Systems | Development | Analytics | API | Testing

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.

‍ The healthcare industry stands at the cusp of a revolutionary change, driven by an emerging technology that can do more than just analyse data; it can create it. That technology is Generative AI, or GenAI, and its arrival in medicine is being hailed as the next frontier in personalised, efficient, and predictive patient care.

As organizations expand their AI initiatives, they increasingly need to provide users, be they data scientists, AI/ML engineers, researchers, or application developers, with secure access to interactive development environments such as JupyterLab, VS Code, or other internal tools.

Traditional crowdsourced testing has always promised scale, but it’s often come with headaches.

In the United States, the evolution of shopping malls is no longer just about retail, it has also become about experience, engagement, and intelligence. With more than 900 active shopping malls nationwide attracting millions of visitors annually, traditional brick-and-mortar destinations are battling shifting consumer preferences and rising digital expectations. Today’s consumers are blending browsing with dining, entertainment, socializing, and convenience-driven digital interactions.

As we close out 2025, it's time to reflect on the hard lessons learned from deploying AI agents in production environments. The promise of AI agents is compelling: autonomous systems that can handle complex tasks, make intelligent decisions, and execute actions on our behalf. But as several high-profile incidents this year have starkly demonstrated, this autonomy comes with unprecedented risks when proper identity and access management controls are absent.

The landscape of software development is undergoing a profound transformation. We are witnessing a collision between unprecedented development speed and spiraling architectural complexity. According to the 2024 Global DevSecOps Report by GitLab, 69% of Global CxOs report that their organizations are shipping software at least twice as fast as they did a year ago.

Every technology cycle comes with hype, backlash, and eventually… utility. AI is shaping up to be no different. As we head into 2026, the conversation is already shifting from “AI will replace everything” to “why isn’t this paying off yet?” This shift is heavily influenced by evolving market trends, as businesses and technologists respond to changes in customer behavior, operational patterns, and broader market conditions that shape expectations around AI.