As AI agents take on a larger role in digital commerce, trust, identity verification, and secure transactions are becoming critical priorities for businesses. In an exclusive conversation with AI Reporter America, Kathleen Peters, Chief Innovation Officer at Experian, discussed how Experian’s partnership with Akamai aims to strengthen trusted AI-driven commerce through real-time security intelligence, fraud prevention, and Human-to-Agent Binding frameworks designed for the evolving agentic economy.

1. How does this partnership strengthen trust and identity in AI-driven commerce?

AI-driven commerce represents a major shift in how digital interactions happen. For decades, businesses have operated under the assumption that a human is directly behind every search, every payment, and every transaction. As AI agents begin acting autonomously on behalf of consumers, that assumption changes significantly.

What becomes critical is the ability to verify the AI agent as well as the human behind it, and the person’s intent associated with the transaction. Trust cannot exist in agentic commerce without accountability.

That is exactly what this partnership is designed to address. Experian brings deep expertise in identity verification, fraud prevention, and risk assessment, while Akamai contributes real-time cybersecurity intelligence and edge enforcement capabilities. Together, we are creating a more comprehensive trust framework that allows businesses to interact confidently with AI agents in a secure and scalable way.

At the center of the model is Human-to-Agent Binding, which establishes a secure, persistent connection between verified consumers, their devices, and the AI agents acting on their behalf. This creates continuity and accountability across the transaction lifecycle rather than relying on isolated verification moments.

The collaboration also strengthens trust through continuous evaluation. In a world of autonomous commerce, trust must be dynamic. Behavioral signals, transaction context, authorization status, and risk indicators all need to be evaluated in real time. Combining Experian’s identity intelligence with Akamai’s edge security capabilities allows organizations to make those decisions with greater speed and confidence.

Equally important, this work is being built within an open ecosystem. Through initiatives like Know Your Agent and KYAPay, we are helping establish interoperable standards for how AI agents identify themselves, declare intent, and transact securely across platforms.

Consumers will only embrace AI-driven commerce if they trust the systems operating on their behalf. Businesses will only scale autonomous transactions if they can confidently manage fraud, risk, and accountability. This partnership helps create the infrastructure needed for both.

2. What role will real-time threat intelligence and bot mitigation play in enabling trusted AI agents?

Real-time threat intelligence will become foundational in the age of agentic commerce because the challenge is no longer simply distinguishing humans from bots. The real challenge is determining which automated interactions are trustworthy and which are malicious.

Trusted AI agents will increasingly become legitimate participants in commerce ecosystems. At the same time, bad actors will inevitably attempt to exploit automation at scale.

This is where real-time intelligence becomes essential.

Akamai’s edge capabilities allow organizations to evaluate traffic patterns, contextual signals, device intelligence, and behavioral anomalies as transactions happen. When combined with Experian’s identity and fraud analytics, businesses gain a layered trust framework that evaluates both identity and intent.

Bot mitigation also evolves significantly in this environment. Historically, bot management focused on blocking automated traffic. Going forward, organizations must differentiate between authorized AI agents acting legitimately and malicious automation attempting to impersonate trusted behavior.

The network edge becomes an important control point because it enables organizations to evaluate trust before activity reaches core systems. That improves both security and performance while reducing unnecessary friction for legitimate users.

As AI agents operate at machine speed, trust decisions must happen just as quickly autonomous commerce.

3. How could trusted AI agents reshape fraud prevention and digital payments?

Trusted AI agents have the potential to improve both fraud prevention and payment experiences because they introduce identity continuity and transactional context into digital commerce.

Today, many fraud prevention models are reactive. Organizations evaluate risk after a transaction has already been initiated, using fragmented signals to determine whether activity appears suspicious. Trusted AI agents create the opportunity to embed identity, authorization, and trust directly into the transaction framework itself.

If an AI agent is securely linked to a verified consumer through Human-to-Agent Binding, merchants and payment providers gain greater confidence in who initiated the action, whether authorization exists, and whether the behavior aligns with trusted patterns. That additional intelligence can help reduce fraud while minimizing unnecessary friction for legitimate consumers.

One immediate impact will likely be improved transaction transparency. Trusted AI agents can provide structured signals related to identity verification, delegated authority, consent, and transaction risk in real time. Merchants receive more contextual intelligence than they often have in traditional e-commerce interactions today.

Tokenized payments will also play an important role. Through initiatives like KYAPay, AI agents can transact using secure tokenized credentials that reduce exposure of sensitive payment data while improving accountability and traceability.

From a consumer perspective, the experience also becomes more convenient. AI agents can evaluate products, compare pricing, manage preferences, and facilitate purchases without requiring repeated authentication steps or manual intervention throughout the process.

Longer term, trusted AI agents may even become active participants in fraud prevention. Agents could monitor spending activity, identify suspicious behavior, flag anomalies, or proactively intervene before fraudulent transactions occur.

What matters most is ensuring these capabilities develop within a framework grounded in accountability and transparency. Trusted AI agents should strengthen confidence in commerce, not introduce ambiguity around responsibility or authorization.

4. What governance and compliance safeguards are critical for AI agents transacting at scale?

As AI agents begin transacting autonomously, governance and compliance become increasingly important for maintaining trust across the ecosystem. Autonomous commerce introduces new questions around accountability, authorization, auditability, and consumer protection.

