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Service as a Software: No it’s not SaaS, But a New Business Model in Age of AI – What Is it and Why It Matters To Your Business ?

Being Human for a Better Tomorrow in the Age of AI
  • March 14, 2025
  • 39th edition
Service as a Software No it s not SaaS But a New Business Model in Age of AI What Is it and Why It Matters To Your Business

Welcome to the 39th edition of MindVista’s Being Human in the Age of AI series, exploring AI’s role in empowering individuals, enterprises, and society.

Now, imagine a business model where AI doesn’t just provide tools but delivers results—scalably, autonomously, and adaptively. Enter Service as a Software: not a toolbox for rent, but an AI-powered engine driving outcomes, redefining revenue, and building lasting competitive edge.

This 39th edition unpacks this emerging model, its six principles, and the journey ahead with lead indicators.

What is Service as a Software?

Service as a Software is a new business model born in the Age of AI defined by six foundational principles explained below and objectively measurable. (see Sidebar 1 for indicators)
  • 1. Outcome-Driven Business Model: Seamlessly integrates advanced AI technology with innovative outcome-based monetization, creating differentiation through value delivery rather than mere software access.
  • 2. Decoupled Revenue from Costs: AI-centric automation allows services to scale revenue and manage costs independent of human headcount. Technological infrastructure and AI model training represent fractional costs compared to the exponential growth in revenue potential, enabling scalability and agility.
  • 3. Autonomous Operation with Minimal Human Intervention: Leverages state-of-the-art AI systems and capable of independently executing complex tasks, decisions, and services with minimal or no human oversight.
  • 4. Ethical and Secure: Builds trust by high quality service with accurate models and trained data continually checked for bias, security, quick qualified human escalations and proven statistical review for quality and ethical by instituitional review board.
  • 5. Continuous Intelligence and Adaptation: Employ AI to learn continuously from interactions and environment, and dynamically adapt services. The model anticipates customer needs, intelligently prompts engagement, manages usage patterns, and optimizes resources, transcending traditional automation and ensures high customer satisfaction (CSAT) leading to a high net promoter score (NPS)
  • 6. Sustainable Competitive Advantage: Composite that is functional of competitive advantage from data , connectivity or integrations with systems and intrinsic model advantage.

Service as a Software: Evaluation of Five AI Innovators Against the Framework

The “Service as a Software” model represents a paradigm shift in how AI delivers value—moving from software tools to outcome-focused services, non-linear costs, and scalability enabled by technology.

Research for the 38th edition called out that only five companies out of the 37 AI innovators (13%) featured in 33rd to 37th editions in FS, Pharma, Healthcare, Enterprise Software, and Physical AI, have a Service as a Software business model.

Let’s apply the six foundational principles and validate how many of them are truly Service as a Software businesses and see where they stand.

1. Betterment (Wealth Management)

Score: 5/6 – Excels in autonomous operation (managing 900,000 portfolios with minimal staff) and continuous intelligence (processing 14TB of market data daily), but revenue remains partially tied to assets under management rather than purely outcome-based.

2. Woebot (Mental Health Support)

Score: 6/6 – The quintessential example with perfect alignment across all principles: outcome-driven (22% faster depression remission), fully autonomous (2M+ users with minimal staff), ethically designed (rule-based CBT for safety), continuous learning from interactions, and clinical validation creating a sustainable competitive advantage.

3. Moxi (Hospital Robot)

Score: 4.5/6 – Strong in outcome delivery (nurse time savings) and adaptation (learning hospital layouts), but requires more environmental structuring and occasional human intervention for complex situations, limiting full autonomy.

4. Wealthfront (Automated Investing)

Score: 5/6 – Similar to Betterment with strong automation and scaling, featuring tax-loss harvesting and portfolio rebalancing, though its competitive advantage is increasingly challenged as AI-driven investing becomes more commonplace.

5. Figure (Humanoid Robotics)

Score: 5/6 – Pioneering physical task automation with strong decoupling of revenue from human costs, though nascent technology means autonomy in unstructured environments remains challenging, requiring occasional human oversight for complex situations.

These scores reveal a spectrum—from Woebot’s full alignment to Moxi’s promising but partial fit—showing how close (or far) today’s innovators are from the Service as a Software ideal.

See Sidebar 2 on Woebot.

Question: If you have built or are building an AI-driven business, what is your score?

Why Should You Bother with Service as a Software?

Just one company (Woebot) across five industries stands out not only for creating a new service but adapted to a new business model. That begs the important question: if this is so hard then why bother?

Let’s go back in history.

While not an AI business, the Google search business driven by its proprietary page ranking algorithm is a forerunner to the Service as a Software business (search is the outcome, algorithm scaled with Internet growth, autonomous and human independent).

With page ranking algorithm as its core technology offering search as a service, Google soared. It’s search business grew from $220K (yes 220K) revenue in 1999 to $29B in 10 years. Google search competitors like Yahoo, Altavista, Excite, Lycos, Ask Jeeves and many others were shut down or became bankrupt or irrelevant.

As you can relate, getting to a Service as a Software business could mean market dominance in the Age of AI. If you’re competing against a Service as a Software (SaaS 2.0) model, you’re not just risking market share—you risk becoming irrelevant, obsolete or even extinct.

Service as a Software demands focus, AI infrastructure demands investment, autonomy takes time, and ethics require vigilance. It’s a journey, not a destination.

