Provost Rupendra Paliwal introducing the AI & Business Transformation Executive Roundtable

AI-Driven Business Models

Apr 02, 2026, by Staff

In sectors from retail to healthcare and marketing to finance, artificial intelligence (AI) continues to transform how organizations operate. AI has strategic applications in business operations, customer engagement, and industry-specific workflows.

Organizations that successfully leverage AI can gain a competitive advantage in the marketplace. And business professionals who know how to apply AI tools to real-world challenges are needed across industries.

Developing and implementing AI-driven business models requires strategic insight and AI expertise. Both new ventures formulating their first business plans and established organizations updating their strategies can benefit from assessing how AI can fit into their business models. 

AI Trends in Business

The impact of AI in business continues to escalate. Organizations plan to invest more in AI than in cybersecurity or infrastructure modernization in the next two years, according to a 2025 McKinsey & Co. survey. 

In spite of the strong interest in artificial intelligence, nearly 2 in 3 organizations remain in the early stages of scaling AI, according to McKinsey. And while 88% regularly use AI in their business functions, only 7% have fully deployed and integrated AI across their organizations.

Most organizations remain in the exploratory phase, with 84% of companies stating that they have not yet redesigned their jobs or workflows around AI, according to a 2025 Deloitte survey.

Organizations are employing several different types of AI. In recent years, both predictive and generative AI tools have been adopted by organizations. The use of AI agents, also known as agentic AI, is growing. 

  • Predictive AI: Analyzes data to identify trends, track data patterns, and forecast outcomes 
  • Generative AI: Generates original content, such as text, images, and videos
  • Agentic AI: Makes decisions and solves problems autonomously without user prompts 

Over 60% of organizations are experimenting with AI agents, according to McKinsey. And 85% of companies believe they will use customized AI agents in their business operations, Deloitte reports.  

Business professionals in today’s workforce need AI skills. Raising the overall AI fluency of employees ranks as the top talent strategy priority for businesses, the 2025 Deloitte survey found. 

Resources on AI Business Trends 

How are organizations using AI today, and what will change in the near future? The following resources contain information from surveys of business leaders on how they are using AI in their businesses and forecast the impact that the technology will continue to have on how businesses operate to maximize profits. 

What Is an AI-Driven Business Model?

A business model outlines how an organization plans to create value and make a profit. The core components of a business model are the organization’s value proposition, revenue streams, critical assets, and target customers. 

AI-driven business models are those that integrate AI technology into any of these components. For example, a company might use AI tools to solve a problem for customers or to increase its profits by improving its operational efficiency. Similarly, a business model can explain how AI will be used to identify and attract target customers through personalized marketing plans. 

When formulating a business plan, professionals can include how AI will be used in areas such as the following:

Creating Value

  • Personalization: AI can be used to create hyper-personalized products and services for potential customers. 
  • Product Development: AI can be employed to design new products and services to market to customers with unmet needs. 
  • Automation: Organizations can optimize their workflows, reduce human error, and save time and money by integrating AI automation tools into their business operations. 

Delivering Value

  • Customer Service: Chatbots and virtual assistants can quickly address customers’ issues, while AI-driven customer management systems can improve the level of engagement organizations have with their customers. 
  • Logistics: AI can be used in forecasting, data processing, and coordination to optimize organizations’ supply chains. 
  • Feedback Analysis: AI can analyze users’ feedback to identify pain points and highlight trends for organizations. 

Capturing Value

  • Pricing Strategies: AI can be deployed to implement dynamic pricing that factors in demand, behavior analysis, and real-time data. 
  • Workflow Efficiency: AI tools can be used to reconfigure workflows to reduce operational costs and boost efficiency, leading to higher profit margins and more competitive prices. 
  • Data Analytics: AI data analytics tools can be employed to improve operational decision-making and deliver value to customers. 

Both new and established businesses can integrate AI into their business models. An AI-driven business model is one that outlines how an organization will provide value using AI or create new business opportunities based on providing AI-enhanced services. 

Resources on AI Business Models

Integrating AI into business models requires a specialized understanding of AI’s capacities. The following resources explore different approaches to capturing AI’s transformative potential in business models.

