## Part 1: Research — Verifiable atomic claims 1. **Claim:** Gartner predicted in November 2025 that by 2028, **90% of B2B buying will be AI-agent intermediated**, pushing **more than $15 trillion** of B2B spend through AI agent exchanges. * **Source:** Gartner, *Strategic Predictions for 2026: How AI’s Underestimated Influence Is Reshaping Business* * **Date:** November 14, 2025 * **Reliability:** High ([gartner.com][1]) 2. **Claim:** Gartner predicted in November 2025 that through 2027, **GenAI and AI agent use will create the first true challenge to mainstream productivity tools in 35 years**, prompting a **$58 billion market shake-up**. * **Source:** Gartner, *Strategic Predictions for 2026: How AI’s Underestimated Influence Is Reshaping Business* * **Date:** November 14, 2025 * **Reliability:** High ([gartner.com][1]) 3. **Claim:** McKinsey reported in November 2025 that **88% of respondents said their organizations regularly use AI in at least one business function**, up from **78% a year earlier**. * **Source:** McKinsey, *The State of AI: Global Survey 2025* * **Date:** November 2025 * **Reliability:** High ([McKinsey & Company][2]) 4. **Claim:** McKinsey reported in November 2025 that **approximately one-third of respondents said their companies had begun to scale AI programs** at the enterprise level. * **Source:** McKinsey, *The State of AI: Global Survey 2025* * **Date:** November 2025 * **Reliability:** High ([McKinsey & Company][2]) 5. **Claim:** McKinsey reported in November 2025 that **23% of respondents said their organizations were scaling an agentic AI system somewhere in the enterprise**. * **Source:** McKinsey, *The State of AI: Global Survey 2025* * **Date:** November 2025 * **Reliability:** High ([McKinsey & Company][2]) 6. **Claim:** McKinsey reported in November 2025 that an **additional 39% of respondents said their organizations had begun experimenting with AI agents**. * **Source:** McKinsey, *The State of AI: Global Survey 2025* * **Date:** November 2025 * **Reliability:** High ([McKinsey & Company][2]) 7. **Claim:** McKinsey reported in November 2025 that **in any given business function, no more than 10% of respondents said their organizations were scaling AI agents**. * **Source:** McKinsey, *The State of AI: Global Survey 2025* * **Date:** November 2025 * **Reliability:** High ([McKinsey & Company][2]) 8. **Claim:** McKinsey reported in December 2025 that **more than 80% of 200 surveyed C-suite executives said they were already running pilots on agentic AI**. * **Source:** McKinsey, *Transforming Tech Services for Agentic AI* * **Date:** December 2025 * **Reliability:** High ([McKinsey & Company][3]) 9. **Claim:** McKinsey reported in December 2025 that **roughly 12% of enterprises had already scaled agentic AI deployments across multiple functions**, while **half were planning significant investments in scaled deployments over the next six months**. * **Source:** McKinsey, *Transforming Tech Services for Agentic AI* * **Date:** December 2025 * **Reliability:** High ([McKinsey & Company][3]) 10. **Claim:** McKinsey reported in December 2025 that **more than one-third of respondents expected annual outlays for agentic AI to rise by more than 25%**, and **close to three-quarters expected increases above 10%**. * **Source:** McKinsey, *Transforming Tech Services for Agentic AI* * **Date:** December 2025 * **Reliability:** High ([McKinsey & Company][3]) 11. **Claim:** TechCrunch reported on February 5, 2026 that OpenAI launched **OpenAI Frontier**, an **end-to-end open platform** for enterprises to **build and manage AI agents**, including agents built outside OpenAI. * **Source:** TechCrunch, *OpenAI launches a way for enterprises to build and manage AI agents* * **Date:** February 5, 2026 * **Reliability:** Medium ([TechCrunch][4]) 12. **Claim:** TechCrunch reported on February 23, 2026 that OpenAI announced **“Frontier Alliances”** with **BCG, McKinsey, Accenture, and Capgemini** to sell and implement its enterprise AI products. * **Source:** TechCrunch, *OpenAI calls in the consultants for its enterprise push* * **Date:** February 23, 2026 * **Reliability:** Medium ([TechCrunch][5]) 13. **Claim:** TechCrunch reported on February 24, 2026 that New Relic launched a **no-code Agentic Platform** that lets enterprises deploy **prebuilt observability agents**, manage existing bots, and supports the **Model Context Protocol (MCP)**. * **Source:** TechCrunch, *New Relic launches new AI agent platform and OpenTelemetry