Persistent Identity Verification
One of the most impactful safeguards is verifiable identity binding. That connection must remain persistent, transparent, and continuously evaluated over time.

Delegated Authority and Consumer Control
Clear delegated authority is equally critical. Consumers must explicitly define what actions an AI agent is authorized to perform, under what conditions, and within what limits. Those permissions need to be enforceable and revocable.

Auditability and Transaction Transparency
Auditability also becomes essential in an agentic environment. Every AI-initiated action should create a transparent record of identity validation, authorization, transaction context, and risk evaluation. Particularly in regulated industries, organizations must be able to reconstruct how and why a decision or transaction occurred.

Dynamic Trust Evaluation
Dynamic trust scoring will play a major role as well. Trust in autonomous systems cannot rely on static credentials alone. Behavioral analysis, contextual intelligence, device signals, and transaction anomalies all need to be evaluated in real time.

Open Standards and Interoperability
Interoperability is another key safeguard. The ecosystem cannot scale effectively if every organization develops proprietary trust models that operate independently. Open standards like Know Your Agent and KYAPay help establish consistency around identity declaration, authorization, and transaction validation across platforms.

Evolving Regulatory Environment
There is also an evolving regulatory dimension to consider. Existing frameworks governing fraud prevention, consumer protection, anti-money laundering, and payment authorization will increasingly need to adapt to autonomous systems. Organizations deploying AI agents must ensure compliance obligations remain enforceable even as transactions become more automated.

Governance and Accountability
Ultimately, governance in agentic commerce is about preserving accountability in a world where machines increasingly act on behalf of people. Trust requires clarity around identity, intent, authorization, and responsibility at every step.

5. How does this collaboration balance seamless user experiences with stronger security and privacy?

Consumers will adopt AI-driven commerce because of the convenience it promises. People want intelligent systems that save time and personalize decisions. At the same time, they expect those experiences to remain secure, private, and transparent; and shoppers will be reluctant to rely on agent-driven transactions until that trust is established.

The objective is not to force consumers to choose between convenience and security. The future of commerce requires both.

The collaboration between Experian and Akamai focuses on building trust infrastructure that operates intelligently behind the scenes. Human-to-Agent Binding, trust tokens, behavioral analytics, and edge security capabilities allow identity verification and fraud evaluation without creating unnecessary interruptions for consumers.

If a trusted AI agent is securely associated with a verified individual and operating within expected behavioral parameters, transactions can proceed more seamlessly. Businesses receive real-time trust signals while consumers avoid repetitive authentication steps and excessive friction.

Akamai’s edge infrastructure also supports both performance and security simultaneously. Evaluating trust closer to the edge improves response times while identifying malicious behavior earlier in the interaction lifecycle.

Consumers should experience the benefits of personalization and automation without having to manage the complexity of security themselves. The trust framework operates in the background, enabling experiences that feel both seamless and accountable.

6.What integration challenges do enterprises face when adopting trusted AI agent frameworks?

Many enterprise systems were built around the assumption that humans directly initiate digital interactions and continue to engage as the transaction progresses, driving and checking in each step of the way. Agentic commerce changes that operating model significantly, which introduces both technical and operational process challenges.

Identity infrastructure is often one of the first hurdles. Organizations may have separate systems managing authentication, fraud prevention, payments, customer identity, and authorization workflows. Supporting trusted AI agents requires those environments to work together more cohesively than they have historically.

The good news is organizations do not need to replace existing infrastructure to participate. Our approach is intentionally platform agnostic and designed to integrate with current commerce and payment environments, helping businesses extend trusted identity frameworks into the age of AI without rebuilding everything from the ground up.

7. How does this partnership advance the long-term vision for an open Agent Trust ecosystem?

The long-term success of agentic commerce depends on trust being interoperable, scalable, and shared across the ecosystem. No single company can establish that future independently. It requires collaboration across identity, payments, cybersecurity, AI platforms, and digital commerce infrastructure.

This partnership represents an important step toward building that broader foundation.

Experian contributes identity intelligence, fraud prevention, and trust scoring capabilities. Akamai adds real-time security intelligence, behavioral analysis, and edge enforcement. Skyfire supports interoperability and tokenized payment innovation, while Visa provides trusted payment infrastructure and network scale. Each participant strengthens a different layer of the trust stack required for autonomous commerce.

The larger vision extends beyond securing individual transactions. The objective is to create an open ecosystem where trusted AI agents can operate consistently across platforms, merchants, payment providers, and digital environments.

Initiatives like Know Your Agent and KYAPay are critical because they establish shared standards around identity declaration, authorization, transaction integrity, and trust signaling. Without common frameworks, the ecosystem risks fragmentation and inconsistent security models that would limit adoption and scalability.

Identity portability is also important. Consumers should not need to repeatedly establish identity and authorization every time an AI agent interacts with a new platform or merchant. Trusted credentials and behavioral trust signals should move securely and consistently across the ecosystem while preserving privacy and accountability.

Looking ahead, agentic commerce will likely extend far beyond retail and payments. AI agents may increasingly participate across financial services, healthcare, travel, insurance, and many other industries where identity and trust remain essential.

For that future to scale responsibly, organizations need confidence that AI-driven interactions are secure, auditable, and interoperable; trusted by consumers and retailers alike.

This collaboration helps move the industry toward that outcome.