Asserting identity in AI-native environments – Questions you need to be asking

By Patrick Harding, Chief Product Architect at Ping Identity.

AI agent adoption is surging, transforming virtual assistants, streamlining workflows, and influencing decision-making across industries. In fact, recent research from KPMG found that 65% of organizations are now piloting AI agent programs — up from 37% in Q4 2024 — as clear evidence that adoption is accelerating at exceptional speed.

On a daily basis, these agents are handling tasks once reserved for humans: booking travel, assisting with healthcare decisions, authorizing transactions, and recommending products. This shift has large implications in how companies and customers engage. Decisions once shaped by advertising campaigns, loyalty programs, or curated websites are increasingly made by machines interpreting structured data.

In other words, brand perception is no longer solely in human hands. And if brands can’t effectively present their identity in this environment in a consistent, verifiable, and machine-native way, they risk being misrepresented, hallucinated, or even ignored.

This new reality raises a fundamental challenge: how do you ensure that your brand’s identity is correctly represented, trusted, and protected when its first point of interaction is no longer human, but machine?

Top identity considerations with agentic AI

Identity has always been interfaced through humans via a driver’s license, a login, or even an in-person interaction. These engagements were the gateways to trust, and the starting points for customer-to-organization relationships.

With agentic AI, those traditional gateways disappear as brands increasingly interact with machines more than individuals. This shift to AI-native environments introduces new and complex identity challenges that every organization must prepare for.

For example, instead of managing a limited set of users and systems, companies may soon oversee thousands of agents acting on behalf of employees and customers. Each must be issued credentials, governed, and eventually decommissioned like human users, raising the risk of unchecked access if proper controls aren’t in place.

At the same time, identity itself is becoming more complex. Some agents represent real people, while others act autonomously with their own credentials, blurring the line between human intent and machine-driven action — a distinction that is critical for both security and accountability.

Traditional safeguards are also being tested. Existing security tools were not designed to discern between a bad actor and a legitimate AI agent, leaving organizations vulnerable to both false positives and undetected threats. Once agents are granted delegated authority, oversight becomes even harder: tracking their decisions, permissions, and alignment with risk policies is a constant challenge. This results in a new layer of operational, financial, and reputational risk that demands stronger identity governance.

Each of these concerns points to the same conclusion: identity in the age of agentic AI cannot be static. It must be continuously managed, verified, and asserted if organizations are to maintain trust.

How brands can assert identity

Despite these challenges, there are concrete steps brands can take to assert their identity in AI-native environments. The key is to treat agents as participants in the identity ecosystem rather than outliers to be managed ad hoc.

1. Provision AI Agents Like Users. The first step is recognizing that agents themselves require identities. They should be issued credentials, assigned policies, and classified according to their risk profile. Treating agents as full digital citizens allows organizations to establish more agent accountability.
2. Enforce Precise Delegation. Every individual agent should be authenticated and authorized only for the actions they are explicitly permitted to perform. For especially sensitive operations, humans must remain in the loop to verify and approve. This prevents agents from overstepping or impersonating the individuals they represent.
3. Monitor and Govern Continuously. Trust and risk are dynamic, and so must be the oversight of agents. Continuous monitoring of agent activity makes it possible to detect anomalies in behavior, flag unusual activity, and prevent issues before they arise. Organizations should also build revocation into their systems so rogue agents can be cut off immediately.
4. Structure Identity for Machines. Human-built branding means nothing to machines. Companies must structure their identity data in ways that AI can parse, verify, and trust. That includes optimizing metadata, schemas, and content formats for AI consumption. Every action taken by an agent should also be traceable back to its source, and reversible if necessary.

What questions should brands be asking themselves?

To prepare for this new reality, leaders should challenge their organizations with tough but necessary questions:

• What happens when AI agents are manipulated by false or biased data?
• Who bears responsibility when an autonomous decision causes harm?
• How do we ensure our identity is presented in a way that machines interpret accurately?
• Do we have safeguards in place to revoke agent actions when things go wrong?
• What are the ethical boundaries when efficiency is the agent’s primary goal?

As we enter this new chapter of digital identity, asking and answering these questions now is the only way to preserve trust in the future. The organizations that thrive will not be those that make the most noise, but those that present their identity in structured, verifiable, and ethical ways.

In the AI age, trust will be the most valuable currency. Identity, when properly asserted, is the system that will preserve it.

About the author

Patrick Harding is Ping Identity’s Chief Product Architect.

Article Topics

AI agents  |  digital identity  |  digital trust  |  identity verification  |  Ping Identity