All terms
Agentic AI

Agentic AI

Agentic AI describes systems that pursue goals through their own sequence of decisions and actions, combining real-time reasoning with conversational understanding, in contrast to models that only generate a response when prompted.

What is agentic AI?

Agentic AI is a shift in what a model is expected to do. A generative model produces output in response to input; an agentic system holds an objective, decides what to do next, acts, and evaluates the result. The distinction is between producing an answer and pursuing an outcome.

The two capabilities it depends on

Agentic behaviour is built on conversational understanding and real-time reasoning working together. Neither is sufficient alone.

Memory may include:

  • Conversational understanding, interpreting intent, context, and history rather than literal words
  • Real-time reasoning, acting while an event is still in progress rather than analysing it afterward
  • Memory that persists across sessions and accumulates context
  • Tool use, reaching into systems of record to read and write
  • Grounding, tying every claim to a verifiable source

Why real time is the harder half

Conversational understanding is now widely available; reasoning fast enough to be useful during a live conversation is not. A system with one second to surface something relevant faces a different engineering problem to one with an hour to produce a summary, and most of the category solves the easier version.

How it differs from a chatbot

A chatbot waits for a question and answers it. An agentic system observes what is happening and acts on it, so the person is not required to know what to ask. This is why agentic systems are evaluated on what they surface unprompted rather than on the quality of their replies.

What outcomes can it improve?

  • Relevant information surfaced without being requested
  • Action taken during the moment, not after it
  • Context maintained across sessions and participants
  • Records kept current without manual entry
  • Less dependence on knowing the right question to ask

How does SpikedAI apply this?

SpikedAI is a Digital Twin built on both halves. It reasons in real time during live conversations and understands them conversationally, surfacing signals and next-best moves as they become relevant, then syncing records and follow-ups afterward, without waiting to be asked.

See agentic AI working live

Knowledge is valuable.
Knowing what to do with it changes outcomes.