According to a recent McKinsey survey, a majority of enterprises of all sizes are actively embracing AI. The areas seeing the biggest boost from AI adoption include service-operations optimization, AI-based enhancement of products and contact-center automation. When the general American populace is asked about AI, most have a positive view on AI's potential. But if you ask the more engineering-centric, IEEE Spectrum crowd, AI has a long, long way to go before they're willing to stand and applaud. IEEE Spectrum "members are involved with hard-to-penetrate vendor decision teams, usually in management capacity," according to the 2020 media kit.

A few days back when I wrote my second article on Medium, I gave it to my friends for review. One of them immediately told me that the title is very captive and that can pull the readers, I didn't take his words seriously and thought he was just encouraging me. I finally published it on a Saturday afternoon. It reached 70 views that day. The next morning when I woke up to check if I had done any better than my first blog, my blog managed to reach 120 views.

In another week that saw mainstream news dominated by the spread of COVID-19, FindBiometrics readers managed to keep the virus out of the latest top stories roundup. Instead, this week's collection of our most popular articles is dominated by facial recognition news, together with a bit of FinTech and a big announcement from the Department of Homeland Security. Starting with the latter, this week brought a call for submissions for the third-ever Biometric Technology Rally. This time, the DHS's Science and Technology Directorate is focused on finding solutions that can identify small groups of people within crowded environments: In FinTech news, meanwhile, FIS announced this week the launch of a new 3-D Secure payment authentication service. Another facial recognition specialist, Onfido, also got some attention with its news that it has once again been listed in CB Insights' AI 100 ranking.

What did CMSWire readers care about in 2019? Well, if you measure that by who's clicking on what, our readers are invested in watching technology moves of major vendors in digital customer experience, information management and the digital workplace. Twelve of our top 20 stories of the year covered vendor technology, including our No. 1: Virginia Backaitis' thoughtful look into the paradoxical vibe of SAP's company restructuring and multi-billion-dollar acquisition as it held its SAP Qualtrics X4 Experience Management Summit in March. Our readers also cared about the connection between employee experience and customer experience, major web design fails and why digital transformation can't be confused with customer experience. Without further ado, let's take a peek at our reader's top 20 most popular stories: Managing an organization-spanning Microsoft Teams environment is no easy task.

Here are the top 17 articles published by The Financial Brand in 2017, revealing what concerned banks and credit unions most in the past year. Insights from a crowdsourced panel of 100 financial services influencers, industry analysts and banking providers combined with the results from a global research study helps identify future trends and strategies for long-term growth. AI can improve customer personalization, identify patterns and connections that humans can't, and answer questions about banking issues in real-time. Financial institutions are already finding success with AI. However, what may be'amazing' today will be table stakes in the near future.

In this article, we discuss various strategies used to generate exponential traffic growth, while preserving traffic quality, and user loyalty. Raw data science: getting the right data sets, leveraging them, Playing with various tools and API's: designing an automated machine-to-machine communication service between Hootsuite and Twitter / LinkedIn based on insights automatically distilled from the following data sources: (1) data obtained via the Google Analytics API (traffic statistics about 50,000 live DSC articles), and (2) data collected via a web crawler written in Python A blend of high-level (strategic) data science and low-level (tactical or operational) data science. In the end, relatively little coding is involved in the process. Domain expertise and smart innovation play a critical role. Optimizing parameters of the statistical process used to select articles, create tweets, and schedule them, using experimental design and A/B testing Artificial intelligence: detection and removal of articles that are time-sensitive, automated creation of relevant hash-tags for selected tweets, and creation of a taxonomy of all our articles using simple indexing classification scheme Smart analytic-driven advertising on Twitter, using a good list of data science thought leaders worth following, as our core data set for advertising purposes. The creation of this list is an interesting data science project in itself.