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• Survey Scope and Context

  • A total of 10,000+ leaders participated, evenly split between 5,540 analytics/IT decision makers and 5,540 business leaders worldwide.

  • The survey spanned North America, Latin America, Asia-Pacific, and Europe, capturing diverse industries, from technology and manufacturing to finance and retail.

  • Data was collected between June 16 and July 31, 2023, focusing on data management, analytics utilization, and the effects of rapid AI advancements.

• AI’s Mounting Influence

  • 92% of analytics/IT leaders say trustworthy data is more important than ever.

  • 86% agree that AI’s outputs can only be as good as its data inputs, placing pressure on data teams to ensure accuracy and completeness.

  • 87% of these technical leaders say that advances in AI make data management a high priority right now.

• Generative AI’s Emerging Role

  • 91% of business leaders believe generative AI would significantly benefit their organizations.

  • However, 77% of business leaders worry they are missing out on AI’s potential, with 88% of marketing leaders most concerned about falling behind.

  • Over half of IT leaders cite the need for accurate, complete, and unified data as central to generative AI success.

• Data Maturity and Readiness

  • More than one-third of analytics/IT leaders consider their organizations “best-in-class” in terms of data maturity.

  • Only 6% rate themselves as below or far below standard.

  • High-maturity organizations are twice as likely as low-maturity peers to say they have sufficient data quality for AI initiatives.

• Security Threats and Other Challenges

  • 94% of business leaders believe they’re not extracting enough value from their data.

  • Both business and technical respondents name security threats as the #1 barrier to effective data management.

  • 78% of analytics/IT leaders admit difficulty in using data to drive strategic priorities.

  • Nearly half of analytics/IT leaders have only partial or no visibility into data usage within their organizations.

• Misalignment Between Data and Business Goals

  • 41% of line-of-business leaders and 37% of analytics/IT leaders see data strategies that are only partially or not at all linked to business objectives.

  • Fewer than one-third of analytics/IT leaders measure the value of data monetization; over 60% don’t track how quickly teams access insights.

• Soaring Data Volumes

  • Over two-thirds of analytics/IT leaders expect data volumes to increase in the next 12 months, with 22% average growth anticipated.

  • They forecast a similar surge across multiple data sources (e.g., first-party, third-party, device, API data), complicating efforts to harmonize data.

• Bolstering Data Culture

  • 78% of analytics/IT leaders cite an underdeveloped data culture as a key obstacle, in addition to privacy and security concerns.

  • 70%+ plan to increase investments in data analytics tools and training to boost adoption and user confidence.

  • Leaders with higher data maturity often use data governance frameworks to ensure quality, foster trust, and democratize data access.

• Data Governance’s Multi-Faceted Role

  • 85% use governance to guarantee baseline data quality.

  • 86% of high-maturity organizations deploy governance to expand data access (versus 70% in low-maturity groups).

  • Other uses include ensuring privacy compliance, providing ethical guidelines, and setting clear accountability for data stakeholders.

• Cloud Migration for Flexibility

  • Nearly three-quarters of analytics/IT leaders have moved or are in the process of moving applications to the cloud, or started there from the beginning.

  • Their top reasons:

    1. Simplified IT management

    2. Stronger security

    3. Greater flexibility

    4. Scalability

    5. Room for innovation

• Future Outlook

  • Analytics/IT leaders want data platforms with AI capabilities, fast deployment, and intuitive interfaces for business users.

  • 96% of business leaders say data and analytics improve decision-making—if insights are accessible and accurate.

  • Companies that excel in data quality, governance, and culture will be best positioned to capitalize on AI—from generative content to predictive analytics—ultimately driving faster decisions, efficiency gains, and enhanced customer experiences.