AI drives 27% rise in IT spend but firms lack data strategy

Couchbase, a cloud database platform company, has unveiled the findings from its seventh annual survey of global IT leaders. The survey, encompassing 500 senior IT decision-makers, indicates a notable 27% increase in IT modernisation spending for 2024. This surge is attributed to enterprises eager to leverage new technologies like AI and edge computing while addressing escalating productivity demands. However, 59% of these enterprises harbour concerns that their data management capabilities will fall short of meeting Generative AI (GenAI) demands without significant investments.

Enterprises are not just planning expenditure increases; they anticipate spending an average of $35.5 million on IT modernisation in 2024. Crucially, more than a third of this investment is targeted towards AI, with enterprises dedicating over $21 million in 2023-24, including $6.7 million specifically for GenAI. The motivations behind these expenditures are underscored by the need to rapidly prototype and test new ideas, enhance employee efficiency, and identify emerging business trends.

Despite these efforts, challenges abound. "Enterprises have entered the AI age, but so far are only scratching the surface," stated Matt McDonough, SVP of Product and Partners at Couchbase. "Almost every enterprise we surveyed has specific goals to use GenAI in 2024, and if used correctly this technology will be key to managing the challenges facing organisations."

The survey highlights several critical findings:

Unprepared for Data Demands: A significant 54% of enterprises lack a comprehensive data strategy suitable for GenAI. Only 18% possess a vector database capable of efficiently storing, managing, and indexing vector data. Essential capabilities like real-time data access, efficient vector search, and consolidated database infrastructure are identified as crucial elements in developing a strategy to support GenAI’s data demands.

Reliance on Legacy Technology: Despite increased investment in modernisation, dependence on legacy technology is causing project failures, delays, or scaling back. This results in an average annual waste of $4 million and an 18-week delay on strategic projects.

Targeted Spending: Survey respondents are acutely aware of how investment can augment their GenAI capabilities. 73% are increasing investment in AI tools to expedite GenAI application development, while 65% believe edge computing is critical for enabling new AI applications.

The Dangers of Rushing into AI: A concerning 64% of respondents feel organisations have rushed into GenAI adoption without a fundamental understanding of its safe and effective use. Alarmingly, 26% have redirected funds from areas like IT support and security to meet AI objectives.

Meeting the Productivity Challenge: IT departments are under immense pressure to enhance productivity by 33% year-on-year, with 71% reporting increasing demands to accomplish more with fewer resources. Consequently, 98% of respondents have set specific goals to integrate GenAI by 2024.

Investing in Infrastructure: 60% of respondents are concerned about their organisation's compute power and data centre infrastructure sufficiency to support GenAI. Meanwhile, 61% cite corporate social responsibility and environmental concerns as barriers to fully adopting GenAI.

Adaptability Key to Meeting End-User Demands: With 61% of enterprises under pressure to continually enhance end-user experiences, adaptability in applications is paramount. 45% identified the ability to alter what an application offers users as essential.

"Investing in the right data management and infrastructure architecture will help unlock GenAI’s transformative potential," concluded McDonough. He highlighted that organisations do not need vast, complex applications to meet user expectations or costly, multiple databases to support their needs. An adaptive application, coupled with a modern multipurpose database, can streamline costs and accelerate time to market while enhancing end-user experiences.