77 into search engines – they’re asking Copilot, ChatGPT or enterprise agents to find, summarise and act on information. This shift demands a new approach to content strategy. Organisations must optimise AI accessibility, not just human readability. That means structuring content semantically for machine parsing, using metadata and schema markup to enhance discoverability, and ensuring content is context-rich and action-oriented. The implications are profound. AI agents will favour content that is authoritative, wellstructured and aligned with user intent, not necessarily what ranks highest on online search engines like Google. As a result, marketing, documentation and knowledge management teams must rethink how they create and distribute information. Microsoft is uniquely positioned to lead this transformation. Through its Copilot ecosystem, Azure AI services and agentic frameworks like Agent Builder and Magentic-One, Microsoft is enabling organisations to build and deploy custom AI agents tailored to business needs, govern enterprise data to ensure safe and effective AI use, and accelerate adoption through change management and training. As AI continues to evolve beyond the realms of generative and agentic AI, a new wave of specialised AI paradigms is emerging with unique capabilities and applications. AI comes in many forms: predictive, discriminative, casual, symbolic, embodied and neurosymbolic. While causal and neurosymbolic AI offer exciting possibilities for deeper reasoning and explainability, they are still in early stages of development. Embodied and agentic AI promise autonomy but face challenges in safety, cost and complexity. Ethical AI is essential but functions more as a framework than a standalone technology. Among these, predictive AI stands out as the most likely candidate to Microsoft tools like Magentic-One, which features one loop for containing data and another loop for tracking tasks, are helping businesses to implement agentic AI Source: Microsoft
RkJQdWJsaXNoZXIy NzQ1NTk=