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EMERGING TECH RESEARCHClash of the Titans Institutional Research Group Derek HernandezSenior Research Analyst,Enterprise SaaS andInfrastructure SaaSderek.hernandez@pitchbook.com Incumbents versus challengers in the age of agentic AI pbinstitutionalresearch@pitchbook.com PitchBook is a Morningstar company providing the most comprehensive, mostaccurate, and hard-to-find data for professionals doing business in the private markets. Published on January 14, 2026 Contents Key takeaways Key takeaways1The radical transformation in SaaS2AI-embedded incumbents3AI-native challengers3Market development and investment5Market sizing and growth7Opportunities and constraints8Defensibility and the tech stack9The new moats10Incumbents and challengers meet11The investor perspective12Conclusion and outlook18Appendix: Scoring key incumbents andchallengers19 •The enterprise SaaS sector is undergoing its most significant technological shift ina generation, driven by the maturation of artificial intelligence. This report provides aframework for private market investors to navigate this transformation, which is definedby a central dichotomy: AI-embedded incumbents versus AI-native challengers. •While the enterprise adoption of AI is high (78% of organizations), meaningful businessoutcomes are not (95% of pilots are failing to accelerate revenue).1This execution gapcreates a massive opportunity for a new class of vendors. •This market is bifurcating. Incumbents are embedding AI copilots into legacysuites, leveraging their vast distribution and customer trust. In contrast, AI-nativechallengers are building intelligent systems from the ground up, creating new, highlydefensible moats. •For investors, we argue that the most durable value will not come from the AI modelsthemselves, which are becoming commoditized. Instead, the new, defensible moats arebeing built on proprietary data pipelines that create a virtuous feedback loop, agenticorchestration that automates entire and complex workflows, domain-specific tuningthat provides verifiable accuracy, and auditable control planes that satisfy enterprisegovernance and compliance needs. •This report analyzes the market dynamics, investment landscape (including a $65billion TAM set to grow to $190 billion by 2030), and competitive strategies of bothincumbents and challengers. It concludes with an actionable playbook and diligencechecklist for LPs, GPs, and founders to identify the true, defensible category leaders inthe new AI-native world. The radical transformation in SaaS The enterprise software-as-a-service (SaaS) sector is undergoing its most significanttechnological shift in a generation, even larger than the transformation fromperpetually licensed products to SaaS itself. This shift is driven by the ongoingmaturation of AI, especially the advancements by major large language models (LLMs)and their rush to deployment across nearly every solution within enterprise SaaS.Excluding massive rounds by LLMs, we see this trend driving steady and sustainedgrowth across enterprise SaaS investments since early 2024. All datasets hereinexclude these recent and discrete mammoth AI funding rounds. Thus, this is the first in a series of reports on AI within enterprise SaaS, beginning witha high-level overview of the state of play today. In our future pieces, we will dive into AIin specific sectors and subsectors, including AI in customer relationship management(CRM), AI in HR tech, and others. We invite PitchBook clients to reach out with specificsectors of the enterprise SaaS landscape they would like us to cover in this series aswell. Please direct suggestions toderek.hernandez@pitchbook.com. The AI transformation of enterprise SaaS has sorted the segment into a criticaldichotomy: the distinction between retrofitting existing systems with AI features(AI-embedded platforms) and designing new operations from the ground up aroundintelligent, autonomous processes (AI-native platforms). This choice is a fundamentalstrategic decision that will balance established distribution, defensibility, andcompliance with competitive durability, operational efficiency, and evolving revenuestreams for years to come. The proliferation of generative AI has forced every enterprise software companyto formulate an AI strategy. However, not all AI is created equal. The architecturalapproach an organization takes—either building new systems with AI at their core orlayering AI onto existing platforms—is the single most important determinant of long-term success and value creation. This distinction creates a clear framework for marketanalysis and investment due diligence. AI-embedded incumbents AI-embedded solutions, thus far the domain of legacy SaaS incumbents, offeradditional productivity gains within established solutions and platforms. Theseincumbents within enterprise SaaS are embedding copilots and task agentsinto existing suites, spanning CRM, enterprise resource planning (ERP), supplychain manag