SynopsisThe finance industry is rapidly adopting AI, but soaring costs for computing power and AI assistants like Claude are creating financial strain. This is prompting a shift towards building in-house models and potentially industry consolidation, as firms question the long-term pricing and dependence on US tech giants.AgenciesRepresentative imageThe finance industry’s love of artificial intelligence has reached fever pitch — even in Europe, that traditional tech laggard. Beyond headline-grabbing announcements at HSBC Holdings Plc, or tin-eared ones from Standard Chartered Plc, ask any fund manager, banker or trader and you’re likely to hear stories of increasing adoption and experimentation.Examples range from the humdrum to finance’s brainier realms: Compiling analyst recommendations into a personal automated rating system; training a chatbot in portfolio allocation ideas that don’t just give the same idea in three different ways; and the heavy lifting on writing code for whizzy quant traders.Also read: JPMorgan rolls out AI tools in investment banking globally, senior banker saysBut if there’s a catch right now, it’s cost. Supply constraints are pinching all parts of the AI ecosystem, particularly computing power. Users of Anthropic PBC’s popular AI assistant, Claude, are grumbling about soaring prices. Even Anthropic’s recent deal with SpaceX to increase its processing capacity hasn’t fully absorbed demand from its customers for expensive, computation-hungry tasks. Ergo, the price keeps going up.Financiers’ gripes about the cost of Claude — a favorite for banker geeks — are starting to sound like those from the tech industry. The bill is on track to rise from tens of thousands of dollars for a single firm to several million. Rampant demand from white-collar types is, of course, a good problem to have for companies like Anthropic who can impose price rises that might start to justify the AI industry’s epic losses and hype-fueled valuations. Dario Amodei’s company is on track for its first profitable quarter and is mulling a stock-market listing as early as October.BloombergBut the rapid adoption of AI agents, which can perform tasks independently, and their soaring expense create new quandaries for finance customers even as they can see the advantages. This adds to pressure on a firm’s profitability and is driving cost cuts in other parts of these businesses. It creates fears, too, of being handcuffed to particular AI companies as core IT skills shift to outside suppliers, usually American.No wonder the boss of StanChart touched a nerve with his ill-judged comments about “lower-value” human capital giving way to financial and investment capital as part of the bank’s AI push. It could be construed as salaried employees paying the price for the technology’s increasingly high costs. As one analyst put it to the bank: “The AI companies of today are not making any money and are spending a lot… Is it a problem that we don’t really know how they’ll be charging in a year or two from now?”The behavior of banks and other financial users are likely to evolve. Indeed, we may already be moving away from a “token-maxxing” mindset — whereby heavy spending on AI processing power is a badge of honor regardless of whether it’s wasted — into a more grown up phase, according to users and analysts. I’ve been told of several examples where financial services are shifting to building in-house models for tasks that don’t need an all-knowing external LLM.“Not every task needs a frontier model,” says Christopher Tozzi, author of a history on open-source software. That might encourage some surprise corporate thinking. Maybe “lower-value” humans who can build and maintain a chatbot that’s cheaper than an outside one will have a valuable skill.Also read: Corporate India closing interview doors to prying AIsFinance firms might even do the unimaginable and club together, to better absorb AI costs from without and to share expertise on in-house models. This industry has never been good at sharing tech or data, with banks and asset managers usually trying to get one up on their rivals. Nor has it been good at cross-border mergers that make sense but are politically difficult, such as UniCredit SpA’s tilt at Commerzbank AG. Maybe AI is the catalyst that will revolutionize capital allocation and finally consolidate the industry, especially in Europe’s overbanked parts. Perhaps UniCredit’s boss Andrea Orcel should show German Chancellor Friedrich Merz the banks’ expected AI budgets.For now, few anticipate that Anthropic’s or OpenAI’s competitive moats will be crossed anytime soon. AI evangelists are probably right that the fear of missing out is strong enough today that any chance of an edge against a competitor will keep the finance crowd spending. Tech expenditure by governments and companies is set to rise almost 8% in 2026, the biggest increase in years, according to Forrester data. There are some parallels with cloud computing, where firms started building some stuff in-house without doing too much harm to the profits of Silicon Valley and Seattle. And, of course, AI is deepening Europe’s geopolitical dependence on US tech giants such as Amazon.com Inc.But having seen some users successfully experiment with creating their own models, reducing though not eliminating the spending burden, I do wonder if this time there will be more pressure to avoid outsourcing too much too quickly. Lost in the furor around Bill Winters’ AI comment was a more cautious line: “We are... being very, very thoughtful on the cost of AI.” If that encourages more European corporate self-help, so much the better.(Views expressed in this column are those of Bloomberg author's & do not represent the opinion of EconomicTimes.com)Read More News on