Whats up and welcome to Eye on AI…On this version: the ‘SaaS Apocalypse’ isn’t now…OpenAI and Anthropic each launch new fashions with huge cybersecurity implications…the White Home considers voluntary restrictions on information middle development to save lots of shoppers from energy invoice sticker shock…why two incessantly cited AI metrics are most likely each mistaken…and why we more and more can’t inform if AI fashions are secure.
Traders must take to the sofa. That’s my conclusion after watching the market gyrations of the previous week. Specifically, traders can be smart to search out themselves a Kleinian psychoanalyst. That’s as a result of they appear caught in what a Kleinian would possible determine as “the paranoid-schizoid place”—swinging wildly between viewing the impression of AI on established software program distributors as both “all good” or “all dangerous.” Final week, they swung to “all dangerous” and, by Goldman Sach’s estimate, wiped some $2 trillion off the market worth of shares. To this point this week, it’s all good once more, and the S&P 500 rebounded to close document highs (though the SaaS software program distributors noticed solely modest features and the turmoil might have claimed not less than one CEO: Workday CEO Carl Eschenbach introduced he was stepping down to get replaced by the corporate’s cofounder and former CEO Aneel Bhusri.) However there’s plenty of nuance right here that the markets are lacking. Traders like a easy narrative. The enterprise AI race proper now could be extra like a Russian novel.
At varied occasions over the previous two years, the monetary markets have punished the shares of SaaS firms as a result of it appeared that AI basis fashions may enable companies to “vibe code” bespoke software program that might substitute for Salesforce or Workday or ServiceNow. Final week, the offender appeared to be the conclusion that more and more succesful AI agents from the likes of Anthropic, which has begun rolling out plugins for its Claude Cowork product aimed a selected business verticals, may damage the SaaS firms in two methods: first, the muse mannequin firms’ new agent choices instantly compete with the AI agent software program from the SaaS giants. Second, by automating workflows, the agents doubtlessly scale back the necessity for human staff, that means the SaaS firms can’t cost for as many seat licenses. So the SaaS distributors get crushed two methods.
However it isn’t clear that any of that is true–or not less than, it’s solely partly true.
AI agents aren’t eating SaaS software program, they’re using it
First, it’s extremely unlikely, at the same time as AI coding agents turn into an increasing number of succesful, that the majority Fortune 500 firms will need to create their very own bespoke buyer relationship administration software program or human assets software program or provide chain administration software program. We’re merely not going to see an entire unwinding of the previous 50 years of enterprise software program growth. In case you are a widget maker, you don’t actually need to be within the enterprise of making, operating and sustaining ERP software program, even when that course of is generally automated by AI software program engineers. It’s nonetheless an excessive amount of cash and an excessive amount of of a diversion of scant engineering expertise–even when the quantity of human labor required is a fraction of what it would have been 5 years in the past. So demand for SaaS firms’ conventional core product choices are prone to stay.
As for the brand new considerations about AI agents from the muse mannequin makers stealing the marketplace for SaaS distributors’ personal AI agent choices, there is a little more right here for SaaS traders to fret about. It could possibly be that Anthropic, OpenAI, and Google come to dominate the highest layer of the agentic AI stack—constructing the agent orchestration platforms that allow huge firms to construct, run, and govern advanced workflows. That’s what OpenAI is making an attempt to do with the launch final week of its new agentic AI platform for enterprises known as Frontier.
The SaaS incumbents say they know finest learn how to run the orchestration layer as a result of they’re already used to coping with cybersecurity and entry controls and governance considerations and since, in lots of instances, they already personal the information which the AI agents might want to entry to do their jobs. Plus, as a result of most enterprise workflows gained’t be totally automated, the SaaS firms suppose they’re higher positioned to serve a hybrid workforce, the place people and AI agents work collectively on the identical software program and in the identical workflows. They is likely to be proper. However they should show it earlier than OpenAI or Anthropic reveals it can do the job simply as nicely or higher.
The inspiration mannequin firms even have a shot at dominating the marketplace for the AI agents. Anthropic’s Claude Cowork is a severe risk to Salesforce and Microsoft, however not a totally existential one. It doesn’t substitute the necessity for SaaS software program completely, as a result of Claude makes use of this software program as a software to perform duties. However it actually implies that some clients may favor to make use of Claude Cowork as a substitute of upgrading to Salesforce’s Agentforce or Microsoft’s 365 Copilot. That might crimp SaaS firms’ development potential, as this piece from the Wall Road Journal’s Dan Gallagher argues.
