AI adoption for the enterprise is on the rise. The advantages of AI are clear – it can automate repetitive tasks, it can provide predictive insights to businesses and it can improve customer experience.
Enterprise AI adoption is not always easy. There are many factors that can affect the success of an AI implementation. One of the most important factors is the decision maker. If they do not have a strong understanding of data science, then it will be difficult for them to understand how AI can help their company and make decisions on how to use it effectively. It’s one of the reasons that we are educating decision makers through the work we are doing at the Tesseract Academy.
The other factor that affects enterprise AI adoption is domain knowledge experts, usually at a management position. They are often the ones who know what data needs to be collected and what questions need to be asked in order for an AI system to work properly. If they are not on board with an AI implementation, then it will also have a negative effect on its success rate.
Sean Muller is providing his insights about what enterprises are doing well, what not, and what challenges AI adoption is facing. Some key points:
- Most enterprises find it difficult to adopt AI due to technical and cultural debt.
- AI adoption in big organisations often starts with champions in smaller departments, and not in a top-down fashion.
- Blockchain might follow a similar trajectory of enterprise adoption like AI.
- Quantum computing is going to be a game changer.
If you are interested to discuss about AI, data science, blockchain, product management, startups and related topics, then make sure to get in touch. I would be more than happy to hear from you!