Machine learning has become a crucial business driver not just for some of the most respected companies in the world, like Google, Salesforce, Microsoft, Amazon, but also more broadly across the business landscape. In this interview, Jeff Erhardt, CEO of Wise.io, shares his insight on the future of machine learning.
What do you see as the biggest trend around machine learning this year?
Quite simply, machine learning is finally making its way into the masses as a real business tool and a viable approach to data that businesses look to for competitive advantage. Machine learning is now understood, accepted, and adopted by a mainstream audience—and has become a reliable and measurable driver for success.
Why will 2016 be the year machine learning is finally seeing traction? Why now?
There are three major reasons machine learning has been gaining traction and is posed for great growth over the next year. First, the proliferation of data being collected is so great that the majority of medium-to-large-sized companies are struggling to make sense of the data and take advantage of its real strategic value. Such value includes optimizing business processes and improving the customer experience. Secondly, the computing power to process data—previously reserved for the Googles of the world—has been democratized and is now available to mainstream business professionals. Lastly, media and businesses are really taking notice of the technology and fueling further attention, discussion and growth.
How have communication trends shaped machine learning applications?
People prefer to communicate in short bursts. Customers comment briefly on social media and tweet, and these direct blasts of opinion regarding a brand are where companies can learn the most about their customers, and cater to them. Short-form communication is readily understood and synthesized by machine learning applications. Therefore, customer support teams can use machine learning to measure social signals and understand customers’ needs before they do, anticipating the climate of customer experience. Customers are beginning to expect such technology and behavior from companies and choosing brands that can respond proactively.
How does machine learning impact customer support?
Not surprisingly, there has been a lot of apprehension surrounding machine learning. First, that it would replace people and make customer engagement a cold experience. Also, that companies integrating machine learning into their processes would lose control. Quite the opposite is happening. For example, in customer support, machine learning is allowing support reps to apply their sense of empathy and other personal attributes to conversations with clients instead of engaging only in repetitive work. Customers feel it. They are getting better answers, faster, and having a more enjoyable support experience overall. As for control, companies understand now that machine learning is giving them more power over their processes and customer experiences.
What do you see as the major barriers to adoption of machine learning in businesses?
Interestingly, I no longer see technology as the main barrier -- thanks to the accessibility of powerful compute platforms, the data deluge, and algorithmic innovations. Instead, the adoption rate of machine learning is going to be determined more by organizational and cultural forces. Business units must be prepared to educate and train non-technical staff to use the machine learning solutions effectively and efficiently. Does a company have an appetite to build and maintain a first-class data science and engineering team that is capable of putting machine learning into production and maintaining such systems? Relatedly, since not all machine learning solutions need to be grown in-house, management needs to be prepared to make a well informed build-buy decision about such (relatively) new technologies. And, how will organizations measure the effectiveness and ROI of machine learning solutions?
If you are interested in leveraging machine learning to take your business to the next level in 2016, contact the team at Wise.io to begin a conversation about implementing their predictive applications to solve your biggest business challenges.