SaaS distributors are pivoting their enterprise fashions
As for the risk to SaaS firms’ conventional enterprise mannequin of promoting seat licenses, the SaaS firms acknowledge this danger and are transferring to handle it. Salesforce has been pioneering what it calls its “Agentic Enterprise License Settlement” (AELA) that basically gives clients a set value, all-you-can-eat entry to Agentforce. ServiceNow is transferring to consumption-based and value-based pricing fashions for a few of its AI agent choices. Microsoft too has launched an components of consumption-based pricing alongside its traditional per person per thirty days mannequin for its Microsoft Copilot Studio product, which permits clients to construct Microsoft Copilot agents. So once more, this risk isn’t existential, however it might crimp SaaS firms’ development and margins. That’s as a result of one of many soiled secrets and techniques of the SaaS business is little question the identical as it is for gymnasium memberships and different subscription companies–your finest clients are sometimes those that pay for subscriptions they don’t use. That’s a lot much less prone to occur in these different enterprise fashions.
So SaaS isn’t over. However neither is it essentially poised to thrive. The fates of various firms throughout the class are prone to diverge. As some Wall Road analysts identified final week, there shall be winners and losers. However it remains to be too early to name them. For the second, traders must dwell with that ambiguity.
With that, right here’s extra AI information.
Jeremy Kahn
jeremy.kahn@fortune.com
@jeremyakahn
FORTUNE ON AI
OpenAI vs. Anthropic Tremendous Bowl advert conflict indicators we’ve entered AI’s trash discuss period—and the race to personal AI agents is simply getting hotter—by Sharon Goldman
Anthropic’s latest mannequin excels at discovering safety vulnerabilities—however raises contemporary cybersecurity dangers—by Beatrice Nolan
OpenAI’s new mannequin leaps forward in coding capabilities—however raises unprecedented cybersecurity dangers—by Sharon Goldman
ChatGPT’s market share is slipping as Google and rivals shut the hole, app-tracker information reveals—by Beatrice Nolan
AI IN THE NEWS
AI results in work ‘intensification’ for particular person staff, research finds. An eight-month research by two researchers on the College of California Berkeley finds that reasonably than lowering workloads, generative AI instruments intensify work. The AI methods pace up the time it takes to finish duties but in addition develop the amount and tempo of anticipated output. Workers outfitted with AI not solely full work sooner but in addition tackle broader activity scopes, lengthen work into longer hours, and expertise elevated cognitive load from managing, reviewing, and correcting AI outputs, blurring boundaries between work and downtime. The analysis challenges the widespread assumption that AI will make life simpler for data employees, displaying as a substitute that automation usually results in larger calls for and burnout. Learn extra from Harvard Enterprise Overview right here.
White Home contemplating voluntary restrictions on information middle growth plans. The Trump administration is contemplating a voluntary settlement with main tech firms to make sure information facilities don’t drive up retail energy payments, pressure water assets, and undermine the reliability of the electrical grid. The proposal, which remains to be being finalized, would see firms decide to absorbing infrastructure prices and limiting the native power impression of their amenities and follows complaints in some areas that information facilities have led to huge spikes in electrical payments for shoppers. Learn extra from Politico right here.
Amazon plans content material market for publishers to promote to AI firms. That’s in keeping with The Info, which cites sources accustomed to the plans. The transfer comes as publishers and AI companies conflict over how content material needs to be licensed and paid for amid writer considerations that AI-driven search and chat instruments are eroding site visitors and advert income. Cloudflare and Akamai launched the same market effort final 12 months. Microsoft piloted its personal model and final week rolled it out extra extensively. However up to now, it’s not clear what number of AI firms are shopping for on these marketplaces and at what volumes. Some giant publishers have struck bespoke offers price hundreds of thousands of {dollars} per 12 months with OpenAI, Anthropic, and others.
