AI for the Enterprise

Journey to AI – Three lessons we learned about effective implementation

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IBM has been on the AI journey for a long time, but the path has not always been smooth. My experience in the consulting business has taught me that successful practitioners need to be flexible and quick to make course corrections. We at IBM have learned along our AI journey, and here are three lessons that come to mind from my own interaction with clients and business colleagues.

1. You fail quickly, and learn fast with AI

Remember the adage: garbage in, garbage out. We’ve acknowledged that the results of data analysis are sometimes misleading or even inaccurate. It could result from human error, or personal or institutional biases. Or maybe we’re not asking the right questions. Today we’re building tools that quickly recognize anomalies in the data and even apply a bias rating to outcomes that allow us to make course corrections.

Exploration geologists know all about course corrections. They analyze data from drill logs, geological shapes, connected devices and maps to plan their next exploration drill. At Goldcorp they are using AI to analyze all this data, and try to identify human error and bias quickly. Their AI platform identifies anomalies and allows geologists to focus on good data as they search for new ore deposits.

2. AI does not replace us; it makes us better

The second lesson is that artificial intelligence is not designed to replace the human mind, but to augment our intelligence and amplify our reach. In the early stages, AI systems were not that smart. Training was a slow, arduous process that required a lot of human intervention. Thankfully, that has led to systems that are now much more robust.

Today, AI platforms are being used in all industries to makes us smarter. A great example is found in healthcare.

Ten million people around the world are living with Parkinson’s disease. The drug treatment hasn’t changed significantly in 50 years. One of our employees living with Parkinson’s thought there must be a better way to advance research. Our AI platform was put to work digesting 28 million medical reports and analyzing 3,800 possible drugs. Sixteen potential drug treatments emerged and the Ontario Brain Institute has funded the initial study with the goal to have more diverse and better treatments for people with Parkinson’s.

AI is not replacing doctors and researchers, but making them smarter.

3. Beware of data ownership in the world of AI

Data ownership has been a hot news item lately. Some large companies have been under fire for misusing data that has been entrusted to them. We believe that you should not be required to relinquish rights to your data in order to have the benefits of an AI platform. In fact, IBM neither owns nor stores any of the data touched by Watson solutions and services. We believe the data and resulting insights belong to your organization and its clients.

A recent IBM survey revealed that 78 percent of respondents say a company’s ability to keep their data private is “extremely important” to them, but only 20 percent “completely trust” organizations they interact with to maintain the privacy of their data.

Your data matters to you — whether it’s your own personal medical records, or the findings from your company’s drug trials or geological surveys.

At the enterprise level, your data is your competitive advantage. If your technology partner is sharing your data with others you may be hurting your business and your clients. You should always retain ownership of your data, and know how it is being used. That is a principle everyone in our industry must adopt.

We’re still in the early stages of our AI journey, and have much to learn as the technology matures. The potential in AI to improve our lives and our businesses is potentially limitless, but as with any new technology, we must approach it responsibly and with a willingness to learn and adapt.

With Watson, harness the power of AI to turn data into new ways of doing business.

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