Couchbase’s seventh annual survey of global IT leaders sheds light on a rising trend: the increasing role of artificial intelligence (AI) in IT modernization efforts. With AI-driven tools, particularly generative AI (GenAI), transforming how enterprises approach productivity and innovation, IT modernization spending is set to rise by nearly 30% in 2024. This significant increase highlights the pressures organizations face to adopt new technologies and meet the evolving demands of end users. However, this modernization surge is also fraught with challenges, particularly in data management, as companies struggle to establish robust strategies to support GenAI’s data demands. Below, we examine the survey’s findings and explore how organizations can navigate the complexities of AI-driven modernization.
1. Increasing Investment in IT Modernization and AI
According to Couchbase’s survey, enterprises plan to increase their IT modernization budgets by 27% in 2024, with an average spend of $35.5 million. A large share of this budget is directed toward AI initiatives, with companies spending an average of $21 million on AI in 2023-24 and $6.7 million specifically on GenAI. The reasons for this targeted spending are clear: AI enables rapid prototyping, helps employees work more efficiently, and allows businesses to capitalize on emerging trends. For example, AI-driven applications can enhance customer service by quickly processing vast datasets to provide personalized responses or detect patterns that humans might miss.
Yet, while companies are investing heavily in AI to drive productivity, Couchbase’s report highlights that many are unprepared for the data infrastructure demands that come with it. With 59% of surveyed leaders expressing concern over their organizations’ ability to manage data effectively, there is a growing recognition that AI’s potential can only be fully realized with a strong data strategy in place. This tension between investment and capability underscores the critical need for businesses to align their data management systems with their AI ambitions to avoid wasted resources and missed opportunities.
2. The Data Management Struggle for GenAI
The advent of GenAI has placed unprecedented demands on data infrastructure, requiring organizations to rethink their data management strategies. However, only 18% of surveyed enterprises currently possess a vector database capable of efficiently storing, managing, and indexing vector data—an essential component for optimizing GenAI performance. Without these capabilities, businesses may find that their AI applications are slower, less accurate, and more costly to run. Furthermore, 54% of companies lack a comprehensive data strategy to support GenAI, a gap that could stymie productivity gains and lead to costly project delays.
To meet GenAI’s data demands, enterprises must adopt advanced data solutions that provide real-time access, control, and consolidation of data storage. For example, a unified data infrastructure reduces the risks associated with fragmented data storage, where applications may pull from multiple sources, leading to inconsistencies. Businesses that fail to invest in these capabilities could experience the consequences directly; Couchbase’s survey indicates that such gaps in data infrastructure result in an average of $4 million in wasted investments each year, along with an 18-week delay in strategic project timelines.
3. The Cost of Legacy Technology on Modernization Efforts
Despite the push towards modernization, many enterprises continue to rely on legacy technology that cannot support modern digital requirements. This reliance not only hampers the deployment of new initiatives but also increases the likelihood of project delays or failures. Couchbase’s survey reveals that outdated systems contribute significantly to wasted investments, with organizations losing an average of $4 million annually due to stalled or scaled-back modernization projects. These findings underscore the hidden costs of outdated infrastructure in an era where agility and adaptability are crucial.
Legacy technology also has implications for data security and compliance, as older systems may lack the robustness needed to protect sensitive data in complex, AI-driven environments. The financial impact of legacy technology extends beyond immediate losses, contributing to long-term inefficiencies that make it challenging for organizations to stay competitive. Moving forward, businesses must prioritize phasing out outdated systems and investing in modern, flexible infrastructure to support their evolving needs and fully harness AI’s transformative potential.
4. The Pressure to Achieve More with Less
The survey reveals that 71% of IT departments are under mounting pressure to “do more with less,” with enterprises needing to increase productivity by 33% annually just to remain competitive. GenAI and other AI-driven applications offer promising solutions to meet this productivity challenge, enabling businesses to streamline operations, enhance decision-making, and provide more responsive customer service. However, as Couchbase’s report points out, many organizations are rushing into GenAI without fully understanding the resources required to use it effectively and safely.
The pressure to quickly implement AI has led 26% of enterprises to divert resources from other critical areas, including IT support and security, to meet AI objectives. This reallocation of funds can leave organizations vulnerable, as underfunded IT support may lead to lower system resilience, while reduced security investment can increase the risk of data breaches. Couchbase’s survey underscores the importance of balanced investment: while AI offers considerable productivity gains, companies must avoid compromising other critical functions. A comprehensive approach to IT modernization should ensure that all aspects of infrastructure are adequately supported to enable sustainable growth.
5. Investing in Adaptable and Efficient Infrastructure
As organizations scale their AI initiatives, many are questioning whether their current infrastructure can support GenAI’s high processing and storage demands. According to the survey, 60% of respondents are concerned about having sufficient compute power and data center infrastructure for GenAI applications, while 61% say corporate social responsibility (CSR) considerations limit their ability to adopt GenAI fully without energy-efficient infrastructure. Additionally, 66% of IT leaders believe they would need to invest in multiple databases to meet GenAI’s diverse requirements, although modern multipurpose databases could streamline data management and reduce costs.
Investing in adaptable, efficient infrastructure will be essential for enterprises seeking to balance the demands of GenAI with CSR goals. An optimized, multipurpose database infrastructure, for instance, can support various applications while reducing latency and energy consumption. In the words of Couchbase’s SVP of product, Matt McDonough, “An adaptive application that can use GenAI to enhance a specific end-user experience will be equally effective while also having a much faster time to market.” For businesses aiming to remain competitive and socially responsible, an investment in adaptable infrastructure offers a clear path forward, enabling sustainable and responsive digital transformation.
Conclusion
The rapid adoption of AI technologies like GenAI represents both an opportunity and a challenge for organizations. Couchbase’s survey reveals that while businesses are investing heavily in IT modernization, many are struggling to build the necessary data infrastructure to support their AI ambitions. With $4 million wasted each year due to inadequate modernization efforts and an average delay of 18 weeks in strategic projects, the importance of a strong data strategy cannot be overstated. Enterprises must prioritize investments in adaptable, efficient infrastructure to unlock AI’s full potential, ensuring they meet end-user expectations and remain competitive in an increasingly digital world.
This comprehensive analysis of Couchbase’s survey findings provides actionable insights for organizations as they navigate the complexities of IT modernization, highlighting the need for balanced, data-driven strategies that support both current demands and future growth.
