Link: Almost half of CIOs plan to deploy artificial intelligence enterprise solutions | ZDNet

“According to the CIO agenda survey, four percent of CIOs have already implemented AI in some fashion, but a further 46 percent have plans to follow suit. In addition, 20 percent of CIOs worldwide have pilot AI programs in the pipeline for implementation in the near future.” But, wait: “However, not every AI pilot will be a success. Gartner believes that up to 85 percent of projects will not deliver due to data bias, poor team management, or unsuitable algorithms.”
Original source: Almost half of CIOs plan to deploy artificial intelligence enterprise solutions | ZDNet

Link: Gartner Survey Shows Organizations Are Slow to Advance in Data and Analytics

Still waiting for BI👉analytics👉big data👉AI/ML to hit the big time: “The global survey asked respondents to rate their orgs according to Gartner’s 5 levels of maturity for data & analytics…. 60% of respondents…rated themselves in the lowest 3 levels.”
Original source: Gartner Survey Shows Organizations Are Slow to Advance in Data and Analytics

Link: AI Begins to Infiltrate the Enterprise

It could be a better list, sourced from companies, but good nonetheless: “Some of that confusion may be because there are so many potential use cases for AI. Experts pointed to help desk, customer support, recommendation engines, fraud detection, chatbots, image recognition, language processing and market segmentation as some of the possible applications of the technology. Andrews pointed out that AI could even be helpful at tasks like improving graduation rates at universities or reducing recidivism at prisons.”
Original source: AI Begins to Infiltrate the Enterprise

Link: Google’s AutoML lets you train custom machine learning models without having to code

“The basic idea here, Google says, is to allow virtually anybody to bring their images, upload them (and import their tags or create them in the app) and then have Google’s systems automatically create a customer machine learning model for them. The company says that Disney, for example, has used this system to make the search feature in its online store more robust because it can now find all the products that feature a likeness of Lightning McQueen and not just those where your favorite talking race car was tagged in the text description.”
Original source: Google’s AutoML lets you train custom machine learning models without having to code

AI market sizing: $39bn in growth in less than 3 years?!

The market — defined as A.I.-related hardware, software and services — will surge from $8 billion this year to $47 billion by 2020, predicts IDC, a research firm.

Uh…

Also, some coverage of Watson business models, including customized cocktail drugs, which I hear is a scary big business in the horizon.

And, there’s some IBM AI spreadsheeting you can fiddle around with:

Market-share:

IBM may have a chance to join that group. By 2020, IDC predicts, 60 percent of the A.I. applications will run on the platform of four companies: Amazon, Google, Microsoft and IBM.

Revenue:

UBS estimates that Watson may generate $500 million in revenue this year and could grow rapidly in the years ahead, possibly hitting nearly $6 billion by 2020 and almost $17 billion by 2022.

Having lived through The Great Cloud Forecasting era around the turn of the decade, my advice is: take all this with care, but enjoy the razzle-dazzle!

Source: IBM Is Counting on Its Bet on Watson, and Paying Big Money for It

IBM Watson drove <$100m revenue in 2013

You know, $100m actually seems pretty good for something so obscure and weird. 

IBM Chief Executive Virginia “Ginni” Rometty has told executives she hopes Watson will generate $10 billion in annual revenue within 10 years, according to an October 2013 conference-call transcript reviewed by The Wall Street Journal. She set that target after the executive in charge of Watson said its business plan would bring in $1 billion of revenue a year by 2018. That would make Watson the fastest IBM business unit to reach the $1 billion milestone. But Watson had total revenue of less than $100 million as of late October, according to the transcript. One of its first big projects, with the University of Texas M.D. Anderson Cancer Center, was “in a ditch” in early 2013, said Manoj Saxena, the executive overseeing Watson.

IBM’s revenue targets seem pretty high. It’d be handy to compare them against iOS-world (here’s the software portion from Horace), which is considered an insanely high growth technology that came from nowhere. Once Her posts enough box-office numbers, that’d be a good, humorous comp too (the AI movie is up to $3.7m after being released just under a month ago).

IBM Watson drove <$100m revenue in 2013