LONDON, 31 January 2026 — Agentic artificial intelligence is poised to trigger the most significant structural shift in the Software as a Service industry since its inception, evolving it from a "software for humans" model to a "service-as-a-software" paradigm between 2026 and 2030. The transformation will fundamentally alter how enterprises procure, deploy, and pay for business software, with cascading implications for vendors, investors, and the global workforce.

Executive Summary

• Gartner predicts 40% of enterprise applications will feature task-specific AI agents by end of 2026, up from less than 5% in 2025
• The agentic AI market is projected to grow from $8.5 billion in 2026 to between $42 billion and $52 billion by 2030, representing a compound annual growth rate exceeding 43%
• Traditional per-seat SaaS pricing has declined from 21% to 15% of vendors in 12 months, with IDC predicting pure seat-based pricing will be obsolete by 2028
• Over 40% of agentic AI projects may be cancelled by 2027 due to escalating costs, unclear business value, or inadequate risk controls

The Five-Stage Revolution: From Assistants to Autonomous Agents

The SaaS industry stands at an inflection point comparable to the shift from on-premises software to cloud computing in the late 2000s. Gartner's research outlines a clear trajectory for enterprise AI adoption over the next five years, with each stage representing a fundamental expansion of autonomous capability.

"By 2035, agentic AI could drive approximately 30% of enterprise application software revenue, surpassing $450 billion," noted Gartner analysts in their August 2025 forecast. "This represents a dramatic shift from just 2% penetration in 2025."

Table 1: Gartner's Five-Stage Agentic AI Evolution (2025-2029)

Stage	Year	Capability	Enterprise Impact	Source
Stage 1	2025	AI Assistants Everywhere	Nearly all enterprise apps embed AI assistants requiring human input	Gartner
Stage 2	2026	Task-Specific Agents	40% of enterprise applications integrate agents that act independently	Gartner
Stage 3	2027	Collaborative Agents Within Apps	One-third of implementations combine agents with different skills for complex tasks	Gartner
Stage 4	2028	Cross-App Agent Ecosystems	15% of daily work decisions made autonomously; agent networks collaborate across business functions	Gartner
Stage 5	2029	The New Normal	50% of knowledge workers develop skills to create AI agents on demand	Gartner

The Death of Per-Seat Pricing

Perhaps no aspect of the SaaS business model faces greater disruption than pricing. The traditional per-seat licensing model, which has underpinned enterprise software economics for three decades, is rapidly becoming obsolete as AI agents deliver value without requiring human operators.

According to BCG research, seat-based pricing dropped from 21% to 15% of SaaS companies in just 12 months, while hybrid pricing models surged from 27% to 41% adoption. IDC analysts predict that by 2028, pure seat-based pricing will be obsolete, forcing 70% of vendors to refactor their models entirely.

"More scale. Fewer seats. Lower revenue," observed SaaStr founder Jason Lemkin, describing the paradox facing traditional SaaS vendors. "We're already downgrading seat counts at vendors now that we have 12 or more AI agents in production."

The implications are profound. Companies that persist with per-seat pricing for AI products experience 40% lower gross margins and 2.3x higher customer churn, according to Pilot's 2025 analysis of AI pricing economics.

Table 2: Emerging Pricing Models for AI-Native SaaS (2025-2030)

Pricing Model	Description	Adoption Rate	Example Vendors	Key Challenge
Consumption-Based	Pay per API call, token, or resolved interaction	Growing rapidly	Intercom Fin ($0.99/resolved conversation), Fireflies.ai	Revenue unpredictability; surprise customer bills
Outcome-Based	Pay for results achieved (deals won, issues resolved)	~30% by late 2025	Emerging across enterprise	Requires extensive tracking and trust infrastructure
Credit Systems	Pre-purchased credits consumed by AI actions	Most common interim solution	HubSpot, various AI startups	Customers struggle to understand credit value
Hybrid Seat + Usage	Base subscription with consumption limits	41% (up from 27%)	Salesforce Agentforce	Complex to negotiate; requires defined terms
Agent Licensing	Per-agent seats (not per-human)	Emerging 2026	Salesforce (Agentic Enterprise License)	Valuation of agent capabilities

Platform Giants Race for Agentic Dominance

The world's largest enterprise software vendors are engaged in an aggressive competition to establish dominance in agentic AI, with billions of dollars in contracts and market positioning at stake.

Salesforce has positioned Agentforce as its flagship agentic AI platform, describing it as the "fastest-growing product ever" with 119% agent growth in the first half of 2025. The company secured a landmark $5.6 billion contract with the US Army in January 2026 for its Missionforce agentic AI platform, underscoring the strategic importance of autonomous AI systems in both commercial and government sectors.

"67% of CEOs say implementing agents is critical to compete," according to Salesforce's C-Suite research. "80% expect humans and AI agents to work together as blended workforces within five years."

ServiceNow has responded with its AI Control Tower and AI Agent Orchestrator, positioning governance and auditability as key differentiators. The company completed its acquisition of Moveworks in December 2025 to expand its agentic AI capabilities, projecting 21% subscription revenue growth for 2026.

"2026 will be the year of agentic collaboration," declared ServiceNow COO Amit Zavery. "AI agents will autonomously diagnose, plan, and execute multi-step workflows across enterprise systems."

Market Size Projections and Investment Dynamics

Multiple research firms project explosive growth for the agentic AI market, with forecasts converging around $40-50 billion by 2030. Mordor Intelligence projects growth from $6.96 billion to $42.56 billion at a 43.61% CAGR, while MarketsandMarkets forecasts the AI agents market reaching $52.62 billion by 2030.

