To stay competitive, organizations must continually embrace new tools that enable them to develop innovative products, solutions, and ways of working. Artificial intelligence (AI) has become a powerful catalyst for this shift, reshaping how companies operate and create value.
If your business is early in its journey to becoming AI-first, several innovation frameworks can guide your strategy. Three lenses—architectural innovation, disruptive innovation, and collision theory—offer insight into how AI can transform industries and why some firms thrive while others fall behind.
Innovation Starts with Creative Destruction
Before exploring the innovation types, it’s important to understand creative destruction, an economic concept introduced by economist Joseph Schumpeter that’s discussed in the Harvard Business School Online course AI Essentials for Business. Creative destruction describes how new technologies replace incumbent products, services, and business models—ultimately driving progress.
“It’s an essential fact about capitalism,” says HBS Professor Karim Lakhani in AI Essentials for Business, which he co-teaches alongside HBS Professor Marco Iansiti. “Lots of established firms eventually die because of these gales of creative destruction that come in from entrepreneurial startups and get the ball rolling.”
While difficult to measure precisely, Lakhani notes that some estimates suggest that upward of 50 percent of productivity growth can be attributed to creative destruction. Indicators include the rising number of new organizations and job creation in emerging industries. These same indicators are visible today as AI-native organizations take shape.
“Hello, age of AI, right?” Lakhani notes in AI Essentials for Business. “New organizations are being formed. New jobs are being created. New industries are being created. And established, incumbent firms are particularly at risk when it comes to creative destruction.”
Competence-Enhancing vs. Competence-Destroying Innovation
In AI Essentials for Business, Lakhani explains that the innovations contributing to creative destruction fall into two categories:
- Competence-enhancing innovation
- Competence-destroying innovation
Competence-Enhancing Innovation
Competence-enhancing innovations build on existing products or systems, enabling incumbents to adapt.
For example, electric vehicles reimagine the traditional automobile, but rely on many existing competencies. While Tesla pioneered the market, incumbents like Ford, General Motors, and Volkswagen introduced electric models of their own, avoiding total disruption.
Competence-Destroying Innovation
Competence-destroying innovations introduce new product classes, requiring updated skills and knowledge.
The automobile was a competence-destroying innovation for horse-and-buggy manufacturers, whose deep industry experience didn’t translate to the new product category.
As you incorporate AI into your organization, consider whether these opportunities will be competence-enhancing or competence-destroying—an important distinction for building an effective AI strategy. You’ll want to plan for the implications this may have for your business and the market as a whole.
Architectural Innovation
The first innovation type to consider is architectural innovation, a framework developed by HBS professors Kim Clark and Rebecca Henderson, the latter of whom teaches the online course Sustainable Business Strategy. It helps explain why some incumbents struggle to respond to innovations that transform markets.
Organizations hold two kinds of knowledge:
- Component knowledge: Understanding a product’s individual elements
- Architectural knowledge: Understanding how those elements interact within the whole system
Architectural innovation, as discussed in AI Essentials for Business, occurs when a product’s underlying components remain the same but are combined in a new way that overturns existing architectural knowledge. Rather, organizations understand the pieces but not the new system they create together. A classic example is the motorcycle, which incorporates many of the same components found in a car, but arranges them differently to serve a new purpose.
“Architectural innovations are really hard,” Iansiti says in AI Essentials for Business. “The components interact with each other in a different way. And what Rebecca Henderson and Kim Clark figured out is that it’s just easy to fail, even if the architectural innovation doesn’t look like it from a third party.”
Disruptive Innovation
Disruptive innovation is a process coined by HBS Professor Clayton Christensen, who teaches the online course Disruptive Strategy. It takes place when a smaller entrant challenges and ultimately overtakes the incumbent by:
- Competing initially at the low end of the market, or
- Creating a new market by serving previously overlooked customers
As disruptors refine their offerings, they move upmarket and capture business from incumbent customers.
In AI Essentials for Business, Lakhani and Iansiti highlight Tesla as an example. Porsche and other automakers improved performance incrementally, while Tesla introduced a simple electric alternative that gradually improved until it could directly compete with luxury brands.
“Tesla starts grabbing away the Porsche customers one at a time,” Iansiti explains in AI Essentials for Business, eventually forcing Porsche to invest in its own electric vehicles.
AI-driven disruptors follow similar patterns. Many AI-based startups begin by serving niche or low-end markets before advancing to challenge established leaders—especially in industries undergoing rapid digital transformation.
Collision Theory
Under the collision theory, two types of companies operate in fundamentally different ways:
- Traditional firms: Built around legacy structure and process
- Challenger firms: Organized around new technologies, such as digital platforms or AI systems
As challengers demonstrate more efficient or effective models, they capture market share until they collide with incumbents, often accelerating digital and AI-driven transformation.
“What we see with collisions is fundamentally two different kinds of companies fighting with each other,” Iansiti explains in AI Essentials for Business. “You have a traditional firm with a certain organizational structure, and a certain kind of culture and behavioral mode that has been set for a long time, that’s serving customers in a certain way. And you have a new entrant—a new kind of organization that’s fundamentally built in a different way.”
Digital-first firms collided with traditional businesses during the rise of the internet. Lakhani and Iansiti argue that similar collisions are unfolding today as AI-first organizations reshape expectations around efficiency, scalability, and customer experience. Understanding collision theory can help leaders evaluate how AI innovations may accelerate structural change.
Multiple Modes of Innovation for the AI Age
Although Lakhani and Iansiti state in AI Essentials for Business that collision theory is the most relevant framework for organizations aiming to become AI-first, each of the three—architectural innovation, disruptive innovation, and collision theory—offer value as you consider the role AI can play in your organization.
If you’re ready to deepen your understanding of AI innovations and build a practical AI strategy for your organization, explore the online course AI Essentials for Business. You’ll learn through real-world cases and gain insight from a global network of learners.
Are you ready to apply these innovation frameworks and become an AI-first organization? Explore HBS Online’s AI Essentials for Business course, or dive into the Digital Transformation and AI Learning Track, which allows you to complete three courses in the subject area to earn an advanced Certificate of Specialization. Not sure where to begin? Download our free flowchart to find the right fit.
