Enterprises That Fall Behind in AI Race Risk $87 Million Annual Loss, Couchbase Survey Reveals
Rhea-AI Summary
Couchbase (NASDAQ: BASE) released its eighth annual global IT survey revealing significant AI adoption challenges and opportunities. The study of 800 senior IT decision-makers found that enterprises failing to effectively implement AI risk losing 8.6% of monthly revenue, averaging $87 million annually per company.
Key findings show that 21% of enterprises have insufficient AI control, while 70% admit incomplete understanding of AI data requirements. AI investment is set to surge by 51% in 2025-2026, with spending equally distributed across agentic AI (30%), GenAI (35%), and other AI forms (35%). The survey highlighted that 99% of enterprises face AI project disruptions, resulting in 17% wasted AI investment and average six-month delays in strategic goals.
Positive
- None.
Negative
- 21% of enterprises have zero or insufficient AI control
- 70% admit incomplete understanding of AI data requirements
- Average potential revenue loss of $87 million annually for companies failing in AI adoption
- 99% of enterprises face AI project disruptions, wasting 17% of AI investment
- 75% have multi-database architecture hampering AI output consistency
- 61% lack tools to prevent external sharing of proprietary data
News Market Reaction 1 Alert
On the day this news was published, BASE declined 0.04%, reflecting a mild negative market reaction.
Data tracked by StockTitan Argus on the day of publication.
The stakes are high, with
"The evolution from GenAI to agentic AI is creating vast opportunities for enterprises that can harness these technologies effectively," said Julie Irish, Chief Information Officer at Couchbase. "Creating and operating innovative AI applications at scale is essential for successful enterprises. The right data strategy, including methods to ensure high data quality, scalability and accessibility, is more important than ever to ensure companies unlock the value of AI."
Key findings include:
- Falling behind the AI wave has significant consequences:
99% of enterprises have encountered issues that disrupted AI projects or prevented them outright, including problems accessing or managing the required data; perception that the risk of failure had become too high; and an inability to stay on budget. These issues had real consequences, eating up17% of AI investment and setting strategic goals back by six months on average. - Closing the data understanding gap is key to control:
70% of enterprises admit their understanding of the data (e.g., the quality and real-time accessibility of data) needed to power AI is "incomplete," contributing to62% not fully understanding where they are at risk from AI (e.g., through security or data management issues). Conversely, those with greater understanding are more confident, and are33% more likely to be prepared for agentic AI. - Data architecture is evolving and requires consolidation: The right data architecture is crucial for AI. Yet enterprises say their current architecture has an average lifespan of 18 months before it can no longer support in-house AI applications.
75% of enterprises have a multi-database architecture, which makes it more difficult to ensure accurate, consistent AI output;61% do not have the tools to prevent proprietary data from being shared externally, which increases security and compliance risks; and84% lack the ability to store, manage and index high-dimensional vector data needed for efficient AI use. To address these challenges, all surveyed enterprises are consolidating and simplifying their AI technology stacks to make controlling AI easier and more efficient. - Encouraging experimentation contributes to AI success: Corporate attitudes about AI have a notable impact on its success. Enterprises that encourage AI experimentation have
10% more AI projects enter production and incur13% less wasted AI spend than enterprises with a more restrictive approach. - New developments in AI are rapidly reaching parity: The proportion of AI spend on agentic AI (
30% of total), GenAI (35% ) and other forms of AI (35% ) is almost even, despite agentic AI and GenAI being much newer concepts. This suggests enterprises are investing heavily in keeping up with AI development as66% worry that AI and different approaches to AI are evolving faster than their organizations can keep pace. - Inability to keep up with AI increases risk of being replaced: Enterprises recognize AI's potential for disruption, allowing smaller organizations with a better grasp of the technology to replace larger, less agile competitors. More than half (
59% ) of IT leaders are concerned that their organizations risk being replaced by smaller competitors, yet at the same time79% believe they can do the same and displace their larger competition.
"The data reveals both tremendous opportunities and significant risks presented by AI," continued Irish. "While
"A modern developer data platform is essential for enterprise AI success," added Matt McDonough, SVP of product at Couchbase. "With capabilities like vector search, integrated AI Services and support for agentic AI development, Couchbase empowers customers to develop agentic systems and applications at scale, while delivering compelling price-performance. By supporting the management of all data types involved in AI interactions, our platform helps enterprises unify AI, operational, analytical, vector and mobile workloads into a single, multipurpose architecture. This holistic approach not only enhances data visibility, control and protection, but also gives developers the tools they need to innovate with the next wave of AI technologies."
Additional Resources
- To download the full report, click here.
- To download the graphic that highlights key findings from the report, click here.
- To learn more about how organizations can fully realize the potential of agents, click here.
- To learn more about how Couchbase empowers customers to develop agentic systems and AI applications, click here.
Methodology
Couchbase commissioned an online survey, conducted in April 2025 by Coleman Parkes (https://colemanparkes.com/), an independent market research organization. 800 senior IT decision-makers, such as CIOs, CDOs and CTOs, in organizations with 1,000 employees or more in the
About Couchbase
As industries race to embrace AI, traditional database solutions fall short of rising demands for versatility, performance and affordability. Couchbase is seizing the opportunity to lead with Capella, the developer data platform architected for critical applications in our AI world. By uniting transactional, analytical, mobile and AI workloads into a seamless, fully managed solution, Couchbase empowers developers and enterprises to build and scale applications and AI agents with confidence – delivering exceptional performance, scalability and cost-efficiency from cloud to edge and everything in between. Couchbase enables organizations to unlock innovation, accelerate AI transformation and redefine customer experiences wherever they happen. Discover why Couchbase is the foundation of critical everyday applications by visiting www.couchbase.com and following us on LinkedIn and X.
Couchbase®, the Couchbase logo and the names and marks associated with Couchbase's products are trademarks of Couchbase, Inc. All other trademarks are the property of their respective owners.
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SOURCE Couchbase, Inc.