tools* * **Date:** February 24, 2026 * **Reliability:** Medium ([TechCrunch][6]) 14. **Claim:** TechCrunch reported on February 25, 2026 that Atlassian announced **“agents in Jira”** to let **humans and AI agents work side by side**. * **Source:** TechCrunch, *Jira’s latest update allows AI agents and humans to work side by side* * **Date:** February 25, 2026 * **Reliability:** Medium ([TechCrunch][7]) 15. **Claim:** TechCrunch reported on January 13, 2026 that Salesforce released a new AI-agent version of **Slackbot**, generally available for **Business+ and Enterprise+** customers, that can **find information, draft emails, schedule meetings, and connect to Microsoft Teams and Google Drive with permission**. * **Source:** TechCrunch, *Slackbot is an AI agent now* * **Date:** January 13, 2026 * **Reliability:** Medium ([TechCrunch][8]) --- ## Part 2: Market analysis report for a SaaS startup pitch deck ### Introduction The enterprise AI-agent market is moving from curiosity to budgeted priority, but it has not yet reached broad operational maturity. Recent Gartner and McKinsey data show a market where AI is already mainstream, while agentic deployments remain early and uneven. At the same time, major software vendors are racing to build the control layer, workflow layer, and ecosystem partnerships that could define the next generation of enterprise software (Claims 1–15). ([gartner.com][1]) ### 1. AI agents are becoming a buying-interface shift, not just a feature upgrade The strongest long-range signal comes from Gartner’s prediction that by 2028, 90% of B2B buying will be intermediated by AI agents, channeling more than $15 trillion of spend through AI agent exchanges (Claim 1). Gartner also projects that GenAI and AI agents will create the first true challenge to mainstream productivity tools in 35 years, with a $58 billion market shake-up through 2027 (Claim 2). Together, these claims suggest that AI agents are not being treated merely as add-on copilots; they are starting to reshape how enterprise users discover, evaluate, and execute software workflows (Claims 1, 2). ([gartner.com][1]) For a SaaS startup, that matters because the competitive battlefield may shift from traditional UI-driven adoption to agent-compatible workflows, machine-readable actions, and product surfaces that can be orchestrated by external systems (Claims 1, 2). This favors startups that design for agent mediation early rather than retrofitting it later. ([gartner.com][1]) ### 2. The market is broad at the top of the funnel, but narrow at scale McKinsey’s latest survey shows that 88% of organizations now use AI in at least one business function, up from 78% a year earlier (Claim 3). But only about one-third have begun scaling AI programs at the enterprise level (Claim 4). The gap becomes sharper with agents: 23% are scaling an agentic AI system somewhere in the enterprise, while another 39% are still only experimenting (Claims 5, 6). In any individual business function, no more than 10% report scaling AI agents (Claim 7). ([McKinsey & Company][2]) This is the clearest sign that the current market is in a transition phase. Demand is real, but repeatable deployment remains difficult. For investors, that means the category is no longer speculative. For founders, it means the winning product is less likely to be a generic “AI agent” and more likely to be a focused system that solves one high-value operational problem well enough to move from pilot to scaled usage (Claims 4–7). ([McKinsey & Company][2]) ### 3. Budget momentum is real, even before full maturity arrives McKinsey’s December 2025 enterprise survey shows that more than 80% of C-suite executives were already running agentic AI pilots (Claim 8). Roughly 12% had already scaled deployments across multiple functions, and half planned significant investments in scaled deployments within six months (Claim 9). More than one-third expected annual outlays to rise by more than 25%, while close to three-quarters expected increases above 10% (Claim 10). ([McKinsey & Company][3]) That combination is important for a pitch deck: it shows that the market is not waiting for perfect clarity before spending. Buyers are allocating budget ahead of full operational maturity. The implication is that startups do not need to prove the existence of demand; they need to prove that they can shorten time-to-value, reduce deployment friction, and justify expansion budgets as pilot programs move toward scale (Claims 8–10). ([McKinsey & Company][3]) ### 