#AI@Work: AI & Managing Risk
Using AI requires companies to become experts at risk management, flexibility and change. Most companies are not good at this. In other words, agile. Many companies have seen AI projects fail. They fail not because the technologies are inferior. They fail because the humans who use the technologies are not ready to accept new ways of doing things. When humans don’t understand and don’t trust technologies the results can be less than ideal. Change is not easy and not something that humans embrace. When business processes change, every aspect should be examined. There are very few cases where robots are totally replacing humans. More commonly, AI is enhancing the business process. Hopefully, AI is making it more efficient, effective and flexible. In most cases humans are not eliminated but rather supported. Any kind of change, though, takes education and support.
AI also shines a spotlight on areas of neglect within a company. The internal systems that lack are not connected. They also have a large amount of redundancy. AI is all about the data and the data must have integrity. Customer data is in one system. The financial data in another system. The HR data in another and on and on…. These systems have never been integrated. AI requires data early and lots of it. Many companies find it too difficult and costly to mine the data. Often the data comes from multiple systems. Plus, companies must still protect privacy, security and make sure the data is reliable.
AI and Risk There is no question that installed AI has a set of risk factors all its own. Fears of disruption, threats of infiltration and security risks cloud the safety and dependability of AI systems. System failures can add to the complexity of AI operations. Data can be lost. Deep learning uses data in image and speech recognition. The data involved and how it is used is really not understood by most humans.
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