Omdia's analysis reveals that agentic AI is growing at 175% five-year CAGR, significantly outpacing traditional generative AI's 90% initial growth rate. By 2030, agentic AI will represent 31% of the total generative AI market, up from just 6% in 2025.

Table 3: Agentic AI Market Size Forecasts by Research Firm (2025-2030)

Research Firm	2025 Market Size	2030 Forecast	CAGR	Key Segments
Mordor Intelligence	$6.96B	$42.56B	43.61%	Broad agentic AI market
Grand View Research	$3.67B	$24.50B	46.2%	Enterprise agentic AI
MarketsandMarkets	$7.84B	$52.62B	46.3%	AI agents market (broad)
MarketsandMarkets (Enterprise)	$5-6B	$40B	47%	Enterprise applications
Omdia	$1.5B	$41.8B	175% (5-yr)	Enterprise agentic AI software

From System of Record to System of Action

The fundamental architecture of enterprise software is undergoing a paradigm shift. Traditional SaaS platforms functioned primarily as "systems of record"—databases where humans entered, retrieved, and manipulated data. Agentic AI transforms these platforms into "systems of action" that autonomously execute workflows, make decisions, and coordinate across organisational boundaries.

By 2030, Gartner projects that 35% of point-product SaaS tools will be absorbed into larger agent ecosystems or replaced entirely by AI agents. The surviving platforms will function as orchestration layers, managing fleets of specialised agents rather than serving as destinations for human interaction.

"SaaS will become a System of Context, blending data with AI to understand complex, unstructured workflows," noted industry analysts. "The goal-oriented agent doesn't need a dashboard. It needs access to data, execution capability, and governance guardrails."

Risks and Governance Challenges

The transition to agentic AI carries substantial risks that could derail enterprise adoption. Gartner warns that over 40% of agentic AI projects will be cancelled by the end of 2027 due to escalating costs, unclear business value, or inadequate risk controls.

The probabilistic nature of AI—unlike the deterministic nature of traditional software—introduces fundamental reliability concerns. Gartner analysts estimate that only about 130 of the thousands of agentic AI vendors are legitimate, with most engaging in "agent washing"—rebranding existing products like chatbots and RPA tools without substantial agentic capabilities.

Security vulnerabilities present another critical concern. The BodySnatcher vulnerability (CVE-2025-12420) discovered in ServiceNow's Virtual Agent API in January 2026 demonstrated how authentication flaws in agentic systems could allow attackers to impersonate legitimate agents, potentially compromising entire enterprise workflows.

Strategic Imperatives for SaaS Companies

The research consensus points to four critical actions for SaaS vendors seeking to survive the agentic transformation:

Cannibalise your own product. Companies must proactively replace their own features with AI agents before competitors do. The firms that delay this self-disruption will find themselves displaced by AI-native challengers building from first principles.

Move beyond seat licensing. Metronome's field research indicates that 73% of AI companies are still experimenting with pricing models, with the average company testing 3.2 different approaches in their first 18 months. Outcome-based and consumption-based models require sophisticated tracking infrastructure but align vendor incentives with customer value.

Build trust infrastructure. As Salesforce research confirms, governance is the number one barrier to agentic AI adoption among C-suite executives. Security, auditability, and human-in-the-loop controls are becoming mandatory requirements for enterprise deployment.

Leverage proprietary data. The competitive moat for SaaS vendors lies in their accumulated customer data and workflow intelligence. eToro's Alpha Portfolios, built on proprietary retail trading data from 40 million users, exemplifies how platform-specific data creates defensible AI capabilities that competitors cannot replicate.

The Road Ahead: 2026-2030

The SaaS industry is entering a period of unprecedented disruption. The companies that thrive will be those that embrace the shift from software for humans to autonomous service delivery, restructure their business models around outcome-based value, and build the governance infrastructure required for enterprise-scale agentic deployment.

By 2028, Gartner predicts, 90% of B2B buying will be AI agent intermediated, pushing over $15 trillion of B2B spend through AI agent exchanges. The transformation is not merely technological—it represents a fundamental rewiring of how enterprises create and capture value in the digital economy.

For investors, the message is clear: the agentic AI market represents one of the most significant growth opportunities in enterprise technology since the cloud computing revolution. For SaaS executives, the imperative is equally stark: adapt or face irrelevance in a market that will look fundamentally different by decade's end.

References

• Gartner Predicts 40% of Enterprise Apps Will Feature Task-Specific AI Agents by 2026 - Gartner, August 2025
• Gartner Predicts Over 40% of Agentic AI Projects Will Be Cancelled by End of 2027 - Gartner, June 2025
• Agentic AI Market Share, Size and Growth Outlook to 2030 - Mordor Intelligence, 2025
• AI Agents Market Worth $52.62 Billion by 2030 - MarketsandMarkets, 2025
• Agentic AI Outpacing Growth Rates of Traditional Generative AI - Omdia, September 2025
• The Future of AI Agents: Top Predictions and Trends to Watch in 2026 - Salesforce, January 2026
• Salesforce to Build US Army's Agentic AI Foundation - The Register, January 2026
• What's Next for AI in 2026 - ServiceNow, January 2026
• Rethinking B2B Software Pricing in the Agentic AI Era - BCG, 2025
• BodySnatcher Vulnerability in ServiceNow - AppOmni, January 2026