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White Paper

Driving Efficiency in Cyberspace Through AI

The cybersecurity space faces a severe drought of skilled cybersecurity professionals, while cybercrime and cyberattacks are growing exponentially. In this environment, global organizations are facing a variety of challenges and the risks are growing every day.

The use of AI in cybersecurity allows organizations to detect, discover, predict, and respond to cyberthreats in real-time using machine and deep learning. AI automates manual and repetitive tasks that would otherwise be left for humans. This automation enables the security teams to focus time on critical investigations and scale their efforts without needing to scale their manpower.

Our white paper, Driving Efficiency in Cyberspace Through AI, dives deeper into the current state of AI in cybersecurity and explores the untapped opportunities for growth, efficiency, and advanced risk management.

Download the white paper to learn:

  • How AI can empower cyber missions to deliver on their promises
  • Which specific applications of AI can drive value for cybersecurity teams
  • How DataRobot AI Cloud is uniquely equipped to help cybersecurity teams improve their operational efficiency
  • DataRobot's platform makes my work exciting, my job fun, and the results more accurate and timely – it's almost like magic!
    Omair Tariq
    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
    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

  • 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