The Big Question
Let us ask you something directly.
You run a business, or you are thinking of starting one. You have heard about AI. You have seen the hype. But you are trying to figure out what it actually means for your business model.
Are you supposed to just add a chatbot to your website? Or is there something deeper happening?
We hear this question every week from business leaders and founders who visit our center near Pitampura Metro.
Here is the honest answer based on MIT research and industry analysis: AI is not just a tool to make existing businesses more efficient. It is enabling entirely new ways of creating, delivering, and capturing value. Companies that use AI to simply cut costs will be left behind. Companies that use AI to build new business models will dominate.
MIT Sloan researchers have identified four new business models for the AI era. Let us break them down.
Step 3: The MIT Framework – 4 New Business Models for the AI Era
MIT CISR researchers and colleagues used survey data from 2,378 companies to organize business models into four new categories. They used a hypothetical financial services company to describe how these models operate .
The Four Business Models:
| Model | Description | Example |
|---|---|---|
| Existing+ | Augment an existing business model with AI | A financial services company enhances traditional advisory by using AI to analyze customer information and provide personalized recommendations |
| Customer Proxy | Achieve customer outcomes through predefined processes executed by AI | A financial services company sets parameters to automatically manage a customer's investment portfolio |
| Modular Creator | Use AI to assemble reusable modules (including third parties) into tailored service bundles | A financial services company creates and recommends a bundle of investment, insurance, and credit products aligned with a customer's goals |
| Orchestrator | Use AI to assemble an ecosystem of complementary products and services with no predetermined process | A financial services company provides a fully managed wealth solution that automatically and continuously optimizes the customer's investment portfolio |
How One New Zealand Group Evolved
The ongoing transformation of telecommunications provider One New Zealand Group illustrates these business models in action. Currently, the company uses AI agents to :
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Help answer customers' frequently asked questions and assist employees in serving customers (Existing+)
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Act on requests to upgrade plans or create service tickets (Customer Proxy)
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Monitor power failures, forecast demand, and recommend action during weather-related service disruptions (Modular Curator)
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Looking ahead, they intend to bring autonomous AI agents to marketing operations (Orchestrator)
The Shift from App Economy to Agent Economy
The transition from app economy to agent economy represents a fundamental shift in how value is created and captured.
For most of the internet era, the app was the destination. Consumers opened an app to pay a friend, order dinner, book a ride, or place a bet. The companies that won built the best digital storefronts, captured user attention, and became the default interface for everyday economic activity .
That model is starting to shift. As AI evolves from answering questions to completing tasks, value may shift toward platforms where AI agents can actually transact. In that world, the interface matters less than the infrastructure beneath it .
What This Means:
| Before (App Economy) | After (Agent Economy) |
|---|---|
| Users navigate apps manually | AI agents execute tasks autonomously |
| Value is in the user interface | Value is in the execution layer |
| Companies compete for user attention | Companies compete for agent integration |
| Pricing is per seat or per user | Pricing is per action or per outcome |
| Engagement is the metric | Execution is the metric |
The Execution Layer:
The agent economy rewards companies that own the execution layer: payment networks and digital wallets, e-commerce and merchant platforms, local delivery and logistics systems, online marketplaces, and platforms that connect identity, trust, and fulfillment . These are the systems that make digital activity possible. They do not just attract the consumer; they help complete the transaction.
The "Services-as-Software" Model
Agentic AI is reshaping the economics of software and services. While the AI funding landscape is seeing record highs, the traditional SaaS model is under significant pressure .
The Shift:
| Traditional SaaS | Services-as-Software |
|---|---|
| Sell a tool or "seat" | Sell an outcome |
| Human does the work | Agent does the work |
| Pricing by user | Pricing by usage or outcome |
| Software as a product | Software as a service delivery |
Sectors Being Transformed:
| Sector | Traditional Model | Services-as-Software Model |
|---|---|---|
| IT | Human incident resolution | AI-driven, automated incident resolution |
| Sales & Marketing | Legacy CRMs | AI layers that Sales interfaces with directly |
| Legal | Lawyer-assisting copilots | Firm-serving autopilots |
| HR | Human recruitment | Automated top-of-funnel screening and outreach |
What This Means: Instead of selling a tool or "seat," these companies are selling an outcome. The transition implies a major shift in who is doing the work, from human to agent, that accompanies a change in pricing models from seats to usage, and ultimately, to purely outcome-based models .
