Operations | Monitoring | ITSM | DevOps | Cloud

As we move further into 2025, the distinction between digital transformation and AI transformation is blurring. According to Gartner, 33% of enterprise software applications will incorporate Agentic AI by 2028, signaling the rapid mainstream adoption of this technology. While digital transformation laid the groundwork for modernization, a new paradigm is emerging: Agentic AI. This revolutionary approach to artificial intelligence is reshaping how businesses operate, make decisions, and deliver value.

Over the last 9 months, we’ve been building some of the most ambitious AI-native features in our product. Agents that can investigate incidents in real time. Systems that identify likely root causes. AI that writes exec-ready summaries without being prompted. Natural language interfaces that let engineers ask questions like “what changed before this broke?” and get useful answers. To do this, we had to fundamentally re-evaluate how we built AI products at incident.io.

Are you using AI to inform or guide your pricing strategy? It offers concrete financial benefits thanks to three (exclusive) capabilities: granular demand forecasting, advanced price elasticity modeling, and dynamic markdown optimization. Could a human do these things? With enough time…maybe. But why wait that long? There are significant margin and revenue improvement opportunities right now. With AI, you can seize them immediately. Traditional pricing models make it nearly impossible to see gains.

The way software is written is changing fast. In the past few years, AI coding assistants and large language models (LLMs) have gone from novelty to necessity for many developers. Tools like Cursor, ChatGPT, and custom in-house models are helping teams generate boilerplate, scaffold features, and even build entire apps within minutes. It’s exciting. But it also raises the stakes. When code is written faster, it’s deployed faster.