Beyond the Chatbot: What "Agentic" Actually Means Across AI Labs, Payments and Core Banking
"Agentic" is one of those words that became load-bearing in technology marketing before the industry agreed on what it was carrying. In the space of a single quarter, it has been used to describe a consultancy's new pricing model, a card network's fraud engine, a checkout protocol, and now a core banking ledger. Regulators have started using it too. That is usually a sign a term is either maturing into a real category, or dissolving into meaninglessness, and right now it is genuinely uncertain which way it goes. This piece exists to give technical and business leaders a working definition anchored to three real, observable contexts rather than a single generic explainer.
The three contexts are consultancy and delivery-partner repositioning, payments infrastructure, and core banking. Each uses "agentic" to mean something structurally different, and confusing them leads to real strategic mistakes: budgeting for a delivery partner's agentic claims as though they were a payments capability, or evaluating a payments protocol with the same criteria you would apply to a core banking upgrade.
In This Guide
This article covers:
- A working definition of agentic AI, and how it differs from generative AI
- How "agentic" is being used in consultancy and delivery-partner repositioning
- How "agentic" is being used in payments infrastructure
- How "agentic" is being used in core banking, via Mambu's Intelligent Core
- Why UK regulators, including the Bank of England and FCA, are now using the term themselves
- A reference framework for applying the definition to your own vendor evaluations
Agentic AI Versus Generative AI: A Working Definition
Generative AI produces content, text, code, images, in response to a prompt, with a human deciding what happens next. Agentic AI is defined by autonomy over a sequence of actions: an agent can plan a multi-step task, take actions using tools or systems, observe the results, and adjust, with a human setting boundaries and reviewing outcomes rather than directing every step. The distinction matters because a generative feature bolted onto a product does not become "agentic" simply through better marketing copy; it becomes agentic when it is given the ability to act, not just to draft.
Generative AI answers a question. Agentic AI is trusted to take the next several steps on its own, within limits someone else has defined.
Why the Definition Keeps Getting Stretched
Because "agentic" now confers credibility, it is applied loosely: to chatbots with slightly more autonomy, to automation pipelines that were already rules-based, and to genuinely novel systems that plan, act and adapt. The three contexts below show what the term looks like when it is being used with real structural meaning, not just as a credibility marker.
Context One: Agentic as Delivery-Partner Repositioning
Across the consultancy market, "agentic" is increasingly used to describe a change in how software gets built, rather than a product feature. Elsewhen has repositioned around agentic AI with an outcome-based, four-week proof engagement model. Crosstide has announced a new partnership with Anthropic and is promoting an "Agentic SDLC" concept, positioning agentic AI as a change to the software development lifecycle itself. Vacuum Labs has joined Mastercard's Crypto Partner Program and is applying agentic-payments framing to that participation. Here, "agentic" refers to how an organisation delivers software: how requirements are decomposed, how much of the build is agent-assisted, and how commercial models reflect that shift. We cover this in more depth in our AI Labs evaluation framework for AI-native delivery partners.
Context Two: Agentic as Payments Infrastructure
In payments, "agentic" refers to something structurally different: infrastructure that allows an AI agent, rather than a human, to initiate, authorise and complete a transaction. Visa has introduced an Agent-to-Agent (A2A) fraud prevention enhancement at the network level. Stripe has demonstrated agentic checkout through its Universal Checkout Protocol, using shared payment tokens, and in doing so surfaced a real prompt-injection risk where a manipulated system prompt made a shopping agent behave more aggressively than intended. Mastercard has partnered with Bluefin on card-present security for AI-agent-era point-of-sale. Crossmint provides stablecoin and wallet onramp infrastructure live in more than 160 countries. We map this infrastructure layer in full in our companion piece, the agentic payments stack, explained. Here, "agentic" is a technical and security classification: does the system have the machine-readable authorisation and fraud controls needed to let an agent transact safely.
Context Three: Agentic as Core Banking Infrastructure
The newest and structurally deepest use of "agentic" is emerging in core banking itself. Mambu has introduced what it describes as an "Intelligent Core," connecting agentic AI directly to the banking ledger rather than layering it on top of a separate service. This is a materially different proposition to either of the two contexts above: it is not about how software is built, or about authorising a single transaction, but about giving an AI agent standing access to the system of record that holds account balances, transaction history, and regulatory reporting data.
Why Core Banking Is a Different Risk Category
An agent acting against a ledger carries materially higher stakes than an agent assisting with code delivery or authorising a bounded payment. A ledger-connected agent, even a well-governed one, needs the same rigour applied to any system with write access to financial system-of-record data: clear action boundaries, full audit trails, and a human review point for anything outside pre-approved limits. This is the context in which UK banking regulators are starting to pay close attention.
