#USA #Generative AI #San Francisco #Kong Inc #LLM Adoption

Rise in Enterprise Investment on Generative AI

A recent report from Kong Inc. highlights that a substantial 72% of enterprises are poised to boost their investment in generative AI technologies in 2025. The survey, encompassing insights from IT leaders, software developers, and engineers, uncovers a landscape ripe for innovation, yet fraught with challenges.

With 44% of respondents pinpointing governance and security as significant barriers to the adoption of large language models (LLMs), the need for robust infrastructure becomes ever more critical. As Marco Palladino, CTO of Kong Inc., notes, "Organizations that can keep up with the fast pace of AI adoption will hold a competitive edge." Companies are expected to invest heavily, with nearly 40% indicating budgets above $250,000 this year alone.

Current Landscape of Generative AI Usage

Diving into the technology landscape, the report reveals that OpenAI's models were the predominant choice in 2024, but a notable shift occurred in the first quarter of 2025. Google’s generative models surged to a usage rate of 69%, interestingly shifting enterprise preferences, with only 55% reporting usage of OpenAI models within the same timeframe. Other models from Meta and IBM follow at 38% and 26%, respectively.

This change indicates Google's accelerated advancements in AI, particularly within developer circles aimed at enhancing productivity through automation. Developers are increasingly leveraging generative AI in coding tasks, documentation generation, and even in testing application programming interfaces (APIs).

Emerging Concerns

The report also sheds light on the entry of new players like DeepSeek, which, although popular—80% of respondents showed interest—has raised privacy concerns, with 68% of non-users citing these reasons for their hesitance, alongside 46% acknowledging internal restrictions against its use.

Challenges on the Horizon

Despite the positive outlook for generative AI, enterprises face critical challenges to broader adoption. The persistent worries about data privacy and security are front and center, affecting 44% of respondents. Additionally, cost remains a significant hurdle, as deploying LLMs entails considerable investments, both in cloud resources and the necessary ongoing updates to ensure operational relevance. The technical difficulty of integrating these models into existing systems further complicates the process, acknowledged by 14% of enterprises.

Interestingly, developer sentiment towards generative AI is gradually improving; 46% consider it a vital productivity enhancement tool as companies utilize AI to streamline repetitive tasks, expedite content creation, and assist in comprehensive data analyses.

Key Insights from the Report

The report encapsulates several critical findings that underscore the current trends in AI adoption:

• - Security and data privacy compliance emerged as the top criteria for selecting an LLM provider, noted by 31% of respondents.
• - A significant number, 63%, utilize paid enterprise versions of LLMs, contrasting with only 17% relying on free versions.
• - AI-powered chatbots (27%) and tools for developer productivity (26%) rank as the predominant applications of LLM technology.
• - Open source LLMs are perceived as superior by 51% of respondents, while 37% advocate for a hybrid model balancing proprietary and open-source options.
• - The top platforms for LLM deployment over the last three months have been Microsoft Azure AI (45%), followed by OpenAI Platform (41%) and Google Vertex AI (35%).

The findings in this report underscore a rapidly evolving landscape where enterprises are keen to harness the power of generative AI, despite the hurdles they may face. This anticipated increase in spending highlights the urgency for businesses to adopt AI technologies to remain competitive in a rapidly shifting technological environment.