Ten Keys to AI Success in 2020: Insights from Industry Leaders

With companies around the world adopting AI at a rapid pace, we polled over 170 global enterprise customers to collect their feedback on the challenges and successes they’ve had with AI. This report shares their experience and knowledge, such as:

  • How executive leadership influences AI initiatives
  • The importance of early adoption for your organization’s AI success
  • How data quality issues affect an organization’s ability to spin up AI projects
  • How business and analytics processes need to merge to achieve success with AI
  • Why organizations need to relentlessly measure the ROI of their AI initiatives
  • How business leaders are transforming teams to become AI-driven
DataRobot justifies its place by providing value and returning significant ROI immediately.
Beaumont Vance
Beaumont Vance

Head of Enterprise Analytics, TD Ameritrade

I’ve never had so much ease explaining the inner workings of my models as I do with DataRobot.
Akshay Tandon
Akshay Tandon

VP of Strategy Analytics, LendingTree

We want to be truly customer-focused with all our 16 million customers, and to do that we need to be able to predict the potential behavior of each of them to put the right offer in front of them at the right time. There's no way we can be as customer-focused as we would like without the help of machine learning.
Paul Davies
Paul Davies

Head of Data Science, Domestic & General

DataRobot gives you all the tools you need. It will democratize machine learning across the whole business.
Pardeep Bassi
Pardeep Bassi

Head of Data Science, LV=

Analytics is far too important to be left to the analyst. With these sorts of tools, we can have the whole business being more data-driven, because the power to build really great models lies in many more hands.
Oliver Rees
Oliver Rees

General Manager – Torque Data at Virgin Australia