Most of the Artificial Intelligence (AI) projects that were supposed to help enterprises use data to improve customer service, reduce costs, and speed the core processes that provide competitive advantage have failed. The reasons are many, but the primary reason is that enterprise data was not properly prepared for AI.
Most of the Artificial Intelligence (AI) projects that were supposed to help enterprises use data to improve customer service, reduce costs, and speed the core processes that provide competitive advantage have failed. The reasons are many, but the primary reason is that enterprise data was not properly prepared for AI.
To reap the benefits of AI, enterprises need to create an ontology. However, without a consistent, thoughtful approach to developing, applying, and evolving an ontology, AI systems can only develop in a fragmented way and will lack the underpinning that would allow them to be smart enough to make an impact. Hence, beginning with identifying the data pain points, there are many other critical steps for developing an ontology such as generating solutions based on root causes, understanding use cases and setting the ontology’s organizing principles. Once an ontology and the system to maintain it are developed in a consistent and thoughtful way, the benefits multiply. It becomes an essential part of not only the solution to today’s information problem, but to the next problem that arises, and the next. Additionally, an ontology is a continuously evolving entity; therefore, an intentional process for changing the ontology is critical to keep it fresh and relevant. With every passing day, it is increasingly clear that AI is going to be solving many of the problems in the future. If AI is the future of business, then creating an ontology is an essential investment to realize the benefits of that future. It is a concept that, managed and applied appropriately, makes the difference between the promise of AI and delivering on that promise. Click here to read the original article published by the Harvard Business Review.
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