Ultra TL;DR:

AI-driven identity brings huge convenience and risk. If your digital assistant becomes your passport, what happens when it gets hacked, or forgets who you are? We urgently need new safeguards, recovery options, and digital rights before it’s too late.

TL;DR

As AI evolves from simply assisting us to authenticating and representing us, the boundaries between digital convenience and personal risk blur.  With OpenAI and others moving toward AI-powered identity providers (IdPs), we face a future where your digital assistant could become the gatekeeper to your entire online life, not just validating credentials, but knowing your habits, moods, and behavioural patterns.

This brings radical convenience, continuous security, and a new era of personalisation, but also profound new risks: identity cloning, deepfake-driven fraud, exclusion, and the potential loss of agency over your digital self, especially when illness or life changes alter who you are.

Unlike traditional IdPs, AI-based systems can recognise you by how you think, type, and act, offering both new protections and new avenues for abuse or exclusion. But as industry and policymakers scramble to keep up, crucial questions remain:

• Can you appeal or understand an AI’s decision to deny access?
• What happens to your digital identity if you’re locked out, or when you die?
• Who sets the rules for legacy, recovery, and portability across platforms?
• And how do we ensure that digital identity remains a right, not a privilege?

This article calls for urgent, compassionate frameworks: adaptable protocols for identity recovery, clear appeals and redress, digital legacy planning, and strong safeguards against insider threats, coercion, and global regulatory gaps. The real danger isn’t just technological dependence, but surrendering our right to change, recover, or move on when things go wrong. Now is the moment to shape how AI-driven identity will empower, or endanger, us all.

Prefer to Listen?

We got you, with the AI Generated Podcast discussing the key points of this article.

Introduction: Convenience, Seduction… and the Path We’re On

OpenAI recently announced it is exploring a feature allowing users to sign into third-party services using their ChatGPT credentials, a move that positions it as a potential Identity Provider (IdP) in its own right. This is more than a convenience play; it’s a strategic leap into the very infrastructure of digital trust.

Key sources:

• TechCrunch: https://techcrunch.com/2025/05/27/openai-may-soon-let-you-sign-in-with-chatgpt-for-other-apps/
• OpenAI (Codex CLI & Sign-In): https://help.openai.com/en/articles/11381614-codex-cli-and-sign-in-with-chatgpt
• OpenAI (developer interest form): https://openai.com/form/sign-in-with-chatgpt/

On the surface, this looks like a natural evolution… AI takes the friction out of logins, sparing us from the hassle of passwords and one-time codes. But there’s a subtle, seductive catch: the more convenient the system, the more we entrust to it. When the digital assistant that knows your late-night worries also holds your digital keys, the distinction between “helpful” and “all-seeing” becomes dangerously thin.

We’ve spent years trading convenience for privacy, but never before have we risked binding so much of ourselves, our habits, our moods, our routines… to a single platform. The path ahead isn’t just about seamless logins. It’s about whether we can draw a line before our most private selves are quietly absorbed into the infrastructure of the internet.

From Passwords to Personas

Not long ago, “identity” online usually meant usernames, passwords, and… outside of banking or big enterprise, two-factor authentication was rare. Hardware tokens like RSA SecurID have existed since the 1990s. By the late 2000s, banks and some services started rolling out SMS codes, but it was only in the 2010s that 2FA became truly mainstream with the rise of smartphones and authenticator apps.

Later came single sign-on: Google, Apple, or Facebook vouching for us at the click of a button. But each leap in convenience brought new questions, about data sharing, profiling, and control.

Now, AI is poised to take the next step. Tools like ChatGPT don’t just validate your email… they can recognise your writing style, remember your quirks, and infer your intent. The promise? An authentication system that doesn’t just check a credential, but recognises you… sometimes better than you recognise yourself!

This isn’t abstract. Companies like BioCatch (https://www.biocatch.com) founded in 2011, pioneered the use of behavioural biometrics: capturing metrics on how you type, move your mouse, or hold your phone.

