How digital business models will evolve in the era of agentic AI

Researchers have identified four new business models for the age of agentic artificial intelligence.

Existing+. Augment your existing business model with AI.
Customer proxy. Achieve customer outcomes through predefined processes executed by AI.
Modular creator. Use AI to assemble reusable modules (including third parties) to help customers achieve outcomes without predetermined processes.
Orchestrator. Use AI to achieve customer outcomes by building an ecosystem of complementary products and services without requiring predetermined processes.

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If your company is pivoting amidst a changing technology landscape, rest assured that you are not alone. A recent research brief published by the MIT Center for Information Systems Research outlines how business models are evolving to keep pace with advances in artificial intelligence, and what it will take to successfully navigate the changes.

Unique digital business model

To understand new business models in the AI era, it helps to first unpack old models. 2013, MIT CISR Researcher and We have identified four digital business models.

supplier A company that sells products through a third party, such as a manufacturer.
omnichannel Businesses with a digital and physical presence, such as retailers and banks.
modular producerprovide plug-and-play products or services, such as payment service providers.
Ecosystem driving forceprovides a go-to destination in a specific customer domain (e.g., housing) and connects customers to providers.

These models have undergone significant changes over the past 12 years, with companies leading or participating in digital ecosystems becoming much more prevalent than traditional brick-and-mortar sellers. Focusing on companies' primary models, companies with ecosystem driver business models have grown from 12% of companies in 2013 to 58% of companies in 2025, while supplier and omnichannel business models are currently less prevalent. This is primarily because they were the only of the four companies to exceed industry average revenue growth.

These changes, coupled with the rapid adoption of machine learning and all forms of AI, including agent AI, generative AI, and robotic AI, have prompted the development of new business model frameworks.

Four business models in the AI era

For the latest information, see Weill, Woerner, and colleagues. Using survey data from 2,378 companies between 2013 and 2025, Gayan Benedict organized business models into four new categories. They used the example of a hypothetical financial services company to explain how their business model would work in theory.

Existing+: These companies are enhancing their existing business models with AI. Here, financial services companies can enhance traditional advisory processes by using AI to analyze customer information and provide personalized recommendations.
Customer representative: These companies now use predefined processes supported by AI to achieve customer outcomes (within guardrails). In this case, financial services companies can set parameters to automatically manage their customers' investment portfolios.
Modular creator: Similar to manufacturers of plug-and-play products, these companies use AI to assemble reusable modules (including third-party modules) to create customized service bundles. Applying this model, financial services companies can create and recommend bundles of investment, insurance, and credit products tailored to customer goals.
Orchestrator: These companies are using AI to achieve customer outcomes (within guardrails) by building an ecosystem of complementary products and services. In this case, financial services companies can offer fully managed wealth solutions that automatically and continuously optimize their customers' investment portfolios.

How One New Zealand Group evolved its business model

The continued transformation of telecommunications provider One New Zealand Group shows these business models in action. For example, the company is currently using AI agents to answer frequently asked customer questions and help employees serve customers (Existing+ model). Respond to requests to upgrade plans or create service tickets (customer proxies). Monitor power outages, predict demand, and recommend actions during weather-related service interruptions (Modular Curator).

Looking ahead, One NZ plans to introduce autonomous AI agents (orchestrators) into its marketing operations. Agents can create personalized campaigns and adapt them based on customer responses. Marketing teams set goals and guardrails for the AI agent and monitor its performance.

Researchers say companies looking to adapt to the One NZ way of doing things need to understand where they can create value. Does your company simply assist your customers, or can you express their goals through autonomous actions? Is your business execution built on structured processes, or can you adapt those processes with the help of AI agents based on your customers' desired outcomes?

Leaders who want to understand the opportunities that AI presents to their companies can start by identifying existing AI-enabled business models that can be scaled and the corresponding AI capabilities that companies need to build.

Read the research summary: “Business models in the age of AI”

This article is based on research by Peter Weill, Ina Sebastian, Stephanie Woerner, and Gayan Benedict at the MIT Information Systems Research Center.

peter weil He is a senior research fellow at MIT Sloan and president of MIT CISR. His research explores future trends such as digital business models, IT investment portfolios, and AI maturity models to help organizations stay competitive. Ina Sebastian I am a researcher at MIT CISR. She researches how large enterprises transform to succeed in the digital economy, with a focus on digital partnerships, value creation, and capturing value in digital models. Stephanie Werner He is a Principal Investigator at MIT Sloan and Director of MIT CISR. She researches how companies use technology and data to build more effective business models and how to manage the associated impacts on organizational change, governance, and strategy. Gayan Benedict He is an industry researcher at MIT CISR and a technology partner at PwC Australia.

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