New Industry Study Reveals Chief Data and Analytics Officers Lack the Resources to Deliver on Enterprise AI/ML Innovation Goals
95% of business leaders are betting on AI to increase company revenues but underinvestments across data science spanning people, process and technology limit AI/ML transformational potential
Organizations not investing in hybrid- and multi-cloud AI/ML capabilities are nearly five years behind their peers
SAN FRANCISCO, March 14, 2023 /PRNewswire/ -- Domino Data Lab, provider of the leading enterprise MLOps platform trusted by over 20% of the Fortune 100, today released a new industry report, "Build A Winning AI Offense: C-Level Strategies for an ML-Fueled Revenue Engine." The study determined that while data science is now a key revenue and innovation engine for the enterprise, most enterprise data and analytics leaders are inadequately resourced to deliver on what business leadership wants from AI and ML innovation.
The survey of 100 Chief Data Officers (CDOs) and Chief Data Analytics Officers (CDAOs) at companies with $1B+ in revenue, conducted by Wakefield Research, paints a stunning picture of the mounting revenue expectations put on these leaders and their teams, the organizational imbalances data execs say their leadership must correct, and the toll that underfunded, understaffed and under-governed data science practices take at many large organizations.
Data Science Teams Unprepared to Deliver on AI/ML Innovation Despite Corporate Revenue Expectations
Under pressure, the majority of CDOs and CDAOs (67%) are shifting their organization's data posture from defensive; i.e., data management, compliance, governance and BI modernization, to offensive; i.e., driving new business value with analytics, ML and AI applications. As such, it's no surprise that nearly all (95%) say their company leadership expects investments in AI and ML applications will result in a revenue increase.
Yet, while business leaders increasingly look to data science to be a key revenue engine and a driver of innovation, resources such as budget, people and preparedness are not aligned with these corporate priorities. Indeed, data science is not funded to live up to leadership expectations - less than a fifth (19%) say their data science teams have been provided sufficient AI and ML resources to meet leadership's expectations for a revenue increase.
"Data science executives need proper resources, empowerment and support to achieve revenue and transformation goals," said Nick Elprin, co-founder and CEO of Domino Data Lab. "Boards and the full C-suite must invest in CDOs and CDAOs and put them in charge of people, process and AI/ML technologies, or risk existential competitive pressures."
Put Me in, Coach: CDOs and CDAOs Are Ready to Take the Reins, and Budget
Unleashing the Full Potential of Data Science: Overcoming Pain Points Beyond Funding
Lagging Capabilities Result in AI Risks with Negative Impact Today
"Being model-driven is essential for success, but CDOs and CDAOs often lack the authority to lead IT and other stakeholders towards these goals," said Kjell Carlsson, Domino's Head of Data Science Strategy & Evangelism. "This study clearly demonstrates that they both want and need to take the reins and get on the offense, and the rising tide of data regulations and governance needs makes them perfect for the job."
The AI/ML Divide Is Real and Growing
To access the full study: https://www.dominodatalab.com/resources/build-a-winning-AI-offense-wakefield-report
The Domino Data Lab survey was conducted by Wakefield Research (www.wakefieldresearch.com) among 100 US Chief Data Officers or Chief Data Analytics Officers at companies with $1b+ annual revenue, between December 5th and December 18th, 2022, using an email invitation and an online survey. The margin of error for the study is +/- 9.8%.
About Domino Data Lab
Domino Data Lab powers model-driven businesses with its leading Enterprise MLOps platform trusted by over 20% of the Fortune 100. Domino accelerates the development and deployment of data science work while increasing collaboration and governance. With Domino, enterprises worldwide can develop better medicines, grow more productive crops, build better cars, and much more. Founded in 2013, Domino is backed by Coatue Management, Great Hill Partners, Highland Capital, Sequoia Capital and other leading investors. For more information, visit www.dominodatalab.com.
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SOURCE Domino Data Lab