New Global Research Reveals Key Observability Trends and Challenges for AI Innovation

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Observability program maturity is uneven across data quality, data pipelines, and AI/ML models, as unstructured data adoption grows

BURLINGTON, Mass., April 29, 2025 /PRNewswire/ -- Precisely, the global leader in data integrity, today announced the results of new global research. The Observability for AI Innovation study, created by Business Application Research Centre (BARC) and sponsored by Precisely, surveyed a diverse set of over 250 data and AI stakeholders worldwide, uncovering critical insights into how organizations leverage observability to drive trusted AI and analytics outcomes.

As organizations scale their use of AI, observability has become a foundational requirement for ensuring transparency, accountability, and performance across data ecosystems. The research reveals that while many companies have taken significant steps to formalize observability programs, progress varies across disciplines. Differences in program maturity, measurement practices, and regional adoption trends all point to areas that still require attention.

AI Observability is Gaining Traction, but Gaps Remain

76% of organizations have formalized, implemented, or optimized programs for both data quality and data pipeline observability, demonstrating a strong commitment to building trusted AI foundations. While AI/ML model observability is close behind at 70%, the responses indicate a broader range of maturity levels, with many organizations still operating with inconsistent or underdeveloped programs.

When it comes to measuring success, 68% of respondents use qualitative and/or quantitative metrics to assess their observability efforts, however, the remaining organizations rely on ad-hoc or no measurement at all, posing a significant risk. Without clearly defined metrics and alignment with enterprise-wide governance frameworks, organizations risk falling short of their AI objectives.

Unstructured Data is Emerging as a Key Focus

Organizations are extending their observability programs beyond structured tables to include semi-structured data (such as JSON or log files) and unstructured data (such as text, images, video, and sound). According to the study, 62% of organizations are exploring the use of semi-structured data, with 28% already actively using it, while 60% are currently evaluating unstructured documents. These strong adoption trends signal growing recognition of the importance of diverse data types - particularly as advanced use cases like predictive machine learning and Generative AI depend on them. Observing this data requires different observability techniques than tables, including the careful appending and tracking of object metadata.

North America Leads in AI and Observability Maturity 

Compared to Europe, North American firms report significantly higher AI adoption rates and observability maturity. An average of 88% of North American organizations have formalized observability programs across disciplines, compared to just 47% in Europe. North American firms also place greater emphasis on regulatory compliance and data privacy, despite the absence of federal AI regulations comparable to the EU's AI Act. In addition, North Americans place a higher priority than Europeans on model accuracy and twice as many of them have formal observability measurements in place.

"As AI and the emergence of agentic use cases raise the risks and rewards of analytics, data teams are solidifying their observability programs to strengthen data governance and quality," said Cameron Ogden, Senior Vice President – Product Management at Precisely. "The research reinforces that observability is not simply a nice-to-have but is a foundational capability for ensuring the integrity of enterprise data – particularly when it comes to fueling AI models for trustworthy and scalable outcomes."

Download a copy of the full Observability for AI Innovation report to learn more.

Methodology

The Observability for AI Innovation survey was conducted by BARC and sponsored by Precisely and Collibra. The study collected responses from 264 data and AI stakeholders across industries, including IT, manufacturing, financial services, and retail. Respondents included data engineers, data scientists, C-level executives, and business process owners, providing a comprehensive view of observability adoption, challenges, and best practices.

About BARC

BARC (Business Application Research Centre) is one of Europe's leading analyst firms for business software, focusing on the areas of data, business intelligence (BI) and analytics, enterprise content management (ECM), customer relationship management (CRM) and enterprise resource planning (ERP). Learn more at https://barc.de/

About Precisely

As a global leader in data integrity, Precisely ensures that your data is accurate, consistent, and contextual. Our portfolio, including the Precisely Data Integrity Suite, helps integrate your data, improve data quality, govern data usage, geocode and analyze location data, and enrich with complementary datasets for confident business decisions. Over 12,000 organizations in more than 100 countries, including 93 of the Fortune 100, trust Precisely software, data, and strategy services to power AI, automation, and analytics initiatives. Learn more at www.precisely.com.

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SOURCE Precisely