In the early days, BioCatch captured around 200 subtle interaction points; today, that number exceeds 2,000 biometric signals… from device angle, pressure, and swipe dynamics to navigation habits and hesitation patterns.

While these data points build a rich behavioural profile, BioCatch’s focus is on capturing physical and interaction-based traits… not interpreting your emotional state. By contrast, AI systems like ChatGPT may begin to infer context or mood from language and conversational patterns, but behavioural biometrics remain a separate (and typically more privacy-preserving) discipline.

It’s a shift from static credentials to dynamic, evolving patterns… identity as a living signature. As one VISA executive once remarked during a keynote speech, their favourite Friday takeaway shop knew them better than their bank: it wasn’t about passwords, but about the lived familiarity and personal touch of real relationships. The takeaway staff recognised them on sight, remembered their usual order, anticipated special requests, and even knew when to ask, “more chilli, less sauce?” It was less about formal authentication and more about genuine understanding… built on routine, trust, and personal nuance. In the world of AI-driven identity, it’s not just what you know, but how you are, moment by moment.

As we shift to AI-driven identity, the lines between security, privacy, and surveillance will blur further… often invisibly to the end user. Passwords are being replaced by personas, with AI as both the gatekeeper and the observer. We’re moving from “prove it’s you” to “prove you’re you… across every context, mood, and moment”. The question is, do we understand what we’re trading for that seamless experience? Are we ready for the additional regulatory oversight that is coming our way?

What AI Identity Could Offer

AI identity-based access and management has huge potential in the ever-evolving threat landscape of account takeover, identity fraud, spoof accounts and more. Unlike static credentials or simple multi-factor authentication, AI can leverage continuous, contextual, and behavioural signals to verify not just who you say you are, but how you uniquely act online.

Already, attackers have used deepfake voices to impersonate CEOs in real-time calls.  One infamous 2023 scam saw $35 million transferred after a finance officer was tricked by a cloned executive’s voice. https://www.businesstoday.in/technology/news/story/35-million-gone-in-one-call-deepfake-fraud-rings-are-fooling-the-worlds-smartest-firms-469682-2025-03-27

That’s just the tip of how AI is being abused by threat actors, take a look for yourself:  https://arya.ai/blog/top-deepfake-incidents

The risk is no longer hypothetical.

That said, when implemented thoughtfully, AI-based identity systems offer a range of compelling benefits that extend well beyond convenience:

• Continuous verification rather than one-time login
• Fraud detection based on subtle deviations in behaviour
• Easier onboarding and fewer forgotten passwords
• Access decisions made in real time, based on confidence levels
• Potential mitigation of deepfake-driven impersonation attempts
• More assurance of your identity across services

These features offer a glimpse of a future where identity becomes fluid yet secure, tailored to you in a way that static credentials never could be.

The New Risks: Deepfakes, Model Reconstruction, and Identity Pivot

With great power, comes greater responsibility… or perhaps greater accountability. If AI becomes the gatekeeper of your identity, what happens when it’s compromised?

Today, an attacker may phish your Google password or SIM-swap your phone. Tomorrow, they might train a model to imitate your writing style, vocal cadence, or emotional tone… and trick an AI IdP into believing they are you.

While a breach of your OpenAI or AI-linked identity may feel inevitable in a threat landscape where adversaries adapt rapidly, the consequences depend on:

• How tightly coupled your AI ID is to critical services (banking, healthcare, legal)
• What audit trails or secondary verification methods exist
• Whether fallback mechanisms are accessible to the real user

Unlike today’s federated identity models, the AI IdP may give attackers a far broader pivot point, one that’s behavioural, contextual, and increasingly difficult to reverse engineer or dispute.

But deepfakes and model emulation aren’t the only threats on the horizon. As AI-driven identity systems mature, so too do the attack surfaces and the complexity of the risks we face.

