New budgets funded 55% of incremental enterprise AI spending this year, against 22% from software budgets, and only 9%, or $12.6 billion, moved to AI-native vendors, Menlo Ventures said in 2026: The State of Enterprise AI, published on 3 November. By our arithmetic, incumbents kept about 59% of the AI money that came out of software budgets.
Menlo says the report draws on a survey of nearly 400 U.S. enterprise decision-makers responsible for more than $4 billion in AI spending, fielded by Morning Consult from September 8 to 26, 2026. Menlo Ventures is an investor in Anthropic, and the report marks its other portfolio companies with an asterisk.
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The key insight: By our arithmetic, incumbents kept about 59% of the AI money that came out of software budgets in Menlo Ventures’ 2026 estimate: 13 of the 22 points, against 9 points, or $12.6 billion, for AI-native vendors.
The report asks where $176.8 billion of AI deployment spending came from. Its answer: “Mostly new budgets, which funded 55% of incremental AI spend, compared with 22% from software budgets—though even with that, most (13%) stayed with incumbents converting SaaS licenses to AI, like Microsoft Office to Copilot, while only 9% ($12.6B) moved to AI-native vendors, about a 2-point growth headwind for the $600B+ application SaaS market (from +13% last year to +11% this year)”.
Menlo sets the total against cloud: “At $176.8B, AI deployment spend now equals more than 30% of public cloudrevenue, up from just 6% a year ago”.
By our arithmetic, the 13 points that stayed with incumbents are about 59% of the 22 points drawn from software budgets, and the 9 points that went to AI-native vendors are about 41%.
Menlo also found “limited evidence of enterprises replacing core systems such as Salesforce’s CRM, Workday’s HRIS, or Oracle’s NetSuite with AI”. Its conclusion: “AI is significantly expanding the overall software market while modestly slowing growth for traditional SaaS”.
The report frames the open question for incumbents as “whether their new AI products can win enough incremental spend to avoid decelerating growth alongside the SaaS market”.
More Money Goes Into Using AI Than Building It
Menlo writes: “For every $1 the industry spends building AI models, enterprises spend about $1.70 putting them to work”. It estimates $176.8 billion in enterprise spending on using AI, up 5.4x, against $102.5 billion on building models, up 5.3x.
It ties that demand to the cloud buildout: “We estimate that Anthropic and OpenAI alone account for 25%+ of AWS, Azure, and Google Cloud revenue, with much of that spend going to training. That investment only pays off if enterprises keep putting models to work, which agents are now driving”.
Menlo’s 2024 report found “60% of enterprise generative AI investments come from innovation budgets”, with 40% from more permanent budgets, “58% of which is redirected from existing allocations”. Its December 2025 report said 2025 spending was “capturing 6% of the global SaaS market”. The 2026 split covers incremental spending only, so the three reports measure different things.
The Structural Read
As we read Menlo’s split, AI spending grew mostly beside existing software rather than in its place: 55% of incremental spending came from new budgets, and Menlo found limited evidence of enterprises replacing core systems.
As we read the report, the main cost to SaaS is slower growth rather than lost customers: Menlo puts the headwind at about 2 points, from +13% last year to +11% this year, for the $600B+ application SaaS market.
Menlo Ventures, 2026: The State of Enterprise AI
“AI is significantly expanding the overall software market while modestly slowing growth for traditional SaaS.”
Three Implications
FOR SAAS INCUMBENTS Menlo says 13% of incremental AI spend stayed with incumbents converting SaaS licenses to AI, like Microsoft Office to Copilot.
FOR AI-NATIVE VENDORS Menlo says only 9% ($12.6B) moved from software budgets to AI-native vendors.
FOR THE CLOUD BUILDOUT Menlo estimates enterprises spend about $1.70 putting AI to work for every $1 the industry spends building models.
The framework argues: “Salesforce isn’t a CRM; it’s a data layer other systems depend on. Workday isn’t HR software; it’s the canonical source of organizational truth.”
As we read it, Menlo’s finding of limited evidence that enterprises are replacing Salesforce’s CRM, Workday’s HRIS or Oracle’s NetSuite fits that view. The framework is the owner’s argument and does not discuss Menlo’s report.
The 55%, 22%, 13% and 9% are shares of incremental spending, not of all AI spending. The report text does not itemise the remaining share; its key findings name labor budgets as the other existing source.
The $600B+ application SaaS market and its growth rates are Menlo’s figures. Menlo Ventures is an investor in Anthropic, and the report marks its other portfolio companies with an asterisk. We did not contact Menlo, Microsoft, Salesforce, Workday or Oracle.
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Menlo Ventures found that new budgets funded 55% of incremental enterprise AI spending in 2026, while 9%, or $12.6 billion, moved from software budgets to AI-native vendors. By our arithmetic, incumbents kept about 59% of the AI money that came out of software budgets.
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A note on sourcing. The budget shares, spending figures, survey details and quotes come from Menlo Ventures’ 2026 State of Enterprise AI report, published on 3 November 2026, and its 2025 and 2024 reports. The chart is Menlo’s own. The 59% and 41% splits are our arithmetic on Menlo’s figures. Menlo Ventures is an investor in Anthropic and in other companies named in the report. We did not contact Menlo.
Gennaro Cuofano is a CRO and tech executive who has worked in AI since late 2015, starting with bringing NLP, natural-language generation, voice and chatbot products to the marketing industry. His background is in law and finance: he holds a Master's degree in Law and an International MBA with an emphasis on corporate finance (LUISS Business School and the University of San Diego, 2012), and worked as a financial analyst at a real-estate investment firm in San Diego and as an assistant controller. His work focuses on business model strategy, business engineering and, more broadly, structural analysis: how companies make money, read from their own filings. He created FourWeekMBA and leads research there and at The Business Engineer, his newsletter on AI and business strategy, with over 95,000 subscribers and more than 1,000 published analyses. His writing has also appeared on Entrepreneur (for example, How to Digitize a Family Business in Europe) and HackerNoon. Find him on LinkedIn and Substack. See how we source.
