The orchestration layer of enterprise AI — software that lets large language models plan, take multi-step actions and execute workflows autonomously inside the systems companies already run.
Enterprise software is moving from copilots that suggest to agents that act, and incumbent platforms are repackaging their data and workflow estates as the execution layer for that shift. Gartner expects roughly a third of enterprise applications to embed agentic AI by 2028, up from under 1% in 2024, while McKinsey finds 23% of organizations already scaling an agentic system somewhere in the business. The same transition is rewriting how software is sold, pushing pricing away from per-seat licenses toward consumption-, action- and outcome-based meters as agents — which never log in as named users — break the historical link between revenue and headcount.
Through 2026-2030 agentic deployment broadens from pilots in IT and knowledge management toward cross-functional, multi-agent orchestration, with Gartner projecting at least 15% of day-to-day work decisions made autonomously by 2028 and IDC citing 1.3 billion agents by 2028. Winners are likely to be platforms that combine proprietary enterprise data, governed workflow rails and trusted execution, since value accrues to whoever owns the system of record the agent acts within. The maturation is not linear — Gartner expects over 40% of agentic projects to be cancelled by end-2027 on cost, unclear value or weak controls — making governance, security and measurable outcomes the gating variables for durable revenue.
The forces routing money into this theme right now.
Salesforce reported Agentforce annual recurring revenue of roughly $800M exiting fiscal Q4 2026 with 29,000 cumulative deals, the clearest large-cap proof that agentic software is converting to recurring revenue.
Gartner projects roughly a third of enterprise applications will include agentic AI by 2028, with task-specific agents in ~40% of enterprise apps by end-2026, signaling broad platform-level demand.
Gartner expects at least 40% of enterprise SaaS spend to move to usage-, agent- or outcome-based models by 2030, with Salesforce's $2-per-conversation and per-action Flex Credits pricing illustrating the transition.
ServiceNow's Now Assist annualized contract value climbed toward ~$750M and the company raised its near-term AI ACV target to $1.5B, with agentic capabilities gated to its top Enterprise Plus tier.
Structural large-cap anchors — lower-variance exposure to the theme.
Microsoft, with its Copilot platform and Agent 365, is positioned to be the structural leader in the AI agent space, leveraging its unmatched enterprise distribution. The company's focus on per-seat-to-outcome pricing and custom agent workflows strengthens its position as a key player in the agentic software wave.
Why the excitement: Microsoft's Q3 FY2026 earnings call revealed that tens of thousands of companies are managing tens of millions of agents in Agent 365, signaling strong early adoption.
The honest risk: Gartner predicts over 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear value, or weak risk controls, potentially impacting Microsoft's agent-related revenue.
ServiceNow is positioning itself as a leader in the AI agent space by integrating agents into its existing IT and operations workflows, focusing on measurable work outcomes. The company's focus on per-seat-to-outcome pricing and workflow integration offers a structural advantage in the evolving AI agent landscape.
Why the excitement: Management noted Now Assist is already exceeding expectations and is on track to exceed its $1 billion target for 2026, demonstrating strong early monetization of its AI agent offerings.
The honest risk: Integration of acquired businesses like Armis may create near-term margin headwinds, potentially impacting profitability in the short term.
Salesforce's Agentforce leverages its massive CRM install base to deploy autonomous agents, directly addressing front-office automation. The company's transition towards outcome-based pricing models positions it to capitalize on the growing demand for AI-driven solutions.
Why the excitement: Salesforce is seeing incredible demand for Agentforce, with new bookings for its premium Agentforce One Edition and Agentforce for Apps nearly tripling quarter-over-quarter (Q4 FY2026 transcript).
The honest risk: Despite strong Agentforce demand, continued weakness in marketing and commerce, as well as weaker-than-expected Tableau performance, could offset gains (Q4 FY2026 transcript).
Smaller names with higher upside and deeper potential drawdowns.
UiPath is pivoting from robotic process automation (RPA) to AI-powered agentic orchestration, offering a potential re-rating if it successfully navigates this transition. The company's established enterprise footprint and focus on governance provide a competitive edge in the burgeoning AI agent market.
Why the excitement: UiPath's AI product ARR, including agentic, IDP, and Maestro, reached nearly $200 million this quarter, with strong growth fueled by agentic solutions.
The honest risk: UiPath faces the risk of slower-than-expected adoption of its agentic AI offerings, potentially hindering its growth and profitability targets.
Asymmetry: Large upside on the agentic pivot; deep drawdown if legacy RPA growth stalls first.
C3.ai aims to capitalize on agentic AI adoption within large organizations, focusing on enterprise-wide transformations; however, profitability and market traction remain key challenges.
Why the excitement: Management expects productivity to increase multifold across business functions by leveraging Agentic AI, particularly in generating customer-specific sales proposals.
The honest risk: Despite a focus on large-scale transformations, C3.ai's negative operating margin of -151.7% indicates significant challenges in achieving profitability.
Asymmetry: High upside on enterprise agent wins; sharp drawdown given uneven growth and profitability.
SoundHound is a higher-risk play on conversational AI agents at scale, leveraging its voice AI platform for diverse enterprise applications; success hinges on profitable scaling.
Why the excitement: SoundHound reported Q1 revenue growth of 52% year-over-year, driven by high usage of its products and solutions.
The honest risk: Despite strong growth, SoundHound's negative operating margin of -115.9% indicates a challenge in achieving profitability.
Asymmetry: Upside on voice-agent adoption; deep drawdown given small revenue base and valuation.
The sub-layers and the leaders that anchor each one.
It is AI that takes actions instead of just generating text — agents that book, code, resolve tickets and operate across your tools. It is the application layer of AI and the next software wave.
Platforms with distribution like Microsoft, ServiceNow and Salesforce are best positioned to deploy agents at scale; pure-plays such as UiPath and C3.ai carry higher asymmetry tied to the agentic transition.
As agents do work rather than assist users, pricing shifts from per-seat to per-outcome, which can expand the market for the platforms that capture it.
It weights revenue growth, R&D intensity and market-share gains — favoring platforms with distribution and durable growth over early-stage names.
Agent adoption could prove slower or messier than hyped, incumbents could absorb the opportunity, and the security and reliability of autonomous software remains an open question.
AI InfrastructureDefense Tech 2.0Biotech & AI Drug Discovery
투자 자문이 아닌 교육 콘텐츠. 과거 성과가 미래 결과를 보장하지 않습니다.