Service-as-a-Software: How AI Enables the Next SaaS Frontier
The transformation unleashed by artificial intelligence already feels relentless. Now AI is poised to march directly into the core functions of business and catalyze the creation of a new tech market: Service-as-a-Software (SaaS).
This concept represents the next frontier of software development, pushing beyond the traditional boundaries of Software-as-a-Service (SaaS 2.0) to create systems that don't just support human work but can autonomously perform entire workflows. This shift has the potential to disrupt trillion-dollar markets by turning labor into software and transforming how services are delivered, priced, and scaled.
Unlike the incremental improvements seen in previous software evolutions, Service-as-a-Software stands to dramatically expand addressable markets by tapping into workforce spend rather than just software budgets.
For investors, entrepreneurs, and business leaders alike, understanding this paradigm shift is crucial for navigating the next wave of technological disruption.
Definition and Scope
Service-as-a-Software allows traditional services, typically requiring human involvement, are automated or transformed into software-driven solutions. The focus is on using software to replicate, augment, or replace services, primarily through AI agents that handle tasks autonomously. These AI agents engage in workflows, make decisions, and deliver outcomes with minimal human intervention.
To understand Service-as-a-Software and how we arrived here, let’s look at the evolution of SaaS:
- First Wave (Cloud): SaaS brought services online, representing a significant shift from on-premise software to cloud-based platforms. This wave created "systems of record" which serve as authoritative sources of truth for business data.
- Second Wave (Cloud + Fintech): Financial technology functions were added, increasing revenue by enabling SaaS companies to embed financial services within their software offerings. Toast exemplifies this evolution, starting as a mobile app for restaurant loyalty programs before integrating payment processing, lending, and payroll services. These became "systems of engagement" software that facilitated communication and interaction between businesses, employees, and customers.
- Third Wave (Cloud + Fintech + AI): We're just entering this third wave, which expands SaaS by turning labor into software through AI capabilities. This wave is creating "systems of work" software that provides decision-making and task execution, delivering complete services like a human team would.
What enables this third wave is the development of AI with true reasoning capabilities.
Earlier AI (System 1 thinking) relied on pre-trained patterns, excelling at simple tasks but failing at novel situations requiring reasoning. Recent advances in AI reasoning (System 2 thinking) allow systems to pause, evaluate outcomes, and solve complex problems through thoughtful processes.
This reasoning layer is the critical engine for Service-as-a-Software, allowing AI to go beyond mimicking patterns to making decisions based on reasoning. Four distinct AI agent archetypes are emerging in this new ecosystem:
- Vertical Application Agents: These focus on bounded, well-defined tasks representing normalized workflows across companies, combining AI capabilities with deep functional knowledge.
- Multimodal Agents: These agents handle workflows involving multiple modalities (text, video, voice, image) and will revolutionize human-computer interactions.
- Horizontal Agentic Platforms: These platforms integrate common data sources, tools, and guardrails to build agents for different workflows.
- Agentic Interfaces for SaaS: Incumbent software platforms adding agent overlays to capture workflows that happen within underlying systems of record.
A critical aspect of Service-as-a-Software is the disruption of pricing models. Unlike traditional subscription-based SaaS pricing, companies in this space are increasingly selling units of work completed rather than access to software. Three pricing models are emerging:
- Platform + Agent Fee: A base platform fee plus a usage-based fee for an AI agent functioning as a full-time employee.
- Platform + Outcome-Based Pricing: A hybrid model combining platform fees with charges tied to specific outcomes.
- Pure Outcome-Based Pricing: Enterprises pay solely for achieving defined business outcomes, ideal for high-volume use cases that replace significant operational expenses.
The market opportunity is enormous, as Service-as-a-Software taps into workforce spend rather than just software budgets. For example, while Salesforce generated $35 billion in revenue last year, annual spend on sales and marketing salaries totaled around $1.1 trillion, according to Foundation Capital, NFX. By automating tasks traditionally performed by human teams, Service-as-a-Software solutions can capture a significant portion of this much larger market.
Macro and Market Trends
Several converging factors explain why Service-as-a-Software is emerging as a crucial innovation now:
Labor Market Tightness: Advanced economies missed up to 1.5% of GDP growth in 2023 due to labor shortages, and demographic trends suggest this squeeze will intensify. To maintain GDP growth, these economies need additional labor supplies or productivity growth, with labor-substituting AI emerging as a viable solution.
AI Investment: AI applications, infrastructure, and related services are projected to attract $632 billion of investment by 2028. Major initiatives like The Stargate Initiative (backed by OpenAI, SoftBank, and Oracle) are investing billions in AI infrastructure. Gen AI investments are projected to increase by 60% in the next three years, with 75% of executives ranking AI/GenAI as a top three strategic priority.
Infrastructure Readiness: Record-high infrastructure investments are creating unprecedented readiness for Service-as-a-Software applications, with the total addressable market for AI-related hardware and software projected to grow 40-55% annually, reaching between $780 billion to $990 billion by 2027.
We identified three key trends shaping this landscape:
- Agentic AI: AI capable of autonomous action and environmental adaptation, marking a major advance in automating complex workflows and decisions.
- AI Assistants: Personalized digital assistants that understand context, manage tasks, and offer guidance, continuously evolving to meet individual needs.
- Embodied AI: Intelligence designed to sense, act, and learn, extending beyond static data to perceive and respond in real-time.
Category Insights
The investment landscape for Service-as-a-Software reveals significant geographic disparities. Pitchbook data shows that an overwhelming majority of venture-funded firms are based in the United States, while Europe lags considerably. Within Europe, most capital flows to startups in France, the UK, Israel, and Germany.
The largest funding rounds occur almost exclusively for U.S.-based companies, many valued at over a billion dollars, according to Pitchbook. Recent notable funding rounds include Synthesia ($180M Series D), Hebbia ($130M Series B), Harvey ($100M Series C), and Cognigy ($108M Series C).
Last year, this space saw a massive surge in VC deals. According to Pitchbook, there were 192 deals for a toal of $54.46bn, up from 123 deals that raised $1.3bn in 2023.
In terms of investment activity, US firms dominate as the most active investors by a wide margin. The most active global investors include Sequoia Capital (which invested in Harvey, Sierra, and Clay), Andreessen Horowitz (Hippocratic AI, Hebbia, Decagon), and Foundation Capital (Tennr, Sedric, Oliv). In Europe, MMC Ventures and Seedcamp are the leading investors in this category.
Conclusion
As Service-as-a-Software leverages advances in AI capabilities, particularly reasoning abilities, this new frontier enables software to autonomously perform tasks previously requiring human intervention. The implications for businesses, investors, and the broader economy are profound.
For investors, the opportunities are significant but require careful navigation of new business models, pricing structures, and valuation approaches. The shift from selling access to software to selling completed units of work fundamentally changes how these companies must be evaluated and valued.
For businesses, Service-as-a-Software offers the potential to dramatically reduce costs, increase productivity, and reallocate human resources to higher-value activities. However, it also presents challenges in implementation, workforce transformation, and measuring return on investment.
As we stand at the beginning of this third wave of software evolution, it's clear that Service-as-a-Software will play a crucial role in shaping the future of how businesses operate and how value is created in the digital economy. Those who understand and embrace this shift early will be best positioned to capitalize on the trillion-dollar opportunity it represents.