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Agentic AI vs generative AI: a practical business guide
Compare agentic and generative AI for business. Understand costs, control and human approvals, with practical examples and a checklist for a useful pilot.
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Compare agentic and generative AI for business. Understand costs, control and human approvals, with practical examples and a checklist for a useful pilot.
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Bespoke software is built for one organisation to fit a process it already has, rather than licensed as a product many businesses adapt themselves to.
An AI agent is software that takes a goal and completes it — deciding the steps, using tools and data, and taking actions rather than just replying.
AI automation uses AI models to complete process steps that needed a person to read, decide or write — work that cannot be expressed as fixed rules.
Human-in-the-loop is a pattern where automation produces an output but a person approves it before it takes effect, keeping the decision with a human.
An agentic workflow is a fixed sequence of steps where AI models make decisions or produce content at defined points, keeping the process predictable.
An AI voice agent holds a spoken conversation over the phone, understands what the caller wants and completes the task instead of routing them to a menu.
AI guardrails are the constraints around an AI system that limit what it can do and check what it produces — permissions, validation and approvals.
AI integration is the work of connecting an AI model to the software and data you already run, so it acts on real, current business information.