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Episode summary: In this week’s episode we focus on AI application in the customer service business function, - specifically in the context of call centers. We speak with Ali Azarbayejani, CTO of Cogito based in the Boston area, which works on coaching and providing feedback for call center agents in real time.

A 2017 report by the Pew Research Center found that 69 percent of the American public use some type of social media, like Facebook, Twitter, Instagram, and others.

As interest in artificial intelligence has exploded in the last two years, the prevalence of AI-related events has followed suit.
Leaders across industries are developing an interest in where AI will impact their sectors, and what they should be doing about it now. In partnership with RE•WORK, we decided to get perspective on the value of networking and events from executives with experience both in business, and in hard science of AI.
Our interviewees for this article - Tom Wilde, CEO at indico, and Daniel Golden, Director of Machine Learning at Arterys - are speakers at the RE•WORK Deep Learning Summit & Deep Learning in Healthcare Summit on May 24 - 25th in Boston, MA.
In this article we’ll aim to answer the following questions:

There is a consensus among industry experts (both from our own insurance AI secondary research, and according to a 2017 Accenture survey report) that AI is going to be a key driver in making insurance products "smarter" in the coming 2-3 years.

Dermatology is defined as a branch of medicine primarily focused on the evaluation and treatment of skin disorders, including hair and nails. Market research firm BCC Research projects that the global market for skin disease treatment technologies will reach $20.4 billion in 2020. Based on $17.1 billion in market revenue in 2015, this anticipated increase represents a five-year compound annual growth rate (CAGR) of 3.6 percent.

Tech Provider: TAMR - a company that automates the organization of a company’s enterprise-wide data through a machine learning-driven plus human-guided solution

Episode summary: There are many challenges to bringing AI into an enterprise for example the lack of skilled AI talent, or issues around data organization. In this week's episode, we focus on AI adoption in the enterprise from an investor’s perspective.

Artificial intelligence has already established a small but growing presence in the life sciences industry today, starting with drug discovery and development and now in emerging applications across the product life cycle.

The following brand partnership article was written by BIS Research analyst Rahul Papney, and edited by Raghav Bharadwaj of Emerj. For information about our advertising and publishing arrangements with brands, please visit our partnerships page.

With "machine learning" excitement in full swing, Boston is buzzing as always with it's own batch of startups, accelerators, and VCs, and I decided to do a deep dive into the local artificial intelligence ecosystem.