“How did you go bankrupt?” Bill asked.
– Ernest Hemingway’s 1926 novel, The Sun Also Rises
“Two ways,” Mike said. “Gradually, then suddenly”
When ChatGPT was introduced in November 2022, it was mostly treated as a gimmick. Fast forward 3 years and Generative AI is posing a real threat on the $4 trillion opportunity.
The services market which encompasses $2 trillion spent on services another $1.5 trillion spent on labor, $300 billion on SaaS, and $380 billion spent annually on infrastructure, is being fundamentally reshaped by Agentic AI. The concept is simple but revolutionary: it’s been dubbed Service as Software (the new SaaS).
For venture capitalists and ambitious founders, this is the clearest multi-trillion-dollar opportunity since the mobile or cloud revolutions. It represents a Total Addressable Market (TAM) an order of magnitude greater than all of enterprise software combined, targeting the massive pools of labor spend.
The Core Thesis: Closing the “Hand-Holding Gap”
The “Service as Software” thesis is founded on a fundamental economic shift: the marginal cost of reasoning approaches zero. Intelligence, which was once uniquely human, is becoming abundant, delivered directly through AI agents that can independently perform tasks on a user’s behalf by reasoning, planning, and leveraging memory.
This transition solves the historical problem that made services unattractive to VCs: low margins, complex delivery, and lack of scalability. AI changes the math:
- Margin Expansion: AI allows gross margins in formerly BPO-style services (20–40%) to rise to SaaS-level 70–90%.
- Outcome Delivery: Enterprises measure success in outcomes, not consumption. AI agents close the “hand-holding gap,” providing the personalisation and trust consultants historically delivered, but scaled globally at SaaS economics. This makes AI credible enough to replace consultants entirely.
The Pressures Driving the SaaS Revolution
The traditional professional services industry, including management consultancies and IT service firms, faces an “existential moment”. Take a look at their stocks as of today:
It’s worth mentioning that the large professional services companies are trying to fight this trend with investments, acquisitions and leaning in on building their own AI Agents. CB Insights latest report dives deeper into the future of these firms:
AI agents are rapidly tackling professional services firms’ bread-and-butter workflows.
According to CB Insights survey data, enterprises are already deploying or planning to deploy agents across departments, with customer support, marketing, and software development leading adoption.
The Future of Professional Services – How firms will capture value in the AI agent era (Source: CB Insights)
Revenue Model Disruption and AI Automation rank as the highest threats (Risk Level 9/10).
- The DIY Tsunami: Sophisticated AI tools enable clients to bypass consulting for routine analyses. Clients now recognize that building a SWOT analysis takes just five minutes with AI tools. DIY AI solutions for knowledge-intensive services like Business Planning offer 70–80% professional quality while delivering 90–95% cost savings.
- Financial Erosion: This leads to immediate 20-30% pricing pressure as clients expect AI productivity gains to be reflected in their billing. Former PwC partner Alan Paton warns that up to 50% of audit, tax, and strategic advisory jobs will be automated within 3-5 years.
- The Compressed Timeline: This convergence of immediate revenue pressures and medium-term structural changes creates a compressed transformation timeline, requiring decisive action within the next 12–24 months.
The Startup Playbook: 7 Categories of Opportunity
Startups are directly addressing this vacuum, focusing on replacing legacy service providers in complex enterprise areas like compliance, cash flow, and cybersecurity. This opportunity is attracting experienced founders and has resulted in companies in this emerging category raising over $1.5 billion in the past two years.
Grove Ventures did a great job in pointing out 7 distinct categories where startups are applying the “Service as Software” model:
- Financial Operations: Solutions that streamline collections, payments, treasury, and financial reporting.
- Customer Support: Technologies to improve response, service, and interaction with customers.
- Security and IT: Tools that protect enterprise systems and information from technological threats and help manage them. The SOC AI agents & copilots market shows the highest funding momentum, reflecting the direct solution to the analyst shortage problem.
- Risk and Compliance: Systems that monitor regulatory adherence and safeguard organizational activity.
- People Operations: Automation and optimization of sourcing, recruiting, and managing employees.