The "Agents as a Service" (AaaS) Model
Industry leaders are predicting a fundamental shift in the software industry. NVIDIA CEO Jensen Huang has declared that the AI industry has reached an inflection point, shifting from generative AI chatbots to "Agents as a Service" (AaaS). Huang asserts that every SaaS company will evolve into an AaaS company, where AI agents act as digital employees—working, researching, and executing tasks on behalf of users rather than focusing mainly on text generation .
Key Trends Driving AaaS:
| Trend | What It Means |
|---|---|
| From Copilot to Autonomous | Systems will not just wait for prompts but act 24/7 as independent digital co-workers |
| Reinforcement Learning as a Service | Agents learn and improve continuously, creating efficiencies over time |
| Specialized AI Models | Large Tabular Models (LTMs), Large Action Models (LAMs), and Small Language Models (SLMs) serve specific tasks |
| Security and Trust | AI agents need their own scoped, temporary, and auditable identities |
The Changing Pricing Models
Pricing is one of the areas most affected by the rise of AI agents. Traditional subscription and seat-based models are giving way to hybrid approaches .
Emerging Pricing Models:
| Model | How It Works | Example |
|---|---|---|
| Usage-Based | Pay for what you use | Per API call, per token, per action |
| Outcome-Based | Pay for business results | Per customer support ticket resolved, per hire made |
| Hybrid | Blend of usage and outcome | Flat fee plus success-based bonuses |
The Challenge:
As AI agents enter more widespread use, traditional pricing models won't be adequate to reflect the true value exchange between provider and consumer. AI agents could conceivably give one user the power of many users and reduce the need for the number of seats needed in an organization, impacting the revenue of SaaS providers .
Gartner Predicts:
"By 2030, at least 40% of enterprise SaaS spend will shift toward usage-, agent-, or outcome-based pricing."
A recent survey found that 83% of AI-native SaaS companies currently offer usage-based pricing .
Real-World Implementation: Coforge's "Mod Squads"
Coforge has introduced "Mod Squads," a subscription-based delivery model that replaces traditional time-and-materials pricing with outcome-driven pricing .
Key Features:
| Feature | What It Means |
|---|---|
| Custom AI Teams | Customers assemble custom AI-native teams tailored to industry and engineering workflows |
| Pre-Built Agents | 130+ agents across industry-specific and engineering-focused categories |
| Expert-in-the-Loop | Senior AI specialists oversee, direct, validate, and course-correct agents |
| Fixed Subscription | Pay a fixed fee per month for each AI Mod Squad |
Measurable Outcomes:
| Use Case | Result |
|---|---|
| Banking loan origination | 70% reduction in cycle time |
| Insurance underwriting | 50% faster underwriting cycle |
This represents a clear departure from the traditional time-and-materials pricing model, providing enterprises with cost predictability while accelerating the transition to autonomous AI-driven enterprises .
The "Revenue-Sharing as Infrastructure" Model
Academics are also exploring new business models for AI platforms. A recent research paper proposes "Revenue-Sharing as Infrastructure" (RSI), where a platform offers its AI infrastructure for free and takes a percentage of the revenues generated by developers' applications .
Three Generations of AI Platform Business Models:
| Generation | Dominant Model | Analogy |
|---|---|---|
| First (2022-2023) | Pay-per-use (pay-per-token) | Gasoline |
| Second (2024-2025) | Freemium + Differentiation | Spotify |
| Third (Emerging) | Revenue sharing | YouTube |
Why RSI Matters:
| Impact | What It Means |
|---|---|
| Lower Entry Barriers | Developers without initial capital can participate |
| Aligned Incentives | Platform and developer both benefit from application success |
| Innovation Stimulation | More developers can build and experiment |
| Societal Impact | Unlocks "latent jobs dividend" in emerging economies |
The Rise of AI Agent Marketplaces
Major technology platforms are creating marketplaces for AI agents. Microsoft is extending the Microsoft Marketplace to include software agents, announced at Build 2026 .
Key Features:
| Feature | What It Does |
|---|---|
| Intelligent Discovery | Natural language search to find relevant agents |
| Multiple Storefronts | Agents displayed in Teams, Microsoft 365, Visual Studio |
| Listing Optimization | AI tools help developers optimize their listings for discoverability |
| Validation | All code is validated before listing |
The Opportunity:
If you have developed an agent that solves a problem, you can now sell it on a marketplace. Microsoft is providing tooling to help developers get their listings right. They have a separate AI tool called a "listing optimizer" that reviews listings and provides guidance on how to best improve them for discoverability .
The process of sharing needs to be curated and controlled, and if possible, tied to a revenue stream. Until recently, subsidized tokens have kept costs artificially low. Now companies like GitHub and Anthropic are moving to a more sustainable pricing model, increasing the cost of inferencing. As a result, switching AI projects away from a cost to a revenue source is high on CIOs' agendas .
