Making Enterprise AI an Organizational Asset

How can your company become an AI enterprise? Dataiku enables organizations across all industries to embed machine learning methodology into the very core of their business to bring real value.

Enterprise AI is the ability to embed AI methodology — which combines the human capacities for learning, perception, and interaction all at a level of complexity that ultimately supersedes our own abilities — into the very core of an organization’s data strategy.

Enterprise AI isn’t just a trend or something to be leveraged for one-off projects and use cases. The ability to become a true AI enterprise by successfully scaling and employing robust data methodology at all levels of the company is an organizational asset pivotal to the success of businesses of the future, no matter what industry.

In other words, companies that start today and are able to build their capacity to leverage Enterprise AI now are building the foundation for the future of the business. This future is one where only companies augmenting human capital with AI survive.

The ability to successfully scale & employ Enterprise AI is an organizational asset pivotal to the success of businesses of the future, no matter what industry."
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Download the 2021 Gartner Magic Quadrant for Data Science and Machine-Learning Platforms

How Does Enterprise AI Happen?

At Dataiku, we’ve seen a lot of businesses struggle to get started on their Enterprise AI journey over the years and we’ve also seen some that have thrived. The companies that succeed are the ones that go beyond leveraging Enterprise AI for one particular project or use case and instead focus on scaling it out to a level that will sustain the business in the future.

Scaled Enterprise AI companies manage to build a foundation for data science, machine learning, and AI at an organizational level. In addition, they:

  • BRING ALL PEOPLE TOGETHER around AI efforts, from business people to analysts and data scientists. Enterprise AI companies leverage horizontal (team-wide) and vertical (cross-team) collaboration.


You want to look for a tool that … provide[s] the collaborative approach. That’s what’s going to be necessary to actually take an AI idea from inception and bring it all the way to production." Mike Gualtieri VP & Principal Analyst @ Forrester
  • ITERATE RAPIDLY on a spectrum of data applications, whether that means building out a self-serve analytics platform or fully operationalized AI integrated with business processes. 
  • PRIORITIZE RESPONSIBLE AI, including sound governance practices and sustainable systems that will be agile and open to changing technological needs. With future exponential growth in the number of AI projects, the number of people contributing to such projects, and the number and size of data in such projects, elasticity amidst enterprise AI companies is critical.

Get the Ebook: 5 Myths (& Realities) on Responsible AI for Business Leaders

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By 2022, 75% of new end-user solutions leveraging AI and ML techniques will be built with commercial solutions rather than open source platforms." Gartner Source

Dataiku: Your Path to Enterprise AI

Dataiku is one of the world’s leading AI and machine learning platforms, supporting agility in organizations’ data efforts via collaborative, elastic, and responsible AI, all at enterprise scale.

Dataiku is:

  • End-to-end with one simple UI for data wrangling, mining, visualization, machine learning, deployment, and monitoring.
  • Collaborative, with a team-based user interface accessible to anyone on a data team, from data scientist to business analyst.
  • Operationally ready, with the ability to go from design to production smoothly.

Private: Full Elasticity as the Future of AI

There is no question that elasticity, including on-demand compute resource management, is the future of Enterprise AI.

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