Why Regulators Are Now Using the Term "Agentic"
The Bank of England and the FCA have both begun commenting publicly on agentic AI as a systemic risk category, distinct from generative AI more broadly, reflecting exactly the core banking concern above: autonomous systems with the ability to act, rather than merely advise, sitting closer to the financial system's plumbing. For UK fintech platform owners and embedded finance leaders, this means agentic AI is moving from a product differentiator to a governance conversation, and any core banking, payments, or embedded finance roadmap that includes agentic capability should expect FCA and PRA operational resilience expectations to apply to it directly, not as an afterthought.
A Reference Framework: Which Context Are You Actually Evaluating?
When a vendor, partner, or internal team uses the word "agentic," the first useful question is which of the three contexts they mean. If the claim is about how software gets delivered, evaluate it as a delivery-model change: does pricing, proof structure, or SDLC integration actually change, as set out in our AI Labs delivery-partner framework. If the claim is about a transaction or checkout capability, evaluate it as payments infrastructure: does it sit at the network, tokenisation, point-of-sale, or settlement layer, as mapped in our agentic payments stack piece. If the claim is about core systems, such as a banking ledger, evaluate it as a governance and risk question first, and a technical capability question second, given the standing access being granted and the FCA/PRA expectations that follow. Innovify's AI/ML development and embedded finance and digital wallet teams work across all three contexts, and the distinction above is the first thing we establish with any client before scoping an agentic capability.
Frequently Asked Questions
What is agentic AI?
Agentic AI refers to AI systems capable of autonomously planning and executing a sequence of actions toward a goal, using tools or connected systems, observing outcomes, and adjusting, within boundaries a human has defined and with human review of outcomes, as distinct from generative AI, which produces content in response to a single prompt without taking further action itself.
What is the difference between agentic AI and generative AI?
Generative AI produces an output, text, code, or an image, in response to a prompt, with a human deciding what to do with it. Agentic AI is given the ability to act on a goal across multiple steps, using tools and systems, with a human setting the boundaries rather than directing every individual action.
How is "agentic" being used differently by consultancies, payments providers and core banking vendors?
Consultancies use "agentic" to describe a change in software delivery methodology, such as Elsewhen's outcome-based proof model or Crosstide's Agentic SDLC positioning. Payments providers use it to describe infrastructure that lets an AI agent authorise and complete a transaction, such as Visa's A2A fraud tooling or Stripe's Universal Checkout Protocol. Core banking vendors, such as Mambu with its Intelligent Core, use it to describe an agent with standing access to the banking ledger itself, which is a materially higher-stakes proposition than the other two.
What are some real examples of agentic AI use cases in fintech?
Examples include agent-assisted software delivery within an AI-native consultancy's SDLC, agent-initiated payment authorisation via infrastructure such as Visa's A2A tooling or Stripe's Universal Checkout Protocol, and agentic connections to core banking ledgers such as Mambu's Intelligent Core, each carrying a different risk and governance profile.
Why are UK regulators like the Bank of England and FCA commenting on agentic AI specifically?
The Bank of England and FCA have begun treating agentic AI as a distinct systemic risk category because agentic systems can take autonomous action, including against financial systems of record, rather than only producing content or recommendations for human review, which raises operational resilience and third-party risk questions that generative AI alone does not.
How should a CTO decide which "agentic" claims from vendors are substantive?
Identify which of the three contexts, delivery methodology, payments infrastructure, or core systems access, the claim actually belongs to, then apply the evaluation criteria specific to that context: commercial and SDLC evidence for delivery partners, network and tokenisation-layer specifics for payments, and governance and audit-trail rigour for core banking or ledger-connected agents.
Conclusion
"Agentic" is not one thing. It is a description of autonomy that means something different depending on what the autonomy is being applied to.
A delivery partner's agentic claim is a statement about how software gets built.
A payments provider's agentic claim is a statement about who is allowed to spend, and under what controls.
A core banking vendor's agentic claim is a statement about who, or what, now has standing access to the ledger. Regulators are right to be watching that third one most closely.
Why Businesses Choose Innovify to Navigate Agentic AI
Innovify works across all three contexts covered in this piece, through AI Labs, Agentic Commerce & Payments, and Embedded Finance & Digital Wallets, and the first thing our team does with any agentic AI conversation is establish which of these three contexts actually applies. Speak with our team if you are trying to make that same distinction for your own roadmap.
