There has been a considerable amount of hype around Artificial Intelligence (AI) and Machine Learning (ML) technologies in the last five or so years. So much so that AI has become somewhat of a buzzword – full of ideas and promise, but something that is quite tricky to execute in practice.
At present, this means that the challenge we run into with AI and ML is a healthy dose of skepticism. For example, we’ve seen several large companies adopt these capabilities, often announcing they intend to revolutionize operations and output with such technologies but then failing to deliver. In turn, the ongoing evolution and adoption of these technologies is consequently knocked back. With so many potential applications for AI and ML it can be daunting to identify opportunities for technology adoption that can demonstrate real and quantifiable return on investment.
