Joe McKendrick is an author and independent analyst who tracks the impact of information technology on management and markets. As an independent analyst, he has authored numerous research reports in partnership with Forbes Insights, IDC, and Unisphere Research, a division of Information Today, Inc. Building and supporting the artificial intelligence infrastructure that is guiding our businesses is not an easy job. The applications, data and networks behind the scenes have to perform as close to flawlessly as possible, in real time. The good news is AI itself can be employed to provide relief to stressed IT teams. AIOps - artificial intelligence for IT operations - is paving the way to autonomous operations of critical enterprise systems.

Luke Han is a Co-Founder and CEO of Kyligence, as well as co-founder and Project Management Committee member for Apache Kylin. The era of cloud data has changed drastically. Data that was once concentrated in one location or a central repository is now distributed, and with data spread out, individuals can access it anytime, anywhere. While accessing data has become easier than ever, however, it has also created chaos when it comes to using that data. Disparate data storage has scattered data almost to the point of being unusable.

From wild speculation that flying cars will become the norm to robots that will be able to tend to our every need, there is lots of buzz about how AI, Machine Learning, and Deep Learning will change our lives. However, at present, it seems like a far-fetched future. As we enter the 2020s, there will be significant progress in the march towards the democratization of data that will fuel some significant changes. Gartner identified democratization as one of its top ten strategic technology trends for the enterprise in 2020 and this shift in ownership of data means that anyone can use the information at any time to make decisions. The democratization of data is frequently referred to as citizen access to data.

And we are only beginning to see the potential benefits of AI applications within the enterprise. The growth of AI in the enterprise, however, has been hampered because data scientists too often have limited access to the relevant data they need to build effective AI models. These data specialists are frequently forced rely solely on a few known sources, like existing data warehouses, rather than being able to tap into all the real-time, real-life data they need. In addition, many companies have great difficulty efficiently and affordably determining the business context and quality of massive amounts of data instantly. Given these difficulties, it's easy to understand some of the historical barriers to AI acceleration and adoption.

Inarguably, technology has shaped the current state of procurement. At the Global Procurement Tech Summit, it was evident how true this has become. IBM's Vice President of Global Procurement Dan Carrell gave a presentation putting the topic into perspective. He shed light on how a massive corporation deals with procurement and even how IBM's Watson is helping their procurement processes. Procurement to go through Digital Transformation… like other industries!