Agentic AI: The Emerging Category Every B2B Investor Should Understand Now

The market is moving past AI as a feature and toward AI as labor. 

That is the real shift behind agentic AI. The category is not simply about better chat interfaces or more capable copilots. It is about software systems that can perceive context, plan multi-step actions, use tools, coordinate workflows, and complete meaningful work with limited human intervention. McKinsey’s 2025 global survey describes the current landscape as one of “growing proliferation of agentic AI,” but also notes that most organizations are still struggling to move from pilots to scaled impact. That combination matters: the capability is advancing, but the market structure is still early.

For B2B investors, that is exactly the kind of moment worth paying attention to. Categories tend to be most investable when the technical shift is real, enterprise demand is forming, and the operating playbook is not yet standardized. Agentic AI is now at that point. The window is narrow because the market is moving quickly from research labs into enterprise operations, yet many investors are still analyzing it as though it were just another layer of generative AI tooling.

At Azafran Capital Partners, we view this through an applied deep tech lens. We are less interested in general AI novelty than in where advanced systems become useful, defensible, and operationally durable in MedTech, IoT, and enterprise B2B. In that context, agentic AI is not interesting because it sounds futuristic. It is interesting because it has the potential to become a new operating layer inside enterprise workflows. The firms that understand that early will be better positioned to identify where value will actually accrue.

Agentic AI is a category shift, not a feature upgrade 

A lot of the market still uses “agent” too loosely. Not every automated workflow is agentic AI. Not every assistant qualifies either. What makes the category important is that agentic systems are designed to do more than respond. They can evaluate goals, break work into steps, interact with software systems, and operate across a chain of decisions. Salesforce’s 2025–2026 agentic research frames the shift as the move toward an “agentic enterprise,” where experimentation begins with basic task automation and extends into HR, legal, operations, service, and other enterprise functions. Microsoft makes a similar point in its 2026 guidance on scaling agent adoption: before 2025, most agents were experimental, narrow, manually triggered, and siloed, but the next phase is about organizational adoption and agent systems that can be deployed at scale.

That is why agentic AI deserves category-level attention from B2B investors. Copilots improve the interface between a person and a system. Agents begin to alter how work itself gets executed. That is a much bigger opportunity, but also a more demanding one. Once software starts acting, not just suggesting, the buyer conversation shifts from novelty to governance, reliability, auditability, workflow fit, and business risk.

Enterprise demand is real, but scaled execution is still rare 

This is where investors need discipline. AI adoption is now broad. McKinsey reports that 88% of organizations use AI in at least one function, but most still have difficulty scaling value. Deloitte’s 2026 State of AI in the Enterprise, based on more than 3,000 leaders, similarly emphasizes that organizations are engaging deeply with AI while still wrestling with the practical challenge of turning experimentation into business impact. The implication is clear: demand exists, but operational maturity remains uneven.

That unevenness is precisely why agentic AI is emerging as a distinct investment category. Capgemini’s 2025 report on the rise of agentic AI describes 2025 as a turning point, with advances in NLP expanding agents’ ability not just to answer questions, but to plan, collaborate, and act. Yet Deloitte’s “agentic reality check” warns that over 40% of agentic AI projects could be canceled by the end of 2027, citing execution challenges and weak alignment. That is not a contradiction. It is the category signal. Real capability plus high failure rates usually means there is still room for differentiated winners.

Investors should read that as a separator, not a warning sign to avoid the space. In early categories, failure often comes from weak delivery, poor integration, or the absence of operating discipline. The question is not whether agentic AI will matter. The question is which companies can move from demo to deployment.

The moat is not the agent alone. It is the delivery system around it. 

This is where many investors will misprice the market. 

The companies worth backing are unlikely to be the ones with the flashiest agent demo. They will be the ones that can connect agents to trusted enterprise context, real workflows, and operational safeguards. Salesforce’s January 2026 executive research put it bluntly: the limiting factor is no longer whether to bring AI into workflows, but whether organizations can safely connect AI to the data and processes that run the business. McKinsey’s 2025 survey reinforces the same point by showing that high performers are much more likely to have defined processes for human validation, risk control, and workflow redesign.

In practical terms, the moat in agentic AI will often sit around the agent rather than inside the model. It will come from workflow ownership, proprietary system integrations, domain-specific context, defensible IP, governance architecture, and the ability to produce repeatable outcomes in production. That is why we believe applied deep tech is such an important lens here. In sectors like MedTech, IoT, and enterprise B2B, agents will only become valuable if they can function inside constrained, high-trust environments.

Why B2B investors should care now 

The reason to understand agentic AI now is not that the category is finished. It is that it is forming. By the time a category is obvious to every fund, much of the informational edge is gone. What matters now is developing the right pattern recognition early. Capgemini’s research shows that AI agents are already moving into business operations, while Salesforce’s startup outlook for 2026 calls agentic AI the most dominant trend shaping the technology market. Microsoft is already publishing enterprise guidance on scaling agent adoption. These are not academic signals. They indicate that platform vendors, enterprise buyers, and operators are beginning to build around the category, which is usually when serious infrastructure and application layers start to emerge.

For LPs, VCs, and tech investors, this has two implications. First, agentic AI should not be evaluated as a generic “AI exposure” bucket. It deserves separate analysis because its economics, risks, and adoption barriers are different from prompt-based software or model-layer plays. Second, the most attractive opportunities may sit in the applied layer: companies that use agentic architectures to solve hard enterprise problems where delivery, trust, and domain fit matter more than consumer-style growth velocity.

Our view is straightforward: agentic AI is becoming a real B2B category, and sophisticated investors should understand it before the market fully prices it. 

That does not mean every “agentic” company deserves capital. Many will fail because the category invites hype. But the underlying shift is real. Software is beginning to move from assisting labor to performing labor, and that transition has major implications for enterprise value creation. The winners will not just have capable agents. They will have defensible delivery systems, strong governance, clear workflow fit, and the operational maturity to survive enterprise deployment. (Deloitte) 

At Azafran, we see that as an applied deep tech opportunity. The most valuable agentic AI companies will not be built on narrative alone. They will be built where autonomous capability meets real-world deployment, defensible intellectual property, and long-term operational value. In the next cycle, that will matter more than how loudly a company says the word “agent.” If you want the LinkedIn caption and SEO meta description next, I’ll format them to match the rest of the Azafran series.