2026年企业软件现状（英）

State of EnterpriseSoftware An Overview of Trends in the Venture-BackedEnterprise Software Sector 2026 Contents 5Macro 11Fundraising and Investment 17Survey Results 22Exits 25Appendix Enterprise Software Looking for RO(AI) The enterprise software industry is entering a new phase, one whereAI adoption is expected and teams are making increasingly informeddecisions based on the value offered by AI tools. The question now isnot whether companies are using AI, but how they’re using it to boostproductivity among their workforce and grow revenue. Call it RO(AI).The market continues to price in the distinction between companiesthat show real impact from AI and those that cannot. The former arebenefitting with easier access to capital and attractive valuations,while the latter are finding it harder to defend their businesses. middle just yet. Capital is returning to software startups, but onnarrower terms. AI startups have captured the largest rounds in thepast year, while venture investment outside AI was muted. At theearly stage, lower initial startup costs and AI enthusiasm haveboosted first fundings of AI startups. At the later stage, unicorns havepivoted to profitability, often at the expense of growth. Most will needto rediscover product-market fit as an AI-native business to attractfuture investment or exit opportunities. Exit markets are improving. Accelerating disruption has forcedfounders to consider selling earlier, while the push to incorporatenascent AI capabilities into legacy businesses has brought morecorporate buyers to the table. The IPO window remains constrained,but tides may turn if AI bellwethers go public. The question now is notwhether companies areusing AI, but how they’reusing it to boostproductivity among theirworkforce and growrevenue. Call it RO(AI).” This split is evident in the public markets, though the story is morenuanced than the headlines suggest.Hyperscalersand AI-tangentialcompanies have captured most of the recent upside, while moretraditional SaaS businesses have lagged. Some of that gap reflectsreal disruption from AI, and some of it is simple allocation math asinvestors rebalance portfolios to account for a handful of AI-adjacentnames driving outsized returns. Despite this, tech companies havebeen through a platform shift before. Traditional SaaS businesses,who were once disruptors themselves, have an opportunity to usethis new AI wave to their advantage. The best will adjust and thrive. From a founder perspective, this year’s survey of more than 120enterprise software companies shows just how pivotal this momentis. AI adoption is being encouraged, if not mandated, from the top-down. This is already creating real productivity gains, particularly (butnot only!) within engineering teams. It is also creating knock-oneffects: hiring is slowing, particularly for junior roles, and startups arebeing challenged in how they think about pricing. A new customer is also emerging at scale: the federal government. Ithas committed tens of billions of dollars to AI and related initiatives,and procurement is beginning to accelerate. Pathways that once tookyears are moving faster, though access remains uneven and oftenrequires significant investment in security and compliance. Heading into 2026, the more useful question is not whether SaaS isdisappearing, but whether software companies can adapt quicklyenough to keep earning their place in the budget. The companies thatprove value, stay close to core workflows and incorporate AI where itmatters are most likely to define the next phase of the market. In the private markets, bifurcation continues. Fundraising remainsconcentrated at both ends of the barbell—but don’t count out the Emma EschweilerManaging DirectorInvestor CoverageSilicon Valley Bank Rob HelmSenior Market ManagerTech BankingSilicon Valley Bank Andrew McCartyDirectorTech BankingSilicon Valley Bank Amer TahboubDirectorTech BankingSilicon Valley Bank Perspectives on the Enterprise Software Market AI as a Revenue Driver With AI, Everyone Is a Manager Beware of Shadow AI “The same concepts with managing people apply toAI, from giving feedback to supervising timelines tounderstanding the project goal. Employees shouldbe looking to solve harder problems, not managemore people. It is an important shift in the narrativeof what career growth looks like and how it isachieved.” “We’re seeing real gains from AI inproductdevelopment, sales and customer success arenas—building product value faster, automating proposal-to-close processes, sales’ ability to personalize everytouch, and communicating ROI continuously. It’sbeen a huge revenue and productivity accelerator.” “Larger companies often take time to embrace newtechnologies. Meanwhile, employees tend toexperiment with it on their own, often leavingcompanies with shadow vulnerabilities. It’simportant for organizations to not blanket ban newtechnologies but rather have proper guardrails andchampions for adopting i