Couchbase, a cloud database platform company, has released the results of its seventh annual survey of global IT leaders.

The survey of 500 senior IT decision-makers revealed that investment in IT modernization is set to increase by 27% in 2024. Businesses are aiming to leverage new technologies like AI and edge computing while meeting growing productivity demands. There’s a clear need for modernization and tech investment: 59% of organizations are concerned that their current ability to manage data won’t meet the demands of GenAI without significant investment. With the right strategy, companies can overcome productivity challenges and meet the expectations of users who demand continually improving experiences.

Enterprises plan to spend an average of $35.5 million on IT modernization in 2024, with over a third of that amount earmarked for AI. In total, businesses are investing over $21 million in AI technologies between 2023 and 2024, with $6.7 million specifically focused on generative AI (GenAI). The main drivers for this spending are to prototype and test new ideas, improve employee efficiency, and identify new business opportunities. However, companies recognize the challenges ahead, such as ensuring AI is used effectively, having the necessary compute power, and ensuring their data center infrastructure is up to the task.

Couchbase’s SVP of product and partners, Matt McDonough, emphasized that while enterprises are entering the AI age, they have only just begun to explore its full potential. Nearly every business surveyed has specific plans to use GenAI in 2024. If used correctly, this technology could be key to addressing challenges like meeting end-user expectations and boosting productivity. However, businesses must ensure their data architecture can handle GenAI’s demands, as without access to high-quality, well-managed data, the technology could lead companies in the wrong direction.

Key findings from the survey include:

• Unprepared for data demands: 54% of companies don’t have a complete data strategy in place for GenAI. Only 18% of businesses have a vector database capable of efficiently storing, managing, and indexing vector data. To meet GenAI’s demands, businesses will need to improve data storage, access, real-time usage, and vector search capabilities, as well as consolidate their database infrastructure to prevent issues with data versions.
• Legacy technology holding back modernization: Despite increasing investment in modernization, legacy technologies are causing delays or preventing projects from moving forward. This has resulted in an average of $4 million in wasted investments each year and delays of 18 weeks on strategic projects.
• Targeted spending: Many companies are focusing their investments on AI tools. 73% are increasing their spending on AI tools to help developers work more efficiently and create GenAI applications faster. Additionally, 65% believe that edge computing will be essential for reducing latency and enabling new AI applications.
• Risks of rushing into AI: 64% of respondents believe most organizations have rushed to adopt GenAI without fully understanding what’s needed to use it effectively and safely. This haste has sometimes led to cuts in other areas, with 26% of enterprises reallocating spending from IT support, maintenance, and security to meet AI goals.
• Meeting productivity challenges: 71% of IT departments are under pressure to do more with fewer resources. To remain competitive, companies need to increase productivity by 33% year-over-year. This explains why 98% of survey respondents have set specific goals to use GenAI in 2024.
• Investing in infrastructure: 60% of respondents worry their organization lacks the compute power and data center infrastructure to support GenAI. Additionally, 61% say their corporate social responsibility and environmental goals mean they can’t fully adopt GenAI unless it’s based on more efficient infrastructure. Surprisingly, 66% of respondents believe they would need to invest in multiple databases to support GenAI, despite the availability of solutions that can meet all their needs with a single database.
• Adaptability to meet end-user demands: 61% of enterprises are under pressure to continuously improve user experiences. On average, consumer-facing applications fall behind expectations after 19 months, and employee-facing applications after 20 months. To address this, 45% of businesses believe that adaptability — the ability to modify an application’s offerings based on user needs — will be the most important feature for applications.

McDonough concluded that investing in the right data management and infrastructure architecture is crucial to unlocking GenAI’s full potential. He pointed out that businesses don’t need complex, all-encompassing applications or multiple databases to improve productivity and meet expectations. An adaptive application that uses GenAI to enhance a specific user experience can be just as effective, with a faster time to market and lower costs. A modern, multipurpose database with all the necessary functionalities can help keep architectures and expenses streamlined.