It looks like the beginning of a new technology hype for artificial intelligence (AI). The media has started flooding the news with product announcements, acquisitions, and investments. The story is how AI is capturing the attention of tech firm and investor giants such as Google, Microsoft, IBM. Add to that the release of the movie ‘Her’, about a man falling for his virtual assistant modeled after Apple’s Siri (think they got the idea from Big Bang Theory when Raj falls in love with Siri), and you know we have begun the journey of geek-dom going mainstream and cool. The buzz words are great too: cognitive computing, deep learning, AI2.
For those who started their careers in AI and left in disillusionment (Andrew Ng confessed to this, yet jumped back in) or data scientists today, the consensus is often that artificial intelligence is just a new fancy marketing term for good old predictive analytics. They point to the reality of Apple’s Siri to listen and respond to requests as adequate but more often frustrating. Or, IBM Watson’s win on Jeopardy as data loading and brute force programming. Their perspective, real value is the pragmatic logic of the predictive analytics we have.
But, is this fair? No.
First, let’s set aside what you heard about financial puts and takes. Don’t try to decipher the geek speak of what new AI is compared to old AI. Let’s talk about what is on the horizon that will impact your business.
New AI breaks the current rule that machines must be better than humans: they must be smarter, faster analysts, or they manufacturing things better and cheaper.
Many of us have spent the past 10 years focusing on business intelligence solutions in order to help our businesses make better fact-based decisions. In fact, BI has been among CIOs’ top 10 priorities for more than a decade. These solutions have, for the most part, been successful — and we continue to improve our BI capabilities as the demand for fact-based decision-making goes deeper, wider, and further into the business.
This whole time, we’ve also been aware of the significant amount of unstructured data that resides within our business, and the fact that we struggle to use it to make better decisions. To begin to get value from this data, we have made our organizations more collaborative and implemented tools and platforms to support that collaboration — with varying degrees of success.
The fact remains that there’s a huge amount of unstructured information and data that we do not get value from. However, a growing number of solutions are beginning to mine elements of this data: product information, software code, legal case files, medical literature, messaging data, and other unstructured business data.
I’ve recently been working with TrustSphere, which is a messaging intelligence provider. TrustSphere has an interesting solution that mines your messaging data to get real insights and information from the mountains of emails and messages that bounce into, out of, and around your organization every day. This is an interesting concept, and TrustSphere has developed a number of use cases for its solution. I’ll be presenting at a webinar hosted by TrustSphere on February 25— feel free to register here.
During 2014, we’ll pass a key milestone: an installed base of 2 billion smartphones globally. Mobile is becoming not only the new digital hub but also the bridge to the physical world. That’s why mobile will affect more than just your digital operations — it will transform your entire business. 2014 will be the year that companies increase investments to transform their businesses, with mobile as a focal point.
Let’s highlight a few of the mobile trends that we predict for 2014:
Competitive advantage in mobile will shift from experience design to big data and analytics. Mobile is transformative but only if you can engage your consumers in their exact moment of need with the right services, content, or information. Not only do you need to understand their context in that moment but you also need insights gleaned from data over time to know how to best serve them in that moment.
Mobile contextual data will offer deep customer insights — beyond mobile. Mobile is a key driver of big data. Most advanced marketers will get that mobile’s value as a marketing tool will be measured by more than just the effectiveness of marketing to people on mobile websites or apps. They will start evaluating mobile’s impact on other channels.
IBM launched on January 9, 2014 its first business unit in 19 years to bring Watson, the machine that beat two Jeopardy champions in 2011, to the rest of us. IBM posits that Watson is the start of a third era in computing that started with manual tabulation, progressed to programmable, and now has become cognitive. Cognitive computing listens, learns, converses, and makes recommendations based on evidence.
IBM is placing big bets and big money, $1 billion, on transforming computer interaction from tabulation and programming to deep engagement. If they succeed, our interaction with technology will truly be personal through interactions and natural conversations that are suggestive, supportive, and as Terry Jones of Kayak explained, "makes you feel good" about the experience.
There are still hurdles for IBM and organizations, such as expense, complexity, information access, coping with ambiguity and context, the supervision of learning, and the implications of suggestions that are unrecognized today. To work, the ecosystem has to be open and communal. Investment is needed beyond the platform for applications and devices to deliver on Watson value. IBM's commitment and leadership are in place. The question is if IBM and its partners can scale Watson to be something more than a complex custom solution to become a truly transformative approach to businesses and our way of life.
Forrester believes that cognitive computing has the potential to address important problems that are unmet with today’s advanced analytics solutions. Though the road ahead is unmapped, IBM has now elevated its commitment to bring cognitive computing to life through this new business unit and the help of one third of its research organization, an ecosystem of partners, and pioneer companies willing to teach their private Watsons.