What level of AI fluency are you aiming to achieve across most data and analytics employees in your organization this year?

Innovation & Emerging TrendsTalent Management & Performance

Awareness: Basic understanding of AI and its applications. Aware of AI technologies and societal impact57%

Familiarity: Deeper understanding of AI concepts, techniques, and terminology. Can explain common AI algorithms and methods14%

Proficiency: Solid understanding of AI principles, algorithms, and methodologies. Can apply AI techniques to solve real-world problems29%

Expertise: Advanced knowledge and expertise in AI. Well-versed in various AI domains and can develop complex AI systems

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Senior Data and Analytics Leader in Governmenta year ago

We want them to be AI-savvy, capable of not just applying pre-built models, but also understanding the underlying concepts and reasoning behind them.

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Are you concerned that introducing AI in analytics will make people less interested in the truth and more interested in quick answers that are “good enough”?

Major concern14%

Moderate concern68%

Minor concern13%

Not at all concerned4%

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What metrics do you rely on to prove the value of your data team?

OKRs tied to data objectives25%

Time saved (operational efficiency, time-to-decisions, etc.)50%

Cost reductions54%

Stakeholder value perception31%

Productive output quantities (decisions made, successful pipelines created, data products launched, etc.)35%

Internal data monetization metrics21%

External data monetization metrics18%

Other4%

None, but we should3%

None, and we shouldn’t have to2%

None1%

Not sure1%

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