You keep hearing overhyped terms like Big Data and Machine Learning, but what does it really mean for the way your organisation might work?
What you need to understand is that machine intelligence is completely different from traditional software. It's the dawn of an entirely new set of capabilities, it's not something you just plug in, and deploying it meaningfully is going to require more than a couple of board meetings.
Unlike software as a service, deploying meaningful machine intelligence will be tied to deep, deep process changes or a reset of your entire organisation.
This might be the biggest challenge of this century for many organisations, and those that adopt with intelligence and experiment quickly will be those that emerge from the dust and gain ubiquity in the next decade. Partners who understand this will be imperative to enterprise and corporate success.
Companies are struggling to figure out what to do, as many boardrooms did on “what to do about the Internet” in 1997. Why is this so difficult for companies to wrap their heads around? Machine intelligence is different from traditional software. Unlike with big data, where you could buy a new capability, machine intelligence depends on deeper organizational and process changes. Companies need to decide whether they will trust machine intelligence analysis for one-off decisions or if they will embed often-inscrutable machine intelligence models in core processes. Teams need to figure out how to test newfound capabilities, and applications need to change so they offer more than a system of record; they also need to coach employees and learn from the data they enter.