Service as a Software: Template for AI Driven New Business

As you evaluate and work on disruptive AI to create new markets and services, explore and apply the six principles on a continuous basis:
  • How can technology learn and adapt to link revenue to outcomes than output or input?
  • How and at what point will revenue growth >> cost growth?
  • How to continuously improve technology to reduce human intervention?
  • How to use service data to anticipate and improve service?
  • How to create sustainable service advantage using data and integrations with external systems?

The lead indicators can help indicate where business is today and inform strategies to improve on an ongoing basis.

Remember, it’s a journey, not a destination. Sustained effort—testing, learning, and refining—unlocks the full potential of Service as a Software.

Question: How can you improve your score and lead indicators with each iteration?

Takeaways

AI-led Accelerated Innovation (AI for AI) continues to transform industries. AI technology and infrastructure are rapidly evolving, supporting super agency to deliver revenue and strategic value.

But it’s not only about technology. New business models are also emerging in the Age of AI. My hypothesis is that those who innovate on both technology and business models will become runaway leaders, leaving others far behind.

Being efficient is one path; being disruptive is another. Both deserve pursuit.

To drive disruption, ask these key questions:

  • What hard problems can you solve in your business and function? Ask Peter Thiel's question: What important truth do very few people agree with you on?
  • What value can be created by solving this problem?
  • How will AI enable the solution?
  • What internal and external partners are needed to plan and execute?
  • How can you be part of this change in your industry with your know-how and skills?
  • What can you do to maximize new money for AI initiatives?
  • What innovations in business models will optimize your AI investments?

Final Word

Across our five editions on AI for AI, we’ve seen how a small team at DeepSeek disrupted AI itself, and explored 37 AI and Tech-led innovators transforming FS, Pharma, Healthcare, Enterprise Software, and Physical AI. Even business models are changing in the Age of AI and More exciting examples await in upcoming editions.

In democratized AI, anyone, anywhere can achieve remarkable results with courage, intelligence, and tenacity.

And the time to act is now.

What a promising start to 2025—the first year of the next quarter-century.

Explore, join, and stay tuned for more!

Love to hear your comments, thoughts, and ideas.

Best wishes,

Sidebar 1: Service as a Software Principles, Lead Indicators and Aspirational Metrics

  1. Outcome-Driven Business Model

    • Indicator: % Revenue from outcomes

    • Aspirational Metric: > 95% of revenue linked to outcomes

  2. Decoupled Revenue from Costs

    • Indicator: Revenue/Cost

    • Aspirational Metric: 100x growth in revenue < 10x cost

  3. Autonomous Operation with Minimal Human Intervention

    • Indicator: Human Intervention Rate (HIR) (%) = Total number of AI-processed tasks / Number of tasks requiring human intervention × 100%

    • Aspirational Metric: <5%

  4. Ethical and Secure

    • Indicator:
      a. AI Error Rate (AER)% = False Positives + False Negatives / Total number of transactions ×100%

      • Aspirational Metric: <5%
        b. Security Incident Rate % = Percentage of security risks or attacks not detected by AI system / Total number of transactions

      • Aspirational Metric: <2%

  5. Continuous Intelligence and Adaptation

    • Indicator: AI Driven Engagement Lift (ADEL)% = Baseline Daily or Monthly Active Use / Increase in DAU or MAU due to AI * AI CSAT or NPS %

  6. Sustainable Competitive Advantage

    • Indicator: AI Moat Index =
      a) Data Network Effect (DNE)
      b) Ecosystem Connectivity Score (ECS)
      c) Model Advantage (MA)

Sidebar 2: Who is Woebot and Why Do They Score Well?

Woebot Health is pioneering AI-driven mental health support with its chatbot that provides cognitive behavioral therapy (CBT) and dialectical behavior therapy (DBT) techniques. Available 24/7, Woebot aims to bridge the gap in mental health services, especially in areas with limited access to therapists.

Woebot uses AI to conduct natural language processing for understanding user inputs and delivering personalized therapeutic responses. The AI follows a rule-based CBT rather than generative AI, ensuring consistent and evidence-based therapy. It also uses machine learning to adapt responses based on user interactions, enhancing the therapy experience over time.

  • Outcome-Driven: Achieved 22% faster remission in depression symptoms (JAMA).
  • Autonomous & Scalable: Serving 2M+ users with minimal human oversight.
  • Ethical & Safe: Rule-based CBT ensures consistent, evidence-based outcomes without generative AI risks.
  • Continuous Learning: Learns continuously from user interactions, delivering increasingly personalized therapy.
  • Sustainable Advantage: Extensive, proprietary interaction data fuels continuous service improvement.
  • Recognition: MedTech Breakthrough Award, leading innovation in mental health accessibility.
“AI is a language. Treat it like one: practice, iterate, and mind your grammar prompts, assumptions, and verification.”

II. Questioning / Asking

Good conversations flow from well‑sequenced questions—topical, simple, coherent, cohesive.
LLM Conversation Example 1
Q: What are empirical judgments?

A: Empirical judgments are based on observation, experience, or experimentation.
Q: What are moral judgments?

A: Moral judgments are based on ethical principles and values.

IV. Judgment

“The structure of a language affects its speakers’ worldview and cognition.”
— Henry Hazlitt
“The art of questioning is the source of all knowledge.”
— Thomas Berger
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