Have you heard about or did you attend the AI World Conference and Expo in Boston, Massachusetts, from December 11 to 13, 2017? If you have not heard of AI World before, then you might be wondering what the conference is all about. The conference brochure states that “AI World is the industry’s largest independent event focused on the state of the practice of enterprise AI and machine learning. AI World is designed to help business and technology executives cut through the hype and learn how advanced intelligent technologies are being successfully deployed to build competitive advantage, drive new business opportunities, reduce costs and accelerate innovation efforts. This three-day conference and expo brought together the entire applied AI ecosystem, including innovative enterprises, industry thought leaders, startups, investors, developers, independent researchers and leading solution providers.”
We keep hearing more and more about artificial intelligence (AI) on commercials about everything from IBM’s Watson—and how it is going to solve a number of problems and issues—to personal assistants like Apple’s Siri and Amazon’s Alexa. Overall, though, the AI industry as a whole is still in its infancy. In all actuality, most companies are putting most of the money earmarked for AI into research, development, and experimentation. During research and development, companies are discovering they have a lack of specific user cases for the technology and a lack of the talent that will be needed to harness this technology. In my opinion, the most important finding concerns shortcomings in the overall user experience. All of these things together are limiting companies’ return on investment for the technology, and that contributes to the truly slow pace in the adoption of the technology.
Even given the slow adoption of the technology, venture capitalists’ and enterprises’ investments in AI are still on the rise; the general consensus is that artificial intelligence will be the future, and no one wants to be left out of this exciting new space.
Even though AI is still in its infancy, some areas are doing extremely well. Products in these areas can provide a solid return on investment and have the ability to be deployed into current production environments. Among these areas and products are robotics process automation (RPA) (think of this as software robots); chatbots like Alexa, Siri, and Cortana, to name a few; marketing automation for things like email, social media, and other online marketing activities; and of course, IT service automation. IT Service automation is something that I think most of you reading this post have had some kind of hand in developing to use in deployment to your environments.
IBM has been marketing the Watson AI platform for different use cases. I have heard that the adoption rate has been a little underwhelming, and that some of the biggest issues encountered have been the high cost and complexity associated with Watson. As a side note, did you know that the Watson computer system was originally developed to answer questions posed in natural language on the television game show Jeopardy? In 2011, the Watson computer system did just that and won the million-dollar prize. I would categorize Watson as a general-purpose AI platform. I believe we have advanced enough with the technology to move away from the general purpose to more narrowly focused AI-type solutions. I think Watson demonstrated generally what was possible and now has competition from new startups, open-source technology, and other cloud vendors that are focusing in on specific use cases. Although ROI is driving the narrowly focused solutions currently, the industry as a whole is continuing to pursue the general-purpose AI platform. In my humble opinion, Watson just may be a little ahead of its time.
In closing, I would to remind everyone that artificial intelligence is still in its infancy. It still has a way to go before it can be considered a mainstream technology. I think the current overmarketing of the technology may actually be doing more harm than good as its expectations are established. The technology itself is unable to live up to the hype today. This is going to change as time goes on, but I think we are still a little way out. I do think we are getting pretty close to the point where it will be very difficult to tell the difference between human and machine when it comes to interactions with companies and systems via chatbots and such in the new AI world.