Expanding the Threat Surface

But it’s not just about deepfakes or model reconstruction. As AI-driven identity systems evolve, so do the attack surfaces. Insider threats, where trusted individuals manipulate or exploit the system, become a real risk. Attackers might target the training process itself, poisoning data or introducing subtle biases that evade detection. Adversarial machine learning techniques could be used to fool identity systems, while physical attacks (such as 3D masks or replayed voice samples) threaten biometric defences.

Modern social engineering campaigns may even attempt to bypass “emotion” or “duress” detection, tricking the system into granting access or failing to trigger alerts.

Robust AI identity management requires anticipating these new and emerging threat vectors, not just the headline risks.

The question arises: what differentiates this approach from Google or Facebook as IdPs?

To fully understand the implications, it helps to compare traditional identity providers with this new generation of AI-based IdPs:

Comparison Table: Traditional vs AI-Based IdP

While the incumbents already collect vast swaths of data (20,000+ signals in Meta’s case), AI-based IdPs profile users more deeply:

• They contextualise behaviour in real time, not just from historical logs
• They integrate multi-modal interaction signals (voice, tone, writing, usage, sentiment)
• They begin to build an LLM-shaped you… potentially usable across services

This opens profound new pivot points for threat actors: what if your AI-based ID is compromised not through credentials, but by identity emulation via model reconstruction?

Recovery in the Age of Emulation

We already struggle with account recovery from traditional IdPs when our identities are hijacked. But what happens when the attacker is you… or at least, a convincing mimic of you, built from months or years of scraped data, conversations, and behavioural patterns?

It’s not just about cybercrime or fraud. Real life happens:

• What if you suffer a stroke, neurological disorder, or medical event that fundamentally changes how you speak, type, or interact?
• What if trauma, medication, or natural ageing alters your digital “signature”?
• How can a spouse or executor regain access after bereavement, to manage critical accounts or settle an estate, if the system is looking for a version of you that no longer exists?

Another crucial aspect is inclusivity. Not everyone’s “normal” matches the assumptions of an AI. Neurodivergent users, those with physical or cognitive disabilities, and people experiencing changes in mental health may interact with technology in unique ways that challenge automated systems. Even temporary life events, like stress, injury, or the natural ageing process, can lead to new patterns of behaviour that might be flagged as suspicious or unrecognisable. Truly resilient digital identity systems must be designed to accommodate this human diversity, with compassionate and accessible routes for appeal and recovery.

The barriers to recovering stolen or lost identity grow exponentially in an AI-driven world:

• A spoofed LLM model of your digital self could convincingly argue “it” is you.
• Takedown and appeals processes remain inconsistent, slow, and platform-specific.
• There are few, if any, standards for cross-provider digital identity revocation.
• Life events can change you, sometimes overnight… making even legitimate users look “suspicious” to an algorithm.

If you’ve ever tried to reclaim a Gmail or Facebook account after a hack, you already know how frustrating it is… without the added complexity of LLM impersonators or evolving behavioural profiles.

What’s needed is a blueprint for identity recovery and digital compassion:

• Protocols for identity revocation and revalidation, akin to digital certificate revocation in PKI.
• Cross-platform trust registries, linking behavioural “keys” to validated individuals and their legal representatives.
• Human fallbacks and appeals, for those whose lives and behaviours are fundamentally changed by medical, psychological, or life events.

Future AI identity systems must anticipate not just technical failure, but the reality of human fragility and change. If identity is “how you are” as much as “who you are”, the system must be able to forgive, and adapt… when you inevitably change.

What Can You Do Right Now?

As we wait for industry, policy, and technology to catch up with the challenges of AI-driven identity, there are practical steps you can take to protect yourself and your organisation. None of these are silver bullets.  Though each one reduces your risk, raises awareness, and helps set expectations with vendors and policymakers about what’s needed for digital identity resilience.

Don’t forget your digital legacy:

It’s also wise to plan for the unexpected. If you become incapacitated or pass away, who should be able to access your accounts or digital persona? Most current systems do not address digital inheritance or the transfer of AI-shaped identity. Consider documenting your wishes, using account legacy features where available, and talking to family or trusted contacts about digital succession, so your digital life isn’t left in limbo.

