The A.I. Spring has arrived in full force, thanks to a couple of key trends coalescing at the same time.
First, prominent industry incumbents have opened up their cognitive platforms. New startups claim to base their entire platforms on machine learning capabilities. Some startups have opted to leverage new artificial intelligence (A.I.) technologies from incumbent enterprises such as Google (Google Cloud Platform), IBM (Bluemix) and Amazon (AWS). A symbiosis has formed between enterprises that own clouds and the startups that build businesses on them. These startups have tied themselves to the success of these technologies. Fortunately, enterprises won’t pull the rug from underneath them. Large companies receive valuable data and business thanks to them. So, the same enterprises offer it as a key capability to companies wishing to build A.I. services.
Secondly, the proliferation of data has forced businesses to harness A.I. as a competitive advantage. Businesses must leverage machine intelligence to gain deeper customer insights beyond traditional analytics. There are many buzzwords thrown around in the big data field (data lake is my personal favorite). Even so, anything with a microprocessor collects valuable knowledge about user behaviors. Using A.I. to understand this data helps us process it all. The next evolution of computation will process information measuring larger than the number of people on Earth.
A.I. is not a silver bullet
A technology-first strategy is inferior to a user-centered strategy. There are many examples of products that were too far ahead of their time. These products showcase great features that demo well but are never widely adopted. To be an A.I.-first company, businesses must completely reassess the needs of their customers. Technology-first companies often get lost because they lose sight of the customer experience.
Read the source article at CIO.com.