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International Data Corporation (IDC) reported in their  Worldwide Semiannual Big Data and Analytics Spending Guide that global investment in big data and business analytics (BDA) will grow from $130.1 billion in 2016 to more than $203 billion in 2020. In a previous report, we covered machine learning in the finance sector, and in this report, we dive deeper into big data solutions and data management platforms for financial institutions. The companies in this report all claim to help financial institutions with at least one of the following:

The oil and gas industry is usually divided into three major operational sectors: upstream, midstream, and downstream. Upstream involves the exploration and production of oil and natural gas. Midstream usually refers to transportation and storage stages. Downstream encompasses the various processes involved in refining and selling oil.

Government interest in AI has picked up in recent years, and many government officials are starting to ask the same questions business executives were asking two or three years ago. Governments and large NGOs are starting to invest in AI, spending budget and time on pilot programs for various AI applications and discussions with people in the field on the future implications of the technology.

Episode Summary: In this episode of AI In Industry, we interview Nick Possley, the CTO of a company called AllyO, based in the San Francisco Bay area. We speak with Nick about where artificial intelligence and machine learning are playing a role in recruiting today and how picking the right candidates from a pool is in some way being informed by artificial intelligence.

Most of the time when we have requests for speaking engagements here at Emerj, they're from business leaders. At the time this article was published, I just came back from a presentation at National Defense University in Washington DC. Presenting there was unique in many regards. Obviously, the use cases for tanks and submarines are quite different than they are for drug development or selling more products off retail shelves.

Moore Stephens estimated the size of the marketing technology or martech industry around $24 billion in 2017. It follows that AI would find its way into the martech world. Numerous companies claiming to assist organizations in their marketing; we wrote a report on marketing and AI detailing this connection.

KPMG estimated the size of the automotive insurance is expected to shrink by 70% due to the rise in demand for autonomous cars and the shift in liability then being placed on the car manufacturer. With the rise of AI in most sectors, it follows that AI would find its way into the automotive insurance world. AI may allow car insurance companies to keep up with an evolving consumer base that is looking for faster service, faster payouts, and policy prices tailored to them.

In 2017, Emerj conducted research into the applications of machine learning in marketing with 51 different AI-focused marketing executives. The AI marketing vendors we spoke to named retail and eCommerce as the top sectors ripe for applying marketing AI software. Below is a graphic from our research showing the sectors that AI marketing vendors sell into most:

Robotic process automation, or RPA, is a technology used across multiple industries to automate business processes. RPA software involves what are known as "software robots" to handle repetitive tasks traditionally handled by human employees. That said, there are no actual robots involved in the way one might see in manufacturing or heavy industry.

We have discussed the importance of having the right talent in place when it comes to AI adoption in enterprise quite thoroughly here at Emerj. The scarcity of data science talent and its price point are one of the main reasons small businesses are not likely to adopt AI successfully at this time.