Building an agentic-ready enterprise starts with trust between a company and its employees. As our CEO Brian Doubles has said: “Our culture is built on trust — giving our people the freedom to innovate, experiment and apply technologies like AI in ways that make a real difference for our customers and partners.”
At Synchrony, years of consistent listening, collaboration and follow-through have ensured that employees trust that we’re using artificial intelligence to make their work better.
When they told us they wanted more access, training and use cases of how to use AI tools daily, we rolled out SynchronyGPT across the company, now paired with an AI Field Guide covering best practices and prompt training so employees could immediately apply it to their everyday work.
Adoption is strong, with nearly 100% of our professional workforce using AI tools and 80% of employees believing AI will positively impact their careers. Importantly, employee trust is high — 90% of employees trust Synchrony to use AI fairly, ethically and responsibly.
We see AI as additive, where people remain at the core as the creative idea leads, critical thinkers, and decisionmakers. Artificial intelligence frees our best talent from tactical work and redeploys them to more meaningful, innovative work.
Agentic AI also requires transforming the relationship between companies and customers. As purchasing authority shifts to AI acting under permission, hard questions must be answered. Who is authorized? What actions can an agent take? How is consent captured and enforced? Who is accountable for disputes, fraud or errors? Companies that answer those questions clearly and perform consistently will be the safest choice for consumers to delegate to and the easiest choice for agents to recommend.
Trust in this context becomes much more than a brand message. It is measurable performance by AI agents including predictable approvals, low fraud loss, fast and fair dispute resolution, transparent terms, strong identity protection, actual performance in customer service and clear boundaries on agent behavior. Agents will steer spend toward institutions that deliver reliable outcomes because reliability reduces risk for the consumer and friction for the merchant. When software becomes the shopper, trust becomes the last durable advantage.
How do you create AI agents that meet these high standards? First, prioritize collaboration. By aligning with frameworks like Google’s Agent Payments Protocol (AP2), Universal Commerce Protocol (UCP) and Model Context Protocol (MCP), financial services companies can help shape standards for how AI agents securely find products, place orders and make payments.
Financing products must also be redesigned for a world where buyers include agents, not just consumers. Rewards, fees and financing terms need structured, machine-readable formats; fine print that diverges from what an agent ingests will send spending elsewhere. Fraud and authorization models must recognize agent patterns, and humans must remain accountable for outcomes, especially in financial services, where explainability isn’t optional.
Finally, issuers should recognize that retailer agents can be natural partners. Both parties prioritize high approval rates and fast decisions. Piloting agent-aware offers with merchants positions issuers as the default choice for machine-to-machine commerce.
