The article also discusses the business model advantages of "Service-as-a-software," suggesting that it could lead to performance-based pricing models. It concludes by stating that the winners in Enterprise AI will be those who can capture entire workflows, deliver performance, and innovate their business models.
Key takeaways:
- AI adoption in the enterprise requires understanding how AI unbundles work and creates new opportunities to rebundle it elsewhere, the mis-steps that enterprises have made over the past decade in their quest for digital transformation, and the overall forces in an enterprise ecosystem that determine where power, inertia, and decisions sit and where they move with new technology coming in.
- Enterprise AI is moving towards a Service-as-a-Software model, where work is unbundled from workers and gets rebundled into software. This shift is driven by improvements in AI's ability to perform specific tasks and the increasing efficiency of workflows.
- Enterprise AI service providers can take over the entire workflow and sell the actual work, eliminating the onboarding concerns and issues entirely. This also delivers a strong business model advantage to a Service-as-a-Software company.
- With the rise of AI, there is a natural advantage to move towards a performance-based model, similar to what was seen with IoT and sensors in hardware. Instead of selling software, this involves selling actual outcomes and performance of work.