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

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

According to a recent PwC report, AI could contribute up to $15.7 trillion to the global economy by 2030. 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.

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

We gathered our findings into one report, Ten Keys to AI Success in 2020: Insights from Industry Leaders , where executives share their experience and knowledge, such as:

  • How companies are working strategically to ensure AI adoption across their organizations
  • The competitive advantages early adopters of AI are gaining
  • The ways in which today’s leaders are getting diverse teams invested in becoming AI-driven
  • Choosing the right use cases to ensure AI success
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely -- it's almost like magic!
    Omair Tariq

    Data Analyst, Symphony Post Acute Network

  • I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
    Oliver Rees

    General Manager – Torque Data at Virgin Australia

  • At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
    Akshay Tandon
    Akshay Tandon

    VP of Strategy Analytics, LendingTree

  • DataRobot allows us to understand the data that’s being fed into our models without blindly feeding whatever we get into our system. DataRobot makes my team very effective.
    Deena Narayanaswamy
    Deena Narayanaswamy

    Head of Data Insights, Avant

  • We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.
    Evariant