Riverbed, the leader in AIOps for observability, today announced the results of the Riverbed Global Survey on ‘The Future of IT Operations in the AI Era’, which found that organisations are highly committed to AI adoption and are strategically transforming IT operations to support AI. However, the research reveals that while organisations have nearly doubled their overall AI investments and 87% report that the ROI on their AIOps initiatives has met or exceeded expectations, only 12% of AI projects have reached full enterprise-wide deployment.*
Organisations report that they face several significant barriers to AI implementation. The majority are not fully prepared to roll out AI projects, with challenges including persistent issues with data quality and a gap between leadership optimism and the technical realities of implementation. In search of practical, AI-powered solutions, organisations are aggressively consolidating tools and vendors across IT operations, adopting a unified platform, moving to open standards, navigating issues with unified communications, and addressing the challenges of AI data movement across IT infrastructure.
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We found that as organisations move towards AI readiness, IT operations are transforming in consistent ways across countries and industries. The IT marketplace is changing as 93% of businesses consider switching vendors in order to consolidate tools. The new realities of today’s workplace mean that performance of unified communications has become critical and key focus with leaders and practitioners spending on average 42% of their work week using these tools. Data challenges mean that leadership are increasingly committed to the open-source observability framework OpenTelemetry. Additionally, IT departments are seeing more AI data residing in public cloud and edge environments as they prepare for enterprise-wide AI deployment.
The global survey surveyed 1,200 business decision-makers, IT leaders, and technical specialists across seven countries and a range of industries, providing a comprehensive overview of how organisations are implementing AI across IT operations, including how they are addressing challenges, deploying tools, adopting standards, and devising strategies for success. The survey explores: gaps in AI adoption and strategies for success; changes in the deployment of observability tools; the current state of unified communications tools; OpenTelemetry framework adoption; and data infrastructure for AI.
“Companies are investing heavily in AI for IT because they understand the potential it has to transform operations in today’s working world,” said Jim Gargan, Chief Marketing Officer, at Riverbed. “However, our research shows that enterprises face several significant challenges as they attempt to move from the early stages of implementation to practical AI solutions that deliver a strong return on investment. Across the globe, Riverbed is helping organisations to improve user experiences and IT operations with safe, secure, and accurate AI. We’re focusing on what our customers need: full support for AIOps; a solution to the data gap with observability across all of IT; and fast, agile, secure AI data acceleration.”
Enterprises are seeing three key barriers to AI implementation
Organisations are nearly doubling their investment in AI to $27 million (from $14.7 million in 2024) and 87% report that their return on investment from AIOps initiatives is in line with their expectations or better than they hoped. However, companies must address three gaps: in readiness, data quality, and realistic expectations (the ‘reality gap’).
- Companies are not ready for AI: only 12% of AI projects have been fully deployed, and just 36% of organisations consider themselves ready to operationalise AI, down from 37% last year.
- Organisations face significant challenges in data quality, a foundational issue for AI success. While 88% agree that data quality is important, only 46% are fully confident in the accuracy and completeness of their data as they prepare to implement AI. In reality, most enterprises admit their data isn’t ready, with just 34% rating their data as excellent for relevance and suitability, 35% for consistency and standardisation, 37% for security and protection.
- Leaders are more optimistic than technical specialists: 42% of leaders but only 25% of specialists say their organisation is fully prepared to implement AI projects today.
To unlock the full potential of AI, organisations need more than increased investment – they must close the readiness gap, elevate data quality, and align expectations between leadership and technical teams.
Organisations lack visibility into applications and systems performance
As companies set out to complete the implementation of AI projects, they seek visibility into system performance and data. Currently, organisations deploy an average of 13 observability tools supplied by 9 vendors, equating to one or two tools per vendor for each type of observability. The vast majority (96%) of organisations are consolidating the number of tools and vendors they utilise across ITOps and 93% say that a unified platform would make it easier to identify and resolve operational issues. A key driver is the need to improve productivity, which is considered even more important than the desire to reduce costs.
Unified communications tools are central to operations
The research found that business leaders are much more confident than technical experts about AI implementation. To address this reality gap, it’s important for executives and experts to get aligned on AI projects. There should be no barriers to collaboration across companies orchestrating an AI roll-out and seamless communication is essential. However, 43% of organisations report performance issues with unified communications tools such as video calls, messaging platforms, and collaborative workspaces.
In a post-2020 working world, this is a significant issue. Employees spend 42% of their work week using UC tools, and 65% of organisations state that they are essential to operating effectively. But at present, the survey data suggests that UC-related issues may be the primary source of helpdesk tickets across organisations. These tickets take an average of 43 minutes to resolve, and one in five takes over an hour.
An observability framework that’s changing everything
As companies seek to improve visibility across decentralised systems in preparation for AI implementation, we found that 88% have begun to implement OpenTelemetry (OTel), an observability framework used to standardise data collection across systems. 41% have fully implemented OTel and 47% are making progress in adopting it. 95% state that the ability to standardise data across applications, infrastructure, and user experience is critical to their observability strategy.
Nine out of ten companies (94%) say that OTel is a stepping stone to projects such as AI-driven automation. Over half (57%) expect that the framework will be widely adopted within the next two years. 36% agree that OTel is already mandated within their enterprise. However, we see a perception gap between business leaders and technical specialists: 41% of leaders believe that OTel is mandated in their organisation in contrast with only 27% of technical specialists.
Data movement is central to AI strategies
Nine in ten enterprises (91%) view the movement and sharing of AI data as important to their AI strategy – with one in three (33%) describing it as critical, foundational to how they design and execute AI.
- Businesses are storing 36% of their AI-related data in the public cloud, but by 2028 they expect this to be 39%
- Organisations say that private cloud data storage will drop from 25% to 21% by 2028
- They predict that storage in on-premises data centres will drop from 23% to 17% by 2028
- AI-related data storage in edge computing environments is expected to grow from 9% to 13% in 2028
- AI-related data storage in co-location facilities is expected to rise from 7% to 10% in 2028
- Three quarters of organisations plan to establish an AI data repository strategy by 2028
As the AI data landscape moves to more distributed environments, companies report that the top three considerations are the cost of data movement and storage (95%), security and compliance (94%), and network performance and reliability (94%). For 78% of survey respondents (and 81% of business leaders) network performance and security are critical success factors of their AI strategy.
The Riverbed Global Survey on the Future of IT Operations in the AI Era polled 1,200 business decision-makers, IT leaders, and technical specialists across seven countries, with an average of $2.2 billion in annual revenue. Key industries included manufacturing, financial services, government and public sector, and healthcare providers, among others. The survey was conducted by Coleman Parkes Research in July 2025.
To view the complete findings, download the full report here.