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‍ Artificial Intelligence is unequivocally becoming the essential driver of business growth, a mandate clearly expressed by the market. But if you’re a U.S.-based enterprise leader, you know the reality feels a lot messier than the headlines suggest. Everyone is talking about AI transformation, but for many, it turns into a maze of complex data science, over-budget projects, and Proofs of Concept (PoCs) that never make it to production.

While AI is revolutionizing the future of nearly every industry, it’s also created a unique set of challenges and liabilities that will need to be addressed as the area grows. Enter AI governance: a set of rules and best practices to ensure that AI is used effectively, securely, and responsibly. But what exactly does that mean, and why is it so crucial for businesses?

The performance of AI applications depends on its underlying infrastructure. Whether its fine-tuning custom models, performing real-time inference, deploying AI agents, AI workloads require high-performance hardware like Nvidia GPUs or next-gen AI accelerators from Tenstorrent. On top of performance, efficiently running AI workloads in production and at scale is a challenge.

Another year is wrapping up, and we’re taking a moment to reflect on what made 2025 a defining year for Kong. With major advances in building the AI connectivity layer and soaring enterprise adoption of agentic systems, this year sparked a hockey-stick surge in demand for the infrastructure that powers intelligent agents. Below is a rundown on the updates, the innovations, and the moments that moved the industry in one year-end recap.