First Annual ‘State of ModelOps’ Report Finds 80 Percent of Surveyed Executives View Managing Risk and Compliance as Key Barriers to Unlocking Value from AI

Key Findings From Panel of 100 Industry Experts is First-Ever Customer-Centered Analysis of AI Operationalization Challenges

ModelOp, the pioneer of ModelOps software for major enterprises, announces release of the first annual State of ModelOps report. Conducted by independent research firm Corinium Intelligence, the report summarizes the first ever research into the state of model operationalization and details the challenges faced by AI-focused executives from top global financial services companies as they scale their AI initiatives. Findings show that while AI is already widely deployed in many large enterprises and investments are growing, nearly 80 percent of surveyed executives reported difficulty managing risk as a barrier to AI adoption, and cite ModelOps as a key enterprise discipline that is receiving significantly increased attention and investment.

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The report is based on interviews with 100 executives from top global financial services companies in early 2021, providing a unique snapshot of the practices and future plans of large enterprises to govern and scale mission-critical AI initiatives. The findings were combined with commentary and insight from seven industry experts from organizations including Wells Fargo Asset Management, NY Life Insurance, BNY Mellon, FICO and others. The release of the report corresponds with the first annual ModelOps Summit, occurring on April 15th, 2021.

“Experience has shown that creating AI models is only half the battle. Operationalizing models – getting them into production, keeping them functioning properly and within guidelines for compliance and risk, and demonstrating their business value – is the next frontier as organizations mature and scale their AI initiatives,” notes Stu Bailey, Co-Founder and Chief Enterprise AI Architect at ModelOp. “As the Report shows, enterprises increasingly view ModelOps as the key to ensuring operational excellence and maximizing value from their AI initiatives, in the same way that DevOps, ITOps and SecOps have for the development, IT and cybersecurity sectors.”

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Key Report Findings

Highlights from the survey of 100 AI-focused executives from F100 and Global financial services companies include the following:

• They have an average of 270 models in production, representing a wide range of model types
• Their data scientists are using 5-7 different tools to develop models
• Only 25% rate their existing processes for inventorying models in production as ‘very effective’
• 80% say difficulty managing risk and ensuring compliance is a key barrier to AI adoption
• 69% say improving the enforcement of AI governance processes is a key reason to invest in a ModelOps platform.
• 76% of respondents say achieving cost reductions is at least a ‘very important’ benefit of such an investment, with 42% describing it as crucial
• 90% have or expect to have a dedicated budget for ModelOps within 12 months.

Additionally, a number of AI leaders provided candid and insightful remarks. Skip McCormick, Data Science Fellow at BNY Mellon offered the following: “ModelOps is the next logical step after DevOps. We’re looking for a systematic way to make sure that the models we’re putting into play actually do what they should do.”

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