Fake news spreads six times faster than factual news. The algorithms built into social media software, in an effort to hold our attention, feed us information that triggers the basest instincts of our complex psychologies. These are some of the starkest realities exposed in the Netflix documentary “The Social Dilemma.” Holding our attention is what the robot (if you will) was programmed to do. And it’s doing its job really, really well.

Let me share with you my story about finding the right AI Solution to improve our support self service. The starting point of my journey was pretty common, many will read this and think “Yes! I suffer the same pain”. At JFrog we produce tons of relevant and clever documentation. It’s all out there, available. And yet, we struggle to get to the right piece of information when looking for something specific.

With the promise of unprecedented potential, artificial intelligence (AI) and predictive analytics have permeated into every field of business. Due to their ability to help retail staff serve customers better, personalize video recommendations based on users’ preferences, reduce employee churn, and detect fraud and security threats, AI and predictive analysis are rapidly being adapted across industry verticals.

As your tech stack increases, every new device (network devices, servers, applications) creates a large amount of distributed log data. This forms part of what is called “machine data”, which is growing 50x faster than traditional business data. In fact, everything in your stack is continuously writing new events to your log files, including error logs that contain a record of critical errors encountered by a running application, operating system, or server.

In 1927, the world was introduced to the origins of Artificial Intelligence (AI) in the form of a robot in the movie Metropolis. Throughout nearly a century since then, movies have continued to iterate on the complexities of AI, as both a fun take on it and serious commentary on the potential concerns and consequences. This is all well and good, but as AI has continued to evolve, we find ourselves asking, “how can we actually use this to make our lives easier?”

Every company in the world needs to reduce risk and uncertainty in its IT operations, ITOM. The best way to do that is by combining AI and digital workflows. It’s all about applying machine learning to operational data so that you can generate insights about potential system issues, and then launch automated workflows that resolve problems fast—ideally, before they impact customers. Today’s partnership announcement between IBM and ServiceNow is great news for enterprise customers.

From a security breach to a complete system outage, when an incident occurs and your network or service is impacted, it’s typically the result of a chain of events. A problem with one service has impacted another service, and so on until finally, you’re facing a problem that’s compromising availability and damaging your customer experience. In the event of a serious incident, your team’s immediate response is to focus on identifying the root cause and restoring service.

Think about your last online order. If you’re a frequent online shopper and have created profiles for sites you visit often (*raises hand*), then you’re probably familiar with customized recommendations. Based on your purchase history, location, and other factors, the website may suggest other items you might be interested in buying. And if you’re on the site long enough, chatbots may appear asking if you have questions or need assistance locating something.