This week we speak with Bastiaan Janmaat (CEO and co-Founder of DataFox) about the current and future applications of artificial intelligence in the CRM. No matter what business you're in, there's a high likelihood that managing relationships with customers, wholesalers, suppliers, or affiliates is important to your daily operations. Artificial intelligence is currently being employed to help with automating data entry, automating email and phone reminders, and even prompting salespeople with the right phone scripts in real time. In addition to covering "what's being done now" - spend the end of the interview asking Bastiaan about his predictions of the most likely AI-for-CRM capabilities that will become commonplace in the next 5 years. For more AI executive interviews, and insights into current and future AI trends that are shaking up industries, visit: www.TechEmergence.com  

Artificial intelligence is coming - should be worried about our jobs? Well, it depends. Our guest Dr. Kevin LaGrandeur spent the last two years researching the impacts of automation and artificial intelligence on society and the job market. In this interview on AI in Industry, we explore the near future of AI's impact on the world of work, and I ask Kevin some important questions, including: What skills are least "automate-able" in the next decade? What middle class professions have the greatest risk of automation, and what should those professionals be doing now to hedge against job loss? What should business leaders be doing now to prepare for "phasing out" work while still taking care of their employees? For more interviews with AI executives and researchers (and more insight on applying AI in your organization) - visit us online at: www.TechEmergence.com

Though we don't think about it on a daily basis - the technologies around us often "work" because of an underlying standard that they depend on. These technologies include: Wifi, ethernet, fax, and much of the internet itself. Do certain AI applications need their own set of standards in order to scale? Imagine if you needed a new type of cable or input every time you wanted to jack your computer into the wall? Imagine if you needed different hardware to pick up wifi in every location you moved around to? Imagine if all websites had totally different protocols for how they were loaded or served to your computer? If this were the case, it would be extremely challenging for a robust "ecosystem" of internet companies and technologies to emerge, because the technology wouldn't scale or work well at all. This week we interview Konstantinos Karachalios,‎ Managing Director of the Standards Association at the Institute of Electrical and Electronics Engineers (IEEE). Konstantinos holds a PhD in Physical and previously worked for 25 years at the European Patent Office. He speaks with us this week about the kinds of AI standards that may need to arise in order for AI to be safe and trusted enough to support a business ecosystem. Konstantinos also speaks to us about some of the current AI standards that IEEE is working on developing currently, and the implications they might have businesses everywhere.

It would be great if instead of having our car break down - could have them fixed as soon as the underlying problem began. It would be great if instead of having to diagnose a malfunctioning piece of mechanical equipment - would could have the right "fix" presented to us immediately. As it turns out, artificial intelligence may be working its way to accomplish both of those goals in the not-so-distance future. This week we interview Tilak Katsuri, CEO of Predii, a predictive maintenance AI company based on Palo Alto. Predii focuses on helping service people by using AI and sensor data to prescribe proper repairs. In this episode, Tilak speaks with us about what's currently possible within the world of "predictive maintenance," as well as the possible ramifications of industrial IoT and AI in the next 5 years. For more interviews about the real-world applications of artificial intelligence in business, visit: www.TechEmergence.com

A huge percentage of digital advertising dollars today go to Google and Facebook, who dominate that sector - and are inevitably central for the future of programmatic advertising. There’s a lot of evidence to suggest that the growth in digital advertising in the last two to three years has gone almost entirely into their coffers. At least for the foreseeable future, Facebook and Google will retain the ability to dominate that space. The ability to be able to bid for the attention of particular target audiences, whether they’re searching for a specific term, live in a specific place or they like a specific sports team, is something that doesn’t seem to be going away, and seems to be rather efficient, thanks in the large part to Artificial Intelligence. In this episode we talk to Lior Tasman who is the CEO of PredictiveBid, an Israeli-based predictive advertising optimization start-up. The team focuses on applying AI to some of the bigger issues in programmatic advertising to help draw out more ROI from ads. We discuss some of the challenges of programmatic advertising and what the future of programmatic advertising may look like from an advertiser’s perspective. For more executive interviews on the applications of AI in Industry, visit: TechEmergence.com

The big tech giants, such as Amazon, Google and Netflix, tend to set the stage in a lot of different domains and set public expectations to raise the aggregate tide of consumer experience. Our online experience is somewhat different each time we use these and other sites. This is because many of these tech giants alter their experience user per user in a real time iterative fashion in order to create sticky experiences and to beat their competitors. In this episode we talk to Adam Spector, the Co-Founder & Chief Business Officer at LiftIgniter, a company which provide a service which modulates website experience per users, for an array of different businesses. Adam and I discuss what the tech giants are doing to customize their business experiences, what data they’re using to continually alter user experience and what industries and sectors might be impacted by this aggregate trend as it moves forward. See more interviews with AI industry innovators at: www.TechEmergence.com

Imagine you work in a large organization with tens of thousands of employees across multiple countries, a business that’s been around for over a hundred years, and all of a sudden you have people in one department who are interested in applying chatbots, colleagues in another department who wish to implement sentiment analysis and still another department that wants to begin using AI for fraud and risk analysis. How do you manage to put all these pieces together? That is exactly the situation that Muriel Serrurier Schepper found herself in.  Muriel is the Business Consultant Advanced Data Analytics & Artificial Intelligence at Rabobank Digital Bank in Naarden, Netherlands. In this episode, Muriel and I discuss the Artificial Intelligence Center of Excellence at Rabobank, where she manages projects and has connected ad virtual and physical team across the company which is comprised of over 60,000 employees spread across the world. For more interviews on the applications of AI in industry, visit: www.TechEmergence.com

If you work in healthcare, or in an established business that is looking to implement AI for the first time - then this won't be an interview you'll want to miss. AYASDI is one of those rare AI startups that has raised over $100MM since its inception in 2008. This week on the "AI in Industry" podcast,

Marshall Brain discusses how wetware (the human brain) is increasingly becoming a part of a bigger system which may in itself be managed by software systems. The roles and relationships of humans and machines are rapidly changing. With the increasing advances in technology, there are fewer and fewer skills or activities that an enterprise needs from human beings, and they only need those until they can be replaced by software or hardware. For example, computer vision systems are often still not as effective as the human eye, so we still need human vision systems to recognize text or to recognize object placement, and take action accordingly (in a store, warehouse, or other setting). A human can fill that role as a piece of wetware until the software or the hardware catches up. How will man and machine collaborate in the future? We explore these dynamics in depth in this week's interview. For more interviews and insights from leading thinkers in AI and automation, visit: www.TechEmergence.com

Machine learning currently faces a number of obstacles which prevent it from advancing as quickly as it might. How might these obstacles be overcome and what impact would this have on the machine learning across different industries in the coming decade? In this episode we talk to Dr. Hanie Sedghi, Research Scientist at the Allen Institute for Artificial Intelligence, about the developments in core machine learning technology that need to be made, and that researchers and scientists are working, on to further the application of machine learning in autonomous vehicles. We also touch on some of the impact that might be made if machine learning is able to overcome its own boundaries in terms of computational research, in terms of certain algorithms, and what kind of impact that might have in the arena of autonomous driving and in the realm of natural language processing (NLP). See more episodes online at: www.TechEmergence.com