Whenever a new technology appears, almost everyone claims it will be “transformational.” Usually, that claim is too vague to be useful.
A company may adopt a technology, launch a feature, or improve a few internal processes, all of that without materially changing its business.
A more useful question is:
What fundamental constraint does the technology remove?
I use this question to classify the impact of new technologies on companies, products, and business models.
The framework
A new technology can affect a business model in five distinct ways.
| Classification | What constraint the technology removes |
|---|---|
| No Material Impact | It removes no constraint that materially affects the business model |
| Existing Model Leverage | It removes a constraint that limited the performance of an already viable model |
| Economic Enablement | It removes a cost constraint that prevented a technically possible model from being viable |
| Technological Enablement | It removes a capability constraint that made the model technically infeasible |
| Model Destruction | It removes a constraint that an existing model depended on to create or capture value |
1 - No Material Impact
The technology removes no fundamental constraint that materially affects the business model’s performance, differentiation, or viability.
The company may still use the technology to automate internal tasks, improve marketing output, or reduce minor operating costs.
Consider a restaurant using an LLM to draft job descriptions and marketing copy. The tool may be useful, but the restaurant still depends on locations, food, labor, customer traffic, and operational execution.
The technology improves activities around the business. It does not materially change the business itself.
2 - Existing Model Leverage
The business was already viable, and the technology removes a constraint that limited its scale, margins, productivity, differentiation, or monetization potential.
Rather than creating something fundamentally novel, the technology amplifies a model that already worked.
An established software product, for example, may use AI to automate part of an existing workflow. Customers complete the same job faster, the product becomes more valuable, and the company may charge more or serve more customers with the same resources.
The product can change substantially while the core business model remains intact.
This category is called leverage, not transformation, because the technology acts as a multiplier on an existing economic engine.
This can improve scale or market share, but the company still competes with established rivals in an existing market.
3 - Economic Enablement
The business was technically possible, but a cost or resource constraint prevented it from being economically viable at scale.
The economic equation changes through lower delivery costs, greater monetization potential, or both.
Personalized tutoring is a useful example.
One-to-one tutoring has always been possible, but it is expensive because each additional student requires additional human time. An AI-based tutor can provide continuous assistance at a much lower marginal cost.
The underlying capability and need are not new. What changes is the cost of delivering the service at scale.
The same pattern can apply to customer support, translation, legal assistance, research, design, and other services historically constrained by skilled labor.
If executed well, the company may expand its total addressable market by making the product or service available to a wider audience.
4 - Technological Enablement
The business was not practically possible because a required technical capability did not exist or was not sufficiently mature.
The technology creates a fundamentally new capability, rather than making an existing capability cheaper.
AI-based protein design is an example.
Companies such as EvolutionaryScale use generative models to reason across protein sequence, structure, and function, allowing scientists to design novel proteins with desired characteristics.
Traditional methods could analyze existing proteins or test variations through slow experimental cycles. They could not explore and generate entirely new biological designs with the same breadth and speed.
This goes beyond reducing research costs. It creates a new design capability around which new medicines, materials, and biological products may emerge.
Companies in this category may create entirely new markets and have the greatest disruptive potential.
5 - Model Destruction
The technology removes a constraint that an existing business model depended on to create or capture value, undermining its viability.
The technology may eliminate the scarcity, friction, or intermediary role that made the model viable.
Stock photography marketplaces, for example, depend on the scarcity of suitable images and on licensing access to large existing catalogs. Generative image models allow users to create customized images on demand, reducing the need to search, license, and adapt pre-existing content.
The companies do not necessarily disappear, but their existing business model loses viability unless they adapt.
Applying the framework
The classification depends on the unit of analysis. A company, product, business line, or internal process may fall into different categories.
A classification can also change over time. What begins as technological enablement may later become economic enablement or a standard source of leverage as the technology matures and becomes widely available.
The framework is not intended to predict winners. It is intended to force a more concrete question:
What wasn’t scalable, economically viable, or even possible before this technology existed?
The answer can help clarify how much a new technology may change a company’s business model and how strategically significant that shift could be.