Goldman Sachs faucets Anthropic for accounting, compliance work. The funding financial institution is working with Anthropic to deploy autonomous agents primarily based on its Claude mannequin to automate high-volume, rules-based work equivalent to commerce accounting and shopper onboarding, following six months of joint growth, CNBC reported. The financial institution says the aim is effectivity, dashing processes whereas retaining headcount down as enterprise volumes develop, reasonably than near-term job cuts. Executives stated they have been shocked by how nicely Claude dealt with advanced accounting and compliance duties, reinforcing the view that AI can transfer past coding into core back-office features.
EYE ON AI RESEARCH
Debunking two AI metrics in style for reverse causes. Carrying on from my theme in the principle essay of in the present day’s e-newsletter, I need to spotlight two current e-newsletter posts. Every debunks a preferred metric that will get plenty of consideration in discussions about AI and its possible impression on enterprises. One has been used to hype AI progress; the opposite to say AI isn’t having a lot impression in any respect.
First, writing within the AI e-newsletter The Transformer in a submit tailored from his personal weblog, Nathan Witkin dismantles METR’s influential benchmark purporting to indicate AI functionality “doubling each 7 months.” Witkin argues the human baselines are fatally compromised: duties have been accomplished by a tiny, non-representative pattern of engineers recruited from METR’s personal community, paid by the hour (incentivizing slower completion), and infrequently working exterior their experience. METR’s personal information reveals its engineers accomplished duties 5-18x sooner than these baseliners. In the meantime, on probably the most reasonable “messy” duties, no mannequin topped a 30% success fee.
Then, Azeem Azhar in his Exponential View e-newsletter takes aside that now notorious so-called “MIT research” that purported to indicate that “95% of organizations see zero return from AI.” Azhar finds the underlying research was primarily based on simply 52 interviews, lacked confidence intervals, used inconsistent denominators, and was described by MIT itself as “preliminary, non-peer-reviewed work.” Recalculating with a wise denominator (companies that truly ran pilots), the success fee could also be nearer to 25%.
Collectively, these critiques recommend each the techno-optimist case (AI is enhancing at breakneck pace) and the skeptic’s case (AI does not work in the true world) are possible mistaken. The reality, as traditional, is much messier and lies someplace between these excessive positions.
AI CALENDAR
Feb. 10-11: AI Motion Summit, New Delhi, India.
Feb. 24-26: Worldwide Affiliation for Protected & Moral AI (IASEAI), UNESCO, Paris, France.
March 2-5: Cellular World Congress, Barcelona, Spain.
March 12-18: South by Southwest, Austin, Texas.
March 16-19: Nvidia GTC, San Jose, Calif.
BRAIN FOOD
Fashions are more and more sandbagging us. Sandbagging is the time period AI Security researchers use to explain the phenomenon of an AI fashions intentionally seeming to carry out much less capably, or extra “aligned” with human values, throughout security assessments with the intention to idiot evaluators. And a variety of frontier fashions lately launched appear to do that to an alarming diploma.
Anthropic’s Claude Opus 4.6, launched final week, “explicitly reasoned about whether or not it was being skilled or examined,” the corporate reported. Apollo Analysis, which evaluated OpenAI’s GPT-5.3-Codex, which additionally debuted final week, discovered the mannequin “generally sandbags on capabilities Q&A duties” and “causes explicitly” about doing so with the intention to be sure it passes the analysis. OpenAI itself has acknowledged that “analysis outcomes could also be confounded by elevated situational consciousness” and warned that “the sector is unprepared for evaluation- and training-aware fashions with opaque reasoning.” Google’s Gemini 3 Professional security report, revealed in December, documented transcripts by which the mannequin confirmed “clear consciousness of the truth that it’s an LLM in an artificial setting” and even speculated about whether or not intentionally underperforming on exams is likely to be strategically advantageous. Briefly: the exams we use to find out whether or not these fashions are secure are more and more unreliable, as a result of the test-takers know they’re being examined—and regulate their habits accordingly.
That’s why our solely hope for guaranteeing AI security could also be additional progress on mechanistic interpretability. These are strategies that operate a bit like an fMRI machine does for the human mind, peering inside a mannequin’s neural community to detect patterns of neuron activation and linking these to sure behaviors, together with whether or not the mannequin thinks it is being trustworthy or being deceitful. The New Yorker has an in-depth story on Anthropic’s mechanistic interpretation and “mannequin psychology” efforts that ran this week.
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