Anodot VP of Customer Success Avi Avital hosted data managers from several industry-leading companies making use of artificial intelligence for a panel discussion, “Fact vs. Fiction in the Application of Artificial Intelligence, Machine Learning and Deep Learning,” at the 2019 Chief Data & Analytics Officer (CDAO) Exchange, in Southern California this January.

During this talk, George Bezerra, Senior Director of Data Science at TripAdvisor, Jaya Kolhatkar, Chief Data Officer at Hulu, David Dadoun, Senior Director Business Intelligence and Data Governance at Aldo Group, discussed with Avital the aspects of utilizing AI/ML for business, the future of AI, and shared practical tips for implementation, such as computer vision, machine learning and deep learning, in contemporary enterprises.

When discussing AI/ML business applications, panel members shared their insight into the proper workflow. “With AI… you need to start with a business proposition, with a business value, an opportunity that you’re trying to solve for,” said Dadoun, “and as long as you feel that with the people that you have, the tools that you have to address that situation, or that problem, then you should.”

When addressing the issue, Kolhatkar stressed the importance of coordinating between the research and development units and the business units: “We spent a lot of time (asking the business team), ‘If you were to build this, how would you use it? What is the KPI that this should drive?’ There’s an educational aspect with the business teams that you also have to think about, and you have to actually do that work to allow your AI to be successful.”

When discussing the future of AI/ML for business, panel members suggested various ways in which the industry can evolve in the future, including more precise algorithms and a growing number of use cases. Bezerra stated that a major advancement in the near future would be further automation of processes and easier deployment of algorithms: “What we are focusing on… is how do we streamline the process of development and put models in production… The goal for me would be to have one-click-deployment of a model. Right now the deployment process is fast but it still takes a lot of engineering.”

Panel members continued to share from their experience, discussing some of the less-successful projects they came across in their careers and how they managed to overcome them. Then, members gave their advice on changes brought upon by the utilization of new technology, and how to get members of the organizations and customers on board with them.

Written by Anodot

Anodot leads in Autonomous Business Monitoring, offering real-time incident detection and innovative cloud cost management solutions with a primary focus on partnerships and MSP collaboration. Our machine learning platform not only identifies business incidents promptly but also optimizes cloud resources, reducing waste. By reducing alert noise by up to 95 percent and slashing time to detection by as much as 80 percent, Anodot has helped customers recover millions in time and revenue.

You'll believe it when you see it