Just when you have your data collection and analysis systems in place, technology changes mean that your company needs new, updated systems. This is a problem for many companies — but it can also be an opportunity. Organizations that work with data from old and new equipment can learn more about the shortcomings that modern techniques have in this context and can gain advantage in developing tools that no one else has.

A global survey by the McKinsey Global Institute finds that AI is delivering real value to companies that use it across operations. C-level executives report that when they adopt AI at scale — meaning they deploy AI across technology groups, use AI in the most core parts of their value chains, and have the full support of their executive leadership — they are finding not just cost-cutting opportunities, but new potential for business growth, too.

Detailed and data-rich insights won’t help your company if your employees don’t know where to find them — but that’s a problem AI can solve. Machine learning can enable faster organizational learning by helping each employee quickly understand what others in the organization understand — forming a knowledge distribution network.

Some people suggest that the concept of “big data” is nearing the end of its fifteen minutes of fame. They couldn’t be more wrong — because big data isn’t just about managing social media, unstructured data or massive data sets. It is an approach to data and analytics that finds new ways of looking at information — and it’s here to stay.

The global financial crisis that occurred in 2008 can be viewed as a systems accident that was fueled, in part, by innovations in the financial sector.