The AI-powered enterprise

Unlocking the potential of AI at scale

Time to tip the AI scales in your favor

Billions of dollars have been flooding into AI. And it’s no wonder – after all, this technology has the power to utterly transform the way we do business. More and more companies across sectors are moving beyond pilots and proofs of concept. But how successful are they at achieving scale, especially in light of the current pandemic?

To find out, for the latest report from the Capgemini Research InstituteThe AI-powered enterprise: Unlocking the potential of AI at scale  we surveyed close to one thousand organizations, with at least one billion dollars in annual revenues and ongoing AI initiatives, and conducted extensive, in-depth interviews with relevant executives. We found that:

  • Scaling AI isn’t easy. Even though more organizations are moving beyond pilots, only 13% have rolled out multiple AI applications across numerous teams and the COVID-19 crisis isn’t helping those that haven’t.
  • But it’s worth it. 97% of the AI-at-scale leaders have seen quantifiable benefits from their deployments and are much more likely to have achieved benefits that meet or exceed their expectations when it comes to generating revenues, reducing risks, engaging with customers, and optimizing costs.
  • And it helps to have a plan. High-performing organizations follow four principles: Empower, Operationalize, Nurture, Monitor and amplify.

To successfully scale AI, leading organizations lay strong data foundations engrained with the right tools, technology platforms, and agile practices. They establish balanced operating models, create ethical AI algorithms, and cultivate rich talent and partner pools. Finally, they continuously check their AI models for accuracy and impact in order to amplify business outcomes. The benefits of AI are there for the taking. You just have to tip the scales to reach them.

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Sound Bites

Amith Parameshwara, Leader of the global AI and Data Science team, Kimberly-Clark

One of the challenges of productionalizing a use case beyond proof of concept is that it requires involvement of the data science team as well as many other teams, including business teams

Mindy Simon, Chief Information Officer at Conagra

We’ve reduced the time pretty dramatically in terms of being able to see the behaviors in the market and being able to execute on them

Key Takeaways


of organizations surveyed mentioned they maintain human oversight for AI models


of the AI-at-scale leaders continue to progress their AI initiatives at the same pace as before


of the AI-at-scale leaders have actually increased the pace of deployment

About the Capgemini Research Institute

Capgemini Research Institute

Capgemini’s #1 ranked in-house think tank on all things digital