4. The platform layer is consolidating quickly Vendor behavior in early 2026 points to rapid competition around the enterprise control plane for agents. OpenAI launched OpenAI Frontier as an open, end-to-end platform for enterprises to build and manage agents, including non-OpenAI agents (Claim 11). OpenAI then added distribution and implementation leverage by forming Frontier Alliances with BCG, McKinsey, Accenture, and Capgemini (Claim 12). ([TechCrunch][4]) Other vendors are moving in parallel. New Relic introduced a no-code Agentic Platform for observability workflows and added MCP support (Claim 13). Atlassian launched agents in Jira for side-by-side human and agent work (Claim 14). Salesforce upgraded Slackbot into an enterprise AI agent that can perform tasks across Slack and connected systems such as Microsoft Teams and Google Drive (Claim 15). ([TechCrunch][6]) The pattern is clear: large vendors are not only shipping assistants, they are building orchestration, administration, interoperability, and workflow-specific execution layers. That suggests a startup pitch should position clearly relative to this stack: either as infrastructure that plugs into these platforms, a vertical workflow product they do not serve well, or a differentiated control/governance layer around deployment and outcomes (Claims 11–15). ([TechCrunch][4]) ### 5. The near-term opportunity is in focused enterprise outcomes The research also implies that the biggest bottleneck is not awareness. It is operationalization. AI is already common, but scaled agentic deployment is still limited by function, organization, and implementation complexity (Claims 3–10). That makes outcome-specific SaaS especially attractive: products that can move one team, one workflow, or one system of work from experiment to dependable execution. ([McKinsey & Company][2]) In practical terms, the best wedge may be software that helps enterprises manage agents, connect them to systems safely, or embed them into domain workflows where buyers already have budget authority. The activity from OpenAI, Atlassian, New Relic, and Salesforce indicates that enterprise buyers are responding to products that fit inside existing software habits rather than asking users to adopt entirely new behaviors from scratch (Claims 11–15). ([TechCrunch][4]) ### Conclusion The rise of AI agents in enterprise software is no longer a future thesis; it is a present market transition. Gartner’s forecasts point to structural change in B2B buying and productivity software economics (Claims 1, 2). McKinsey’s surveys show strong AI penetration, rising pilot activity, and accelerating budgets, but only limited scaled deployment so far (Claims 3–10). Specialized tech press shows that major vendors are responding by building agent platforms, workflow integrations, and implementation ecosystems at speed (Claims 11–15). ([gartner.com][1]) For a SaaS startup, that creates a strong opening: build where enterprise demand is already funded, but where scaled execution is still hard. The category opportunity appears largest for products that turn agent enthusiasm into governed, workflow-level business value (Claims 4–15). ([McKinsey & Company][2]) [1]: https://www.gartner.com/en/articles/strategic-predictions-for-2026 "Strategic Predictions for 2026: How AI’s Underestimated Influence Is Reshaping Business" [2]: https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai "The State of AI: Global Survey 2025 | McKinsey" [3]: https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/reimagining-the-value-proposition-of-tech-services-for-agentic-ai "Transforming tech services for agentic AI | McKinsey" [4]: https://techcrunch.com/2026/02/05/openai-launches-a-way-for-enterprises-to-build-and-manage-ai-agents/ "OpenAI launches a way for enterprises to build and manage AI agents | TechCrunch" [5]: https://techcrunch.com/2026/02/23/openai-calls-in-the-consultants-for-its-enterprise-push/ "OpenAI calls in the consultants for its enterprise push | TechCrunch" [6]: https://techcrunch.com/2026/02/24/new-relic-launches-new-ai-agent-platform-and-opentelemetry-tools/ "New Relic launches new AI agent platform and OpenTelemetry tools | TechCrunch" [7]: https://techcrunch.com/2026/02/25/jiras-latest-update-allows-ai-agents-and-humans-to-work-side-by-side/ "Jira’s latest update allows AI agents and humans to work side by side | TechCrunch" [8]: https://techcrunch.com/2026/01/13/slackbot-is-an-ai-agent-now/ "Slackbot is an AI agent now | TechCrunch"