Riverbed announced new findings from its global survey, The Future of IT Operations in the AI Era, highlighting how Financial Services organizations are progressing with AI adoption. The report focuses on AI readiness in Financial Services and reveals a growing gap between AI ambition and real-world implementation across the sector.

According to the survey, 92% of Financial Services decision-makers reported that improving data quality is critical to AI success. However, progress remains uneven. Only 12% of AI initiatives have reached full enterprise-wide deployment, while 62% remain in pilot or development stages. This underscores the challenges of operationalizing AI in a highly regulated and risk-sensitive environment.

Despite these challenges, confidence in AI remains strong. The report revealed that 89% of Financial Services organizations said returns from AIOps investments have met or exceeded expectations. In addition, 62% reported high confidence in their overall AI strategy. Even so, data readiness, operational complexity, and scaling AI beyond pilots continue to slow adoption.

Riverbed also reported that only 40% of Financial Services organizations feel fully prepared to operationalize AI today. Data quality remains a key barrier, as just 43% expressed full confidence in the accuracy and completeness of their organizational data. As a result, many AI initiatives struggle to move from proof-of-concept to production.

The study further revealed that IT complexity is driving organizations to simplify operations. On average, Financial Services IT teams use 13 observability tools from nine vendors. Consequently, 96% are consolidating tools and vendors, while 95% said a unified observability platform would make it easier to detect and resolve operational issues. Notably, 95% are considering new vendors as part of this effort.

Unified communications performance also emerged as a critical issue. Employees in Financial Services spend 41% of their workweek using UC tools. However, only 47% reported being very satisfied with performance. UC-related issues account for 16% of IT tickets and take an average of 41 minutes to resolve, impacting productivity and customer experience.

The report highlighted strong adoption of OpenTelemetry across Financial Services. About 92% of organizations are already using the framework. Additionally, 96% said cross-domain data correlation is critical, while 99% agreed that OpenTelemetry reduces vendor lock-in and improves flexibility. Most respondents also view it as a foundation for future AI-driven automation.

As AI initiatives mature, attention is shifting toward data movement and network performance. Riverbed reported that 94% of Financial Services organizations consider AI data movement important to their AI strategy, with 37% calling it critical. Network performance and security were cited as essential by 81% of respondents, the highest across all industries surveyed.

Looking ahead, 76% of Financial Services organizations plan to establish an AI data repository strategy by 2028, signaling a push toward governed, high-performance architectures that support AI at scale while meeting compliance requirements.

Key takeaways:

• Financial Services organizations show strong confidence in AI value but face deployment gaps
• Tool consolidation and unified observability are accelerating across IT operations
• OpenTelemetry and network performance are central to scaling AI securely and effectively

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