Enterprise AI Advantage: Illusion of Progress
Companies are embedding AI into various workflows, but most systems share a common pattern: a custom application layer, proprietary workflow, sensitive data, and rented intelligence. This distinction matters as AI becomes the operating layer for various industries. Most enterprise leaders think they're building AI advantage, but they're actually leasing it.
Key points
- Most enterprise companies are embedding AI into customer workflows and operations, but the intelligence behind these systems is often rented from external model providers.
- The application layer is custom, the workflow is proprietary, the data is sensitive, and the intelligence is rented in most AI systems.
- AI is becoming the operating layer for customer support, finance, healthcare, legal workflows, sales operations, supply chains, and product experiences.
- Enterprise leaders think they're building an AI advantage, but they're actually leveraging external models and services.
- The distinction between building and leasing AI advantage matters as companies rely on external intelligence for critical operations.
The concept of AI advantage has become a buzzword in the enterprise world. Companies are adopting AI at an unprecedented rate, embedding it into various workflows and operations. However, a closer look reveals that most of these systems share a common architectural pattern. The application layer is custom, the workflow is proprietary, the data is sensitive, and the intelligence is rented from external model providers.
This distinction matters as AI becomes the operating layer for various industries. Companies are relying on external models and services to power their critical operations, from customer support to finance and healthcare. The illusion of progress is that these systems appear to be transforming the way businesses operate. However, under the surface, most of these systems are built on rented intelligence.
The implications of this trend are significant. If the intelligence behind these systems is not owned by the enterprise, the advantage is not truly theirs either. This raises questions about the long-term sustainability of these systems and the potential risks associated with relying on external models. As AI continues to evolve, companies must reevaluate their approach to building and leveraging AI advantage.
Sources
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