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CEO Perspective: The Challenges and Benefits of AI

What lies ahead for BI and analytics and how can AI help? Anodot's David Drai shares his outlook on the role AI will play in your future enterprise strategy.

• By James E. Powell
• June 24, 2019

Are you getting the most out of AI? David Drai, CEO and cofounder of Anodot, says getting the most from this "new" technology may create more challenges than you realize.

For Further Reading: Autonomous BI and Analytics: Are We There Yet? Prescription for Business Success: A New Breed of Analytics How Can Augmented Analytics Benefit Your Role?

Upside: What technology or methodology must be part of an enterprise's data strategy if it wants to be competitive today? Why?

David Drai: AI and ML. We've all seen the clear trend for over a decade: data volume is expanding dramatically. Over the past few years, the technology for scanning all this data also became available. An enterprise needs to verify that it is analyzing and scanning all its data in order to identify everything that happens and optimize the relationship with each and every customer or user.

What one emerging technology are you most excited about and think has the greatest potential? What's so special about this technology?

Anomaly detection. This enables enterprises to really check the pulse of their service and experience at all times. Anomaly detection has become a must for any enterprise facing an explosion of data. It (along with automatic baselining) is the smartest and fastest methodology to analyze 100% of your data.

What is the single biggest challenge enterprises face today? How do most enterprises respond (and is it working)?

The customer experience. In the world of constant competition, every element of the customer journey must be monitored. Enterprises are expected to deliver exceptional customer service at any stage of the journey. The best example we have seen in the field is, of course, Amazon's customer approach. Building proactive organizations that see things ahead of time (or as soon as possible) and make the needed adjustments is critical for great customer care.

Is there a new technology in data and analytics that is creating more challenges than most people realize? How should enterprises adjust their approach to it?

It's clear that not everyone understands how to get the most out of AI. People think too often of computer vision, image recognition, and other complex applications. We've learned AI adoption should start with finding the use case that makes real business sense for your organization.

Where do you see analytics and data management headed in 2019 and beyond? What's just over the horizon that we haven't heard much about yet?

Autonomous analytics. This is an approach where data has its own voice. Data is collected (like today), but when something important happens the data lets you know. You don't have to query it; you don't have to look at the dashboard. The data comes to you, knocks on your door, and asks you to pay attention.

Describe your product/solution and the problem it solves for enterprises.

We use AI to constantly monitor and forecast business performance for customers such as leading telco, e-commerce, and financial services companies. Our Autonomous Analytics leverages the power of AI and ML to constantly analyze and correlate every business metric, providing real-time alerts and forecasts in context. As a result, enterprises enjoy shorter detection and resolution times as well as faster forecasts for optimizing business operations and maximizing ROI.

Editor's note: David Drai is CEO and cofounder of Anodot, where he is committed to helping data-driven companies illuminate business blind spots with AI analytics. He previously was CTO at Gett, an app-based transportation service used in hundreds of cities worldwide. Prior to Gett, David cofounded Cotendo, a content delivery network and site acceleration services provider that was acquired by Akamai Technologies, where he also served as CTO. He graduated from Technion - Israel Institute of Technology with a bachelor of science degree in computer science.