Beyond legacy planning, there are several steps you can take right now to reduce risk and stay ahead of emerging identity threats:

• Stay alert: Monitor for unusual logins or access attempts, especially if your account supports behaviour-based recovery.
• Advocate: Ask vendors and service providers about their AI identity recovery, appeals, and data correction processes.
• Educate your org: If you’re in IT, security, or compliance, brief your team on the risks of AI-based impersonation and deepfake phishing.
• Practice good digital hygiene: Strong, unique passwords, MFA, and reviewing what permissions you grant AI assistants still matter.
• Join the debate: Participate in industry or standards groups.  Your voice can help shape what recovery and appeals look like in the next era.

Reclaiming Your Identity in an AI-Driven World

Industry efforts are in their infancy.  No robust, widely adopted solution exists yet.

The technology industry is only beginning to grapple with the reality of AI-driven identity theft and impersonation. Right now, there’s no universal playbook for how to reclaim your digital self if a large language model has cloned your behaviour and is passing itself off as “you”.

Here’s what’s emerging… and what’s still missing:

• LLM Watermarking:
Some researchers are working on cryptographic watermarks in LLM outputs, making it easier to spot AI-generated text. But these are easy to evade and don’t address full persona mimicry.
• Decentralised Identity & Verifiable Credentials:
W3C, Microsoft, and others are building DID/VC systems, theoretically letting you revoke or rotate your identity keys. However, they’re not yet designed for behavioural or LLM-based identity theft.
• Behavioural Trust Keys/Digital DNA:
New approaches suggest using a persistent pattern of behaviour as a “key”, but questions remain:
  • Who manages revocation?
  • How do you prove you are you if your behaviour changes?
• Regulatory Frameworks:
The EU AI Act, UK’s NCSC Secure AI Guidelines, and similar efforts are setting boundaries for trustworthy AI. In the US, the NIST AI Risk Management Framework and the White House’s Executive Order on Safe, Secure, and Trustworthy AI have begun to outline principles, but there is still no comprehensive federal law or standard recovery protocol. No country yet has a universal playbook for AI-based identity compromise or recovery.
• No Universal Solution… Yet:
At present, there’s no clear way to invalidate or “revoke” a cloned LLM version of yourself. Appeals processes are manual and slow, and most platforms aren’t equipped to handle AI-based impersonation at all.

Until a new framework emerges, we’re all at risk of being permanently locked out by our own digital shadow.

The Unspoken Risks of Identity Permanence

Passwords can be changed or reset. But what about a behavioural signature… your way of speaking, moving, and interacting… that’s meant to be unique and persistent?

Life rarely stands still. Illness, trauma, and age can fundamentally reshape who we are and how we behave:

• A stroke or neurological event can change how you write, speak, or respond emotionally.
• Trauma or medication might alter your emotional range, language, or interaction style.
• Evolving accessibility needs may require assistive tech that transforms your digital “footprint”.

When identity is anchored to “how you were” instead of “who you are”, the risk is that future-you could be locked out by design.

Today, a password still works after a major life event. But will a future AI IdP recognise you if your LLM-shaped digital signature no longer matches your history?

Future identity systems must be built with compassion, adaptability, and a clear appeals process for those whose lives, and behaviours, are altered outside their control. True digital identity is lived and adaptive, not frozen in time.

Designing Ethical AI Identity

With such deep integration of identity, behaviour, and trust, the ethical stakes couldn’t be higher.

The evolution of AI-based identity systems necessitates a balance between innovation and ethical responsibility. As these systems become more integrated into our daily lives, it’s imperative to consider the frameworks and guidelines that ensure their trustworthy and fair deployment.

🏛️ EU AI Act:
The world’s first comprehensive AI regulation, setting risk-based obligations and aiming to ensure AI systems are safe, transparent, and respect fundamental rights.
https://digital-strategy.ec.europa.eu/en/policies/european-approach-artificial-intelligence
(Community resource: https://artificialