Agents can act now, so the prize is safe and automated execution
“Still hiring humans?” asks a recent billboard in Silicon Valley. Agentic AI has moved from lab demo to the ante room of business. It promises to offer a tireless workhorse for many tasks until now performed by people. Enterprise-ready AI agents can perceive context, plan, and take actions across software and the web – from a ChatGPT agent to Google’s Gemini 2.0, Microsoft’s Copilot agents and Anthropic’s computer-use features that let Claude operate software under policy.
Setting aside the ethics and consequences of this shift, there’s no ignoring the fact that agentic AI offers tantalising prospects for productivity. The challenge, and therefore the opportunity, is whether AI agents can do complex tasks with meaningful outcomes safely, within policy, and with full auditability and human supervision where relevant. There are arguably few areas where it is more critical to overcome this challenge than when it comes to financial tasks. Such tasks are often essential components of business activities such as procuring supplies, managing work, processing customer orders and so on.
That’s where embedded finance comes in: delivering ways to do financial tasks such as access payment cards cards, place orders, move funds, reconcile, and report. All in ways that follow the rules, which are already designed for safety, auditability, and generally, forms of control in the context of third-party application software acting as an intermediary between financial institutions and customers.
Let’s imagine three high-impact arenas where this pairing changes the outcome today.
Business travel platforms
Think about a last-minute multi-city trip. An AI agent inside a travel platform watches the live booking context – fare types, cancellation windows, preferred suppliers, loyalty rules – and the company’s policy in real time. It issues a single-use virtual card locked to the airline’s merchant category, then chooses the best payment rail for the hotel at check-in to balance cost and acceptance, for example card networks for global acceptance, or account-to-account rails like open banking and SEPA Instant when the supplier supports them. Each transaction is tagged with the booking reference so reconciliation to the PNR or order happens automatically.
Now the meeting moves in the calendar. Because the AI agent is integrated with the calendar and the booking record, it spots the conflict, pulls the PNR, checks fare rules, cancels what can be cancelled, triggers refund workflows where allowed, re-issues payment credentials for the new itinerary, and posts the accounting entries – all while contributing to enhanced efficiency, and freeing up time for humans to focus on growing a business, rather than the mundane admin processes that can slow down growth. At platform scale, these micro-decisions move serious money.
Global business travel spending is projected to reach 1.57 trillion dollars in 2025, so basis-point gains in acceptance, cost of funds, and chargeback avoidance compound fast. GBTA. gbta.org
Employee benefits and HR tech
Benefits should feel like a helping hand, not more paperwork. In an HR app, an employee asks whether a particular childcare service or a set of therapy sessions is in policy. The AI agent answers in plain language, checks eligibility and remaining allowance, and proposes vetted providers that meet the company’s rules.
The HR app isn’t becoming an ecommerce site. Instead, embedded finance does the heavy lifting: the AI agent can issue a virtual card or wallet with the right spend category, merchant allow-list, limit, and expiry, ready to use at the chosen provider in store or online. When the payment goes through, the transaction settles instantly to the correct benefit budget, the receipt is captured, and there is nothing to claim back.
This is not cosmetic. 24 percent of UK adults have low financial resilience, and our research shows 81 percent of employees have experienced being out of pocket for over a month while they wait to be reimbursed.
Funding approved spend upfront – with embedded controls, live balances, and automatic reconciliation – solves the human problem and the operational one in a single move.
Closing thought
It’s natural to feel both excited and cautious about AI taking financial decisions. That’s why embedded finance matters. It brings the controls, guardrails, and governance that turn bold new possibilities into safe, everyday practice. The result: faster, fairer, and more human-friendly financial experiences.
