This is the third installment, and likely the one that’s more ambitious and controversial.
I wrote earlier this year that I was changing the model for my work and that I was going to be focused on five topics, with formal research agendas. I shared with you first the model for Customer Service Usage and Adoption, then the one for Data Usage in the Enterprise, and I am somewhat hesitant to offer this third installment: Artificial Intelligence in the Enterprise.
Back in the early 1980’s, I got my hands on the (then) newly-published “Encyclopedia of Artificial Intelligence”. It was three volumes filled with (almost) everything we had learned about AI until then – almost 2,500 pages (and has been updated many times since – I think it is in the fourth edition). I read, devoured, the contents and then set out to find out more. I lived in Argentina and I was in HS – not easy to find computers or programs that were made available to kids, but managed to find some things: compiler design classes (YACC), programming classes (Javelin, a 4GL expert-systems language), and some other conferences and seminars. Later in college, I took classes on building neural networks (Pascal and C, tried but not enough you can do in a 10-week class) and around symbolic systems. Did other things along the lines of linguistics (I know, the irony – the foreigner working on linguistics – right? most of the top experts were foreigners at that time), psychology, cognition, learning, decision making, expert systems, and analytics along the way. All in all, have been around this world for some time.
The hype surrounding AI these days is deep – even deeper than it was for Big Data (hear much about that these days? yeah, not as much… not as much). The “market” for AI is nowhere even beginning to set (like the one for Big Data – but that is another research topic) and there is a ton of potential – most of it latent for the past 40+ years while waiting for more power and faster speeds from computers (similar story to the world of Data Usage in the Enterprise). I want to bring a lot of that potential to the surface and hopefully see it realized.
I am covering AI as a starting market not because the concept or technology is new, rather because I see it as a starting point to where the enterprise can enter and get value out of it. Until now vendors used decision systems, analytics, NLP and linguistics and other technologies as part of what they did and never thought of using AI (there was a time during the 1990s when we used “Fuzzy Logic” ‘member?) for their pitches – but now they all do.
What is an enterprise to do? How do you distinguish between ML offerings from an IaaS provider and a chatbot from a .ai vendor? This is where I will try to show some structure. The notes in my research agenda, and the deadlines – which are all subject to change and to be added to as the year goes by – are:
- February 21 – Artificial Intelligence in the Enterprise Market
- March 28 – Trends and Adoption for AI
- May 9 – Enterprise Use Cases
- June 13 – AI Pulse of the Market
- September 19 – Interesting Examples, Case Studies in AI
In addition, I will be conducting a qualitative study on AI (talking to interesting people in the field, as well as to practitioners, to get a better perspective of what’s going on; will publish findings on June 26.
How can you help (or how can I help you)?
If you have an interesting case study, if you are willing to be interviewed for a “lessons learned” interview, if you have some wisdom or insight you’d like to contribute, if you would like to discuss the market — or if you are looking to sponsor the research (wink-wink) simply contact me. You can also leave a comment below if you prefer.
(part four of this five-part research agenda publishing is coming soon and will display the same information for the topic of Platforms and Ecosystems)
disclaimer: no disclaimers at this time, sorry – writing templates and prepping to cover 5 research topics has taken all the humor away… sigh (it’s so bad, i am even reusing disclaimers) — but i have to say .ai and IaaS are not my clients, they are mentioned as distinguishing factors in conversation. Any coincidence with an actual vendor, totally and purely koinki-dinki.
(Cross-posted @ thinkJar)