AI Observability Study Reveals Global Gaps; North America Leads in Adoption and Maturity

April 29, 2025
AI Observability Study Reveals Global Gaps; North America Leads in Adoption and Maturity
  • Cameron Ogden from Precisely emphasizes that observability is a foundational capability for ensuring data integrity and quality, which are essential for trustworthy AI outcomes.

  • The study reveals that North American firms show higher AI adoption and observability maturity than their European counterparts, with 88% of North American organizations formalizing observability programs compared to just 47% in Europe.

  • Organizations are increasingly expanding their observability efforts to include diverse data types, with 62% exploring semi-structured data and 60% evaluating unstructured documents, recognizing their importance for advanced AI applications.

  • This uneven maturity in observability programs highlights significant gaps, as many organizations struggle with underdeveloped practices that could jeopardize their AI initiatives.

  • The survey methodology included responses from various industries, providing a comprehensive view of observability adoption and the challenges faced by organizations in this rapidly evolving landscape.

  • A recent global research study conducted by Precisely and BARC has unveiled critical insights into observability trends and challenges in AI innovation, based on a survey of over 250 data and AI stakeholders worldwide.

  • Despite 76% of organizations implementing observability programs for data quality and pipelines, and 70% focusing on AI/ML model observability, many exhibit inconsistent practices that hinder their AI objectives.

  • Additionally, North American organizations prioritize regulatory compliance and data privacy more than their European counterparts, despite the lack of similar federal AI regulations.

  • However, 68% of respondents reported using qualitative or quantitative metrics to evaluate their observability efforts, yet many lack structured measurement, which poses risks to achieving their AI goals.

  • Ogden further notes that observability is critical for ensuring data governance necessary for reliable AI models, especially as the landscape of AI use cases becomes increasingly complex.

  • Precisely is recognized as a leader in data integrity, serving over 12,000 organizations globally, including 93 of the Fortune 100, underscoring its influence in the field.

  • Overall, the study highlights a significant trend towards incorporating semi-structured and unstructured data into observability programs, which is crucial for the future of AI-driven innovations.

Summary based on 6 sources


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