Examples of AI-Driven Business Models

Effective business models define an organization’s goals, strategic approaches, and resource allocation. An AI-driven business model explains how artificial intelligence can help the organization meet its business goals. For instance, the business model may cover areas such as:

  • Targeted Marketing: AI can be used to create personalized outreach ads, videos, and emails that target specific customers. 
  • AI Automation: AI tools can be employed to automate the organization’s data management, invoicing, order processing, customer onboarding, and other time-consuming tasks. 
  • Custom Software: The organization can develop its own custom software using AI tools to target its specific needs while maintaining its privacy standards.
  • Predictive Modeling: Predictive AI tools can be used to analyze past data and then apply that analysis to generate predictions for future scenarios that can inform decision-making in order to improve outcomes. 

In addition to describing ways of integrating AI technology into existing operations to perform tasks, business models can also cover how to provide AI services. For example, an organization can develop new AI-native products or deliver AI services to new markets. Emerging AI-focused services in business models include: 

  • AI-as-a-Service (AIaaS): Provides AI resources using a subscription model in which customers access the AI while the provider hosts its infrastructure
  • Custom AI Integrations: Creates AI integrations tailored to each customer’s needs, such as data analytics, customer support, or automation
  • AI Training: Trains AI models to analyze and label data in large datasets, allowing organizations to improve their custom software or AI tools 
  • AI Platform-as-a-Service (PaaS): Offers environments to test and develop AI tools, which can include tools to develop AI 

Established organizations can benefit from regularly updating their business models to capture the value that AI can add to their operations, customer relations, and market standing. 

New ventures can formulate business models that meet the growing demand for AI-customized services or incorporate AI into their operations to gain a competitive advantage. 

Resources on AI Use Cases for Business

How do AI-driven business models work in practice? Across industries, organizational leaders continue to experiment with ways to use artificial intelligence to increase efficiency and maximize profits. These resources showcase AI use cases for many different types of organizations in multiple sectors. 

Benefits of AI-Driven Business Models

What are the benefits of centering AI in business models? AI can be used to automate business processes, optimize workflows, and identify trends in large datasets. The technology also offers several benefits specifically for customer-facing businesses.

For example, AI can solve business problems in the following areas:

  • Business Process Optimization: AI can be used to analyze business processes across an organization, optimize resource allocation, and flag bottlenecks in workflows. Improved monitoring can improve efficiency and capture more value. 
  • Customer Experience Personalization: Using AI to customize the user experience can deliver value to customers. Examples include streaming services that recommend videos based on prior views and social media organizations that use AI-driven algorithms to serve relevant content to users. 
  • Predictive Data Analytics: The forecasting power of predictive AI tools can be deployed to detect fraudulent transactions, plan for equipment maintenance needs, and mitigate risk. The predictive applications of AI allow organizations to leverage big data to optimize their operations. 
  • Customer Support Delivery: AI technology can be used to provide accurate support and real-time troubleshooting to customers, which can help companies gain customers’ loyalty and improve their brand identity. AI also can be used to help improve response time and scale customer support to match demand. 
  • Autonomous Supply Chain: AI agents can be employed to forecast demand, identify potential disruptions, and adjust operations to improve the resilience of organizations’ supply chains. By analyzing data in real time, AI agents are able to adapt to changes quickly and improve efficiency. 

Organizations across industries rely on professionals with AI expertise to maximize the potential benefits of AI. 

In roles such as AI analyst, AI product manager, and business intelligence analyst, professionals can play a key role in integrating AI into operations. And in roles such as AI strategy manager and chief AI officer, they can lead AI-driven organizational change. 

The organizations currently benefiting the most from AI are following the best practices in the field. For instance, AI high performers are more likely to have explicit processes for human validation of AI outputs, leadership that understands AI’s value, and a clearly defined AI road map. 

Interviews With AI Thought Leaders

Professionals can benefit from expanding their understanding of the evolving impacts of AI on business operations. In the following interviews, business and technology leaders share their insights into AI strategies and business models. 

AI in Business Strategy

Leveraging the power of AI in business requires more than an understanding of AI’s opportunities and limitations. It also requires a strategic approach to integrating AI into an organization’s business model. 

As AI continues to evolve, professionals will need to continue to monitor the development of new AI-driven tools and techniques. They can also benefit from a mindset that embraces experimentation and prioritizes ongoing learning.

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