What This Means for Businesses
For Existing Businesses:
| Action | Why |
|---|---|
| Audit your business model | Identify where AI can augment, not just automate |
| Explore Customer Proxy | Can you achieve customer outcomes through AI agents? |
| Consider Modular Creator | Can you assemble reusable AI modules into tailored bundles? |
| Aim for Orchestrator | Can you use AI to orchestrate an ecosystem of services? |
For Startups and Founders:
| Action | Why |
|---|---|
| Build AI-native from day one | AI should be core, not an add-on |
| Design for execution, not interface | The agent economy rewards platforms that complete transactions |
| Explore outcome-based pricing | Sell results, not tools |
| Consider the marketplace opportunity | Build agents that can be sold on emerging platforms |
How Coding Now Prepares You for AI Business Models
At Coding Now – Gurukul of AI, we teach the skills that matter for the AI economy.
Our Programs:
| Program | Duration | Skills Covered |
|---|---|---|
| AI Engineering Diploma | 6 months | Python, ML, LLMs, RAG, LangChain, Multi-Agent Systems, Deployment |
| Data Science | 4 months | Python, Pandas, NumPy, Statistics, ML, SQL |
| AI-Integrated Full Stack | 6 months | Python, Django/Flask, AI Integration |
What We Teach That Matters for AI Business Models:
| Skill Area | What You Learn |
|---|---|
| AI Literacy | Understanding what AI can and cannot do |
| Agentic AI | Building AI agents that take action |
| RAG and Vector Databases | Connecting AI to proprietary data |
| Integration | Connecting AI systems to existing workflows |
Our Location: 2nd Floor, Kapil Vihar, opposite Metro Pillar No.354, Pitampura, New Delhi – 110034
Step 4: Frequently Asked Questions
Q1: What are the new business models AI is creating?
MIT researchers have identified four: Existing+ (augment existing model with AI), Customer Proxy (AI executes predefined processes), Modular Creator (AI assembles reusable modules), and Orchestrator (AI assembles an ecosystem of services) .
Q2: What is the difference between the app economy and the agent economy?
The app economy rewards companies that own the user interface. The agent economy rewards companies that own the execution layer, where AI agents complete transactions .
Q3: What is "Agents as a Service"?
NVIDIA CEO Jensen Huang predicts that every SaaS company will evolve into an AaaS company, where AI agents act as digital employees working, researching, and executing tasks on behalf of users .
Q4: How will pricing models change?
Traditional seat-based pricing is giving way to usage-based and outcome-based pricing. Gartner predicts that by 2030, at least 40% of enterprise SaaS spend will shift toward usage-, agent-, or outcome-based pricing .
Q5: What is "Services-as-Software"?
Instead of selling a tool or "seat," these companies are selling an outcome. This represents a shift in who is doing the work from human to agent .
Q6: What is the "Revenue-Sharing as Infrastructure" model?
A proposed model where AI platforms offer free infrastructure and take a percentage of revenues generated by developers' applications, lowering entry barriers for developers .
Q7: Does Coding Now teach skills for the AI economy?
Yes. Our programs cover AI literacy, agentic AI, RAG, and integration skills for the AI economy.
Q8: How do I enroll?
Call +91 9667708830 or visit our center at 2nd Floor, Kapil Vihar (Opp. Metro Pillar No.354), Pitampura, New Delhi – 110034.
Step 5: Final Tagline
"AI is Not Just Changing How We Work. It is Changing How We Create Value."
Hashtags:
#AIBusinessModels #AgenticAI #AaaS #FutureOfWork #BusinessInnovation #AIEconomy #CodingNow #GurukulOfAI
Step 6: A Note on AI Business Models
The data is clear. The shift from app economy to agent economy is real and accelerating. Companies that understand these new business models will dominate the next decade. Those that do not will be left behind.
MIT Sloan's research shows that ecosystem driver business models have grown from 12% to 58% since 2013—and only these companies exceeded industry-average revenue growth . This is not a theory. It is happening.
The question is not whether AI will change your business model. It is whether you will be ready.
At Coding Now, we teach the skills that matter for the AI economy. Come visit us. Take a free demo class. See what is possible.
Your AI business model journey starts now.
Contact Us
Phone: +91 9667708830
Email: info@codingnow.in
Website: https://codingnow.in/
Address:
2nd Floor, Kapil Vihar (Opp. Metro Pillar No.354)
Pitampura, New Delhi – 110034
Backlink to main website: Explore AI Engineering Diploma and other courses at Coding Now – Gurukul of AI