- Go to Market: Platforms that support product launches, digital marketing, and sales.
- Business Operations: A focus on workflows and improving organizational operations.
This is also consistent with the areas in professional services that are seeing the highest penetration of AI:
Below is a partial mapping of Israeli startups operating in the ‘Service as a Software’ space:
Investment Models: Betting on Outcome Delivery
Founders are adopting two major strategies to deliver service outcomes with software economics:
1. Outcome-As-A-Service (OaaS)
This model shifts pricing entirely to guaranteed results (Scenario 4).
- Risk-Sharing Economics: Gruve’s security consulting model uses a “zero monthly fee, pay only if hacked” approach, demonstrating how outcome-based pricing aligns incentives and achieves remarkable 80% gross margins.
- Mass-Market Scale: Agentic AI tools are poised to revolutionise individual financial life by performing extensive financial planning and analysis. Agents will soon examine balances and suggest optimal payment strategies, a breakthrough that can scale financial advice to the millions of middle-class Americans who cannot afford human advisers.
2. The AI-Enabled Roll-Up
This strategy pairs applied AI technology with the direct ownership and operation of service businesses acquired via M&A.
- New Efficiency Benchmarks: The goal is to eliminate the historical tradeoff between growth and profitability, aiming for 30–40% or more profit margins and setting sights on a new Rule of 60 standard.
- General Catalyst shared some examples:
- Eudia (Legal): Automates M&A due diligence and compliance, delivering complete legal outcomes as a subscription service by combining proprietary AI with an acquired delivery team.
- Titan MSP (IT Services): Deployed AI tools to automate routine work, cutting tasks like new user onboarding from weeks to minutes.
Where VCs are Investing in Agent Infrastructure
Venture capital investment in AI startups targeting the services industry has reached record highs in 2025, with over $49.2 billion invested in generative AI alone in the first half of the year, surpassing the $44.2 billion total for all of 2024 and more than doubling 2023. AI-related investments now account for about 31% of all global VC deal volume, and the software & services segment leads in terms of transaction value and frequency. To win the SaS market, startups must master the infrastructure that makes agents reliable, scalable, and trustworthy. Smart money is flowing into the layers that ensure agents work in production, not just pilots.
- Orchestration and Governance: Enterprises often stall at implementation due to integration complexity, vendor sprawl, and governance concerns. This creates a strategic opening for firms to act as orchestrators. Startups focused on giving agents better context, such as those in Data preparation (median Mosaic: 884) and Memory systems (median Mosaic: 689), show high private market momentum, creating the scaffolding for more powerful agents.
- Proprietary Data Moats: The most powerful agents are those grounded in high-quality, proprietary data. Founders must focus on activating client and firm data. Currently, only one-fifth of the ecosystem is focused on vertical (industry-specific) applications.
- AI-First Applications: Investors favor intelligence-first solutions built specifically for AI. For instance, Harvey AI in legal tech, which drafts contracts and suggests negotiation strategies, is a leading example of Vertical AI.
Conclusion: The Imperative for Founders
The services sector is transitioning from being “gradually, then suddenly” disrupted. The transformation is already forcing incumbents like Accenture to exit staff who cannot be retrained for the age of AI.
For founders, the opportunity is unprecedented. The next wave of enduring software companies will be those that master the “Service as Software” model. The winners will be founders who:
- Own valuable data sources.
- Solve real labor shortages (especially in professional services).
- Create entirely new service categories with AI at the core.
Are you building the next generation of AI-native services? We are actively investing in the infrastructure and application layers that will redefine the $4 trillion services market. I’d love to hear about your vision for the future of applied AI.
Shameless plug: At Remagine Ventures we made several investments in this space that remain in stealth. If you’re building an AI Agent targeting these areas, we’d love to speak with you!
He is a former General Partner at Google Ventures (GV) in Europe, former head of Google for Entrepreneurs in Europe, and founding head of Campus London, Google's first startup hub. Eze writes on Israeli tech, venture capital, artificial intelligence, and founder strategy.
He is also the founder of Techbikers, a nonprofit that brings together the startup ecosystem on cycling challenges in support of Room to Read.
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