AI News, AI and ML Adoption Survey Results from Applied Artificial Intelligence Conference 2017

AI and ML Adoption Survey Results from Applied Artificial Intelligence Conference 2017

Artificial intelligence and machine learning adoption among different industries represents a new chapter in digital transformation.

However, according our own research across industries, AI adoption in 2017 remains low with majority of major success stories coming only from the largest tech players in the industry (Google, Baidu, Apple, etc).

More specifically, we wanted to know what investors, founders and tech employees think about: In the charts and article below, we explore the survey responses from more than 100 professionals during the Applied Artificial Intelligence Conference in May 2017 in San Francisco organized by Silicon Valley-based venture capital firm BootstrapLabs.

(Note 1: Click here to see the actual survey that was filled out by attendees of this conference, otherwise, see the basic breakdown of the responses below.) (Note 2: A note about the survey itself: Our survey was handed out at the beginning of the event (before the presentations), and attendees were encouraged to fill one out before leaving.

Survey respondents to our AI perspective survey included 24 founders, 22 technical employees, and 55 “other” guests (including academics, non-technical employees, investors and executives).

The survey itself can found here via Google Sheets.) We surveyed just over 100 attendees from the conference (many of which were filled out on paper at the conference itself, others were filled out via online survey), and only a handful of the respondents neglected to record (a) who their business sells to, and (b) what their company sells.

As to what they sell, most of the respondents either sell services (~42%) or software (~34%), with a only a handful selling physical products, and another small group (~14.5%) selling both software and services.

In addition, marketing also ranks high among Software companies most probably owing to the fact that most of their sales processes are accomplished using digital channels and their marketing campaigns run on digital marketing elements (content marketing, PPC marketing, funnels, among others).

Commentary from Edgar Alan Rayo: When asked which area their company is most likely to invest in AI/ML in the next three years, both Services and Software firms weigh in more heavily on business intelligence and analytics, and customer service, followed by marketing and process automation.

The above question asked respondents to rank the following reasons that more companies aren’t adopting AI: Comments by Dan Faggella: The first three reasons had similar percent responses, but lack of talent barely eked out an edge over the other reasons.

while areas like marketing and customer service have many current use-cases (see one of our recent case studies about how Dole Foods improved in-store product sales by using artificial intelligence to rapidly test their ad creatives).

How Companies Are Already Using AI

Every few months it seems another study warns that a big slice of the workforce is about to lose their jobs because of artificial intelligence.

My own firm released a survey recently of 835 large companies (with an average revenue of $20 billion) that predicts a net job loss of between 4% and 7% in key business functions by the year 2020 due to AI.

For example, our survey, which asked managers of 13 functions, from sales and marketing to procurement and finance, to indicate whether their departments were using AI in 63 core areas, found AI was used most frequently in detecting and fending off computer security intrusions in the IT department.

In fact, although we saw examples of companies using AI in computer-to-computer transactions such as in recommendation engines that suggest what a customer should buy next or when conducting online securities trading and media buying, we saw that IT was one of the largest adopters of AI.

IT was using AI to resolve employees’ tech support problems, automate the work of putting new systems or enhancements into production, and make sure employees used technology from approved vendors.

For example, only 2% are using artificial intelligence to monitor internal legal compliance, and only 3% to detect procurement fraud (e.g., bribes and kickbacks).

When Joseph Sirosh joined Amazon.com in 2004, he began seeing the value of AI to reduce fraud, bad debt, and the number of customers who didn’t get their goods and suppliers who didn’t get their money.

(That was the year Bing became a profitable business for Microsoft.) Microsoft’s use of AI now extends far beyond that, including to its Azure cloud computing service, which puts the company’s AI tools in the hands of Azure customers.

AP found in 2013 a literally insatiable demand for quarterly earnings stories, but their staff of 65 business reporters could write only 6% of the earnings stories possible, given America’s 5,300 publicly held companies.

You might think companies will get the greatest returns on AI in business functions that touch customers every day (like marketing, sales, and service) or by embedding it in the products they sell to customers (e.g., the self-driving car, the self-cleaning barbeque grill, the self-replenishing refrigerator, etc.).

We asked survey participants to estimate their returns on AI in revenue and cost improvements, and then we compared the survey answers of the companies with the greatest improvements (call them “AI leaders”) to the answers of companies with the smallest improvements (“AI followers”).

The End of Customer Service as We Know It: Aspect Software’s Consumer Experience Index Survey Shows Self-Service, AI, Redefining How Consumers View Customer Service

The number of people who contacted customer service over the phone declined 10 percent in the last two years and contact with customer service overall has dropped seven percent over the same period according to the latest findings from the 2017 Aspect Consumer Experience Index.

Moreover, the ability for brands to be agile in adapting to evolving customer experience demands underscores the compelling nature of continuously-delivered features and functionality that a cloud-based platform like Aspect delivers.” One of the clear opportunities for brands is addressing customer experience effectiveness.

By developing fully native interaction management, workforce optimization and self-service capabilities within a single customer engagement center, we enable dynamic, conversational interactions and create a truly frictionless omni-channel customer experience.

Leveraging a worldwide cloud infrastructure and over 40 years of industry ingenuity, Aspect conveniently and easily connects questions to answers while helping enterprises keep service levels high and operational costs contained.

national study of 1,000 American consumers to investigate the attitudes, preferences and behaviors regarding customer touchpoints and engagement within the context of self-service, customized or personalized service and the hot topics of messaging, virtual assistants and chatbots.

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