The age of artificial intelligence (AI) is here. Despite being around since the early 50s, AI is finally maturing from an interesting piece of technology to one that is delivering significant, tangible benefits in numerous market segments and across many different businesses. From self-driving cars to website chatbots and intelligent robots in factories, AI is here to stay.
Yet, things have been more slow-moving in the enterprise back-office. We are seeing AI introduced in areas such as invoice processing and loan approval, but only as an optional extra to enhance parts of the existing process. To achieve the same levels of benefit as other AI-enabled areas, we need to think bigger and start solving real business problems, not just making existing processes go faster. But to do that, we need to first look at what AI is not.
The AI Silver Bullet
Many people see AI as a silver bullet — a single shot to solve a single, big problem. But the reality is that businesses do not have one single problem they want to solve; they typically have a series of big issues, each of which can be broken down into a further series of smaller challenges. Early AI deployments failed to deal with this nuance. AI software was complex to use, and each AI model took considerable time and effort to build. With so much effort required to solve one problem, what chance did the business have of solving more?
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/03/ai-apps-and-platforms-get-real/?sh=4e8accd6c519
Yet, things have been more slow-moving in the enterprise back-office. We are seeing AI introduced in areas such as invoice processing and loan approval, but only as an optional extra to enhance parts of the existing process. To achieve the same levels of benefit as other AI-enabled areas, we need to think bigger and start solving real business problems, not just making existing processes go faster. But to do that, we need to first look at what AI is not.
The AI Silver Bullet
Many people see AI as a silver bullet — a single shot to solve a single, big problem. But the reality is that businesses do not have one single problem they want to solve; they typically have a series of big issues, each of which can be broken down into a further series of smaller challenges. Early AI deployments failed to deal with this nuance. AI software was complex to use, and each AI model took considerable time and effort to build. With so much effort required to solve one problem, what chance did the business have of solving more?
Continue reading: https://www.forbes.com/sites/forbestechcouncil/2022/01/03/ai-apps-and-platforms-get-real/?sh=4e8accd6c519
