Even as the press is filled with stories of artificial intelligence and cognitive technologies, the market isn’t entirely sure what to make of these advances. As with any emerging technology, the question arises of whether it’s all hype or if it’s truly transformative.
In a recent post, we looked at the reasons why so many cognitive computing initiatives fail. And that leads to the next obvious question, “So, how do you avoid failure and plan for success?”
At Attivio, we think of cognitive computing as a set of building blocks with AI capabilities such as machine learning, NLP, text analytics, and so on. Cognitive search uses many of the same building blocks, which makes it a good place to start any cognitive computing project.
At the 2107 Sohn Conference, Social Capital CEO and founder Chamath Palihapitiya declared, “Watson is a joke, just to be completely honest.” Of course, this quote got a lot of play. But another quote from the same interview is actually more revealing about why so many cognitive computing initiatives eventually circle the drain — and why they take so many resources with them. Palihapitiya noted, "I think what IBM is excellent at is using their sales and marketing infrastructure to convince people who have asymmetrically less knowledge to pay for something."
In terms of cognitive search, IBM has the lion's share of failures at this point, so it's easy to throw stones at them. And, since they approach cognitive search as a services engagement, the reasons behind the failures are instructive.
My last post on cognitive computing was a backgrounder, and it stated the importance of search to any cognitive computing initiative. So, how does cognitive computing powered by search lead to digital transformation? In fact, just what is digital transformation?
It is, no doubt, an overused phrase. But it captures something very real that’s occurring not only in business but across society at large. An article in i-SCOOP frames digital transformation as the ways in which a mix of digital technologies accelerate change in business and organizational activities, processes, competencies and models.
When IBM Watson burst on the scene a few years ago by famously winning Jeopardy! people swooned. Here was a machine that seemed to live up to the promise of a science fiction future. IBM purported to show us all an artificial intelligence (AI) that could understand human language, sift through massive amounts of data, and provide answers to questions.
From a marketing standpoint this is a gold standard for enterprise software. Companies quickly signed on to the promise, looking to Watson for answers for everything from insights in their CRM data to finding a cure for disease.
When you think about customer support, you tend to think about cost savings for the company. But how often do you think about customer experience?
For too many companies, a focus on customer experience ends when the customer is won. The reality is, it’s only the beginning. If the experience you deliver your customers is poor, they will leave you. And it’s easier than ever for an unhappy customer to move to the next company.
If there’s one area of the company where many could improve the customer experience, it’s customer support. So what are the 3 approaches to improving customer support?
What exactly is cognitive computing? Well, if you ask 10 academics or scientists, you’re likely to get 10 different answers. Look it up on Wikipedia. You’ll see that in the academic and scientific community, there is no agreed upon definition. It’s just marketing jargon. Ouch.
On the commercial side though, we may not have a precise definition for cognitive computing, but we’re very aware of its potential to help our businesses.
Cognitive computing and AI have increased the tools in our toolbox. Machine learning, deep learning, neural nets, natural language processing. These technologies are the foundation on which companies are building new capabilities that affect top-line revenue and bottom-line profitability.