16, October 2018
Applying Artificial Intelligence in B2B and B2C - What's the Difference?
We discussed the difficulties large businesses may have in adopting AI in our previous article; despite this, last month we fleshed out the reasons why it’s still more difficult for small businesses to apply AI than the enterprise and how they might catch up to larger businesses in the future.
In this article, we draw a further distinction between B2B companies and B2C companies. It may be more difficult for B2B companies to adopt AI than B2C companies for a variety of reasons. We will focus on why that might be the case, laying out what we believe to be the starkest differences between B2B and B2C companies when it comes to applying and building AI products that could drive business value. These differences involve six key strata:
- Privacy and Aggregate Data Use
- Data Volume
- Interpretability and Transparency (The Black Box Problem)
- Risk and Experimentation
- Regulation and Legal Concerns
- The Culture of Data Science