Are You an AI Leader or Laggard?

This article was written by DataRobot and originally appeared on the DataRobot Blog here:


DataRobot and other AI leaders recently collaborated with ESI ThoughtLab, the thought leadership arm of Econsult Solutions, to generate a benchmark study of senior executives in 1,200 companies focused on the impact of AI on ROI. The report’s goals included defining the essential characteristics of AI leaders.

The report classified firms as beginners, implementers, advancers, and leaders, and used two crucial criteria to discern leading firms from those lagging behind:

AI Implementation

  • Level of AI maturity across the enterprise
  • Progress in precise fields of AI, such as talent development and business case creation
  • Growth of implementing AI for essential operations, such as finance or marketing

AI Effectiveness

  • Business, financial, and market benefits derived from AI impact on revenues and costs
  • ROI from AI implementation in essential operations, such as marketing or finance
  • Performance gains in industry-specific processes

The report further details how companies are taking specific steps to become AI leaders or maintain and enhance their current, respective positions.

AI Leaders Must Master an Array of AI Technologies, especially RPA and Machine Learning

As chatbots have become a standard part of customer service for most AI leaders, computer vision, natural language processing (NLP), and deep learning are also being added atop a foundation of AIRPA and machine learning, the report concludes. Laggards, meanwhile, are behind with technologies such as computer vision, NLP, and deep learning, but are expected to be on par with leaders in RPA and machine learning by 2023. The numbers are compelling:

  • Only 18% of non-leaders today have mature or advanced stages of RPA, and that number drops to 8% for machine learning.
  • In three years, 63% of non-leaders will be at the mature or advanced stages of RPA, and 37% are forecasted to be sitting at mature or advanced stages for machine learning.
  • AI leaders, meanwhile, will be nearing perfection with 97% at the advanced or mature stage of RPA and 94% for machine learning in three years’ time.

AI Leaders Shine at Managing Data

In addition to mastering RPA and machine learning, AI leaders are renowned for their advanced data management skills, with adoption at a rate of up to 91%. Beginners, meanwhile, have a shocking 0% level of mature or advanced data management. By 2023, 35% of beginners plan to have more sophisticated data management systems in place, while leaders will be up to 97%, the report notes.

Taking those numbers into account, the report reiterates that data lies at the heart of AI success:

  • 46% of CEOs and 53% of CIOs stress the importance of ensuring your data management system can support AI.
  • 91% of AI leaders have mature or advanced data management systems, a number expected to grow to 97% by 2023.
  • Beginners spend 44% of their AI budgets on data management, compared to 35% for leaders.
  • 70% of firms with revenue over $20 billion hold the competitive advantage of having advanced data management systems, enabling them to utilize their respective stockpile of data.
  • The Americas are out front in the data race. 43% of firms there are ahead in managing data vs. 35% in APAC and 33% in Europe.

Diversifying Data Formats Unleashes Higher Value

While sophisticated data management is essential, assimilating various data formats also unleashes higher value for AI. Text and image are still the most popular data configurations today and look to remain so for the next three years. Video and high-dimensional data, the reports states, are predicted to be among the quickest to develop:

  • Video will have a near 100% increase over the next three years.
  • Use of high-dimensional data is predicted to rise from 19% to 47%.
  • Use of image and audio data is also expected to be on the rise.


Artificial intelligence is not a magic pill. It may take years to become an AI leader. AI beginners looking to get ahead need to lay a foundation of data management, RPA, and machine learning while AI leaders must actively integrate new data formats, such as computer vision, NLP, and deep learning to stay ahead of the pack. Whether you are an AI leader or in the early stages of your AI journey, download and read the full report to learn more about the best practices that can help you on your journey to becoming an AI leader.