Sinch Agentic AI

  Conversations rarely reside in a single channel. A service request may be filed first on WhatsApp, followed up with requests for information through RCS, escalate to a voice interaction and conclude with a form submission over email. But how can large organizations manage those journeys without simply dictating a separate workflow for each interaction?   The answer is increasingly agentic AI customer service , where AI-driven agents can identify intent, reason about context, effect action on integrated systems, and multi-channel conversation continuity.   The distinction between conversational AI vs. agentic AI becomes more important here: the former is capable of supporting a dialog, while the latter can execute reasoning and actions within a wider business workflow under certain policies in a secure environment.   What changes when AI can take action? Conventional chatbots serve well for defined interactions, but in today’s service context multiple steps are usua...

  Advanced customer engagement is about more than just systems that react to queries. There is a drift toward software that can understand a goal, think through the necessary steps, interface with relevant systems, and act on its own.   That is where agentic AI enters.   In the tutorial, we introduce Agentic AI, discuss what makes AI agents different compared to traditional chatbots and generative AI, and cover why capabilities such as reasoning, memory, context, execution autonomy, and integrations are becoming increasingly important.   What makes an AI agent different? A standard chatbot usually operates on predefined scripts. Generative AI can generate responses on the fly based on a prompt and any available context.   An agent goes further: it can interpret an objective, determine the next action, use approved tools, and continue working across multiple steps.   An agent can:   •        ...

  Customer engagement is evolving beyond using scripts. But what really changes when an enterprise upgrades from a regular chatbot to an AI agent? The difference is clear in what takes place once an intent is recognized, which is reasoning, context, decision-making and task execution.   For businesses that face complicated customer journeys, that line between AI agents vs chatbots can shape how they design, integrate, and scale their digital engagements.   Chatbots handle conversations. Agents handle workflows. Conventional chatbots are very effective for structured interactions. They answer specific questions, take users on a predefined path, fetch information, and execute predefined commands.   AI agents generalize that approach by acting to achieve an outcome. Instead of reacting to just the most recent input, they may use contextual information to decide what to do next, including calling other (potentially connected) capabilities, all within estab...