DEVOPSdigest

Generative AI (GenAI) is a clear priority for organizations — a survey conducted by Couchbase of 500 IT decision makers found that almost all respondents have specific goals to use it in 2024. As organizations prepare for GenAI's rapid growth, they are facing critical questions:

Can their data infrastructure and application architectures handle it?

And how can developers use GenAI to build and improve applications that give users the adaptive, personalized experiences they expect?

Developers are under immense pressure to ship innovations quickly. Yet, they often lack the necessary resources to bring their ideas to life. A modern data management strategy is important — one that not only addresses the challenges posed by AI but empowers developer teams to create leading products and applications.

To address these challenges, organizations are increasing investment in digital modernization. According to the survey, investment in digital modernization is expected to increase by 27% from $28 million in 2023 to $35.5 million per enterprise this year.

Organizations Are Unprepared for GenAI Data Demands

Legacy technology isn't built to support many of the intricacies of GenAI. Developers will struggle to meet customer demands and modernization goals if they don't have the right infrastructure and tools in place. Four in ten (42%) organizations cited the reliance on legacy technology as an issue preventing them from pursuing new projects. Overall, a majority of IT decision makers are worried their organizations' ability to manage data will not meet GenAI demands without significant investment.

The survey found a surprising number of enterprises lack numerous capabilities that enable organizations to modernize, which could lead to them falling behind competitively, unable to deliver applications that customers want:

■ Only 46% of enterprises have complete control over data storage, access and usage.

■ Nearly 7 in ten (69%) enterprises do not have a consolidated database architecture, increasing the risk of applications reading or writing duplicate copies of data and fragmenting the ability to gather data for RAG use cases.

■ Only 25% of enterprises have a high-performance database that can manage unstructured data.

■ Most enterprises (82%) do not yet have a vector database that can store, manage and index vector data efficiently.

■ 60% of IT decision makers are worried about ensuring their organization has sufficient compute power and data center infrastructure to support GenAI.

The Impact of IT Shortcomings on Developers

GenAI tools have the power to increase developer productivity, help them stay up to date and enable more testing and iterating of code to create applications more quickly. However, every organization (100%) said their development team encountered issues when using GenAI tools to support their work creating new applications. Without the right tools to manage GenAI safely and effectively, developers could lose out on an opportunity to do more with less.

Current IT infrastructures that cannot support GenAI applications running in-house are already costing organizations an average of $4 million dollars per year due to failed, delayed, or scaled-back projects. Every single enterprise cited they have been prevented from pursuing a new digital service or other IT modernization project because of issues with technology, resources or organizational buy-in.

Additionally, a concerning 63% of organizations have suffered delays longer than three months because of IT modernization issues. These challenges emphasize the need for a data strategy that delivers more flexible computing power (i.e., edge computing), high-speed access to data and the ability to query it in real time, control over data storage and a consolidated database architecture. Developers will require a significant investment in such tools to successfully deliver applications and products that customers desire.

Harnessing AI for Productivity

AI's ability to support accurate, intelligent automation can address productivity challenges for developers and end users alike. AI-powered coding tools can accelerate the development process, which could be a reason 93% of enterprises are investing in GenAI. Plus, 73% of enterprises are increasing investment in AI tools to help developers work more effectively and bring GenAI to their applications.

Embracing Multipurpose Databases for GenAI Success

As GenAI demands continue to soar, organizations should recognize the critical role of a modern multipurpose database in creating and supporting AI applications. A multipurpose database can offer data access flexibility, vector search, edge computing capabilities, scalability and real-time analytics support, giving enterprises a significant advantage in their GenAI ambitions. By applying data management strategies to enable high-speed data analytics and processing capabilities required for AI, organizations will be well-positioned to benefit from GenAI's full potential.