways that raise the urgency of a forced slowdown. If AI-linked job losses start to sweep through the global workforce, for example, there may be more to be gained politically from a pause.

The more likely scenario is that the natural forces of the boom slow it down anyway. AI is already putting major strains on the U.S. power grid and is raising electricity prices, which is one reason why pauses on data-center projects have legs politically.

AI spending is also encountering more resistance. Some of the big tech companies that have fueled the boom are free-cash-flow negative because of their AI outlays. Prices of corporate bonds linked to AI are falling as tech companies gear up to raise more debt to grow their computing infrastructure.

And returns on AI spending are still murky nearly four years into the boom. It may take time, but development will have to slow if it becomes clearer that companies can’t make back what they are spending.

The social impact of AI is real. For AI developers and investors, though, dollars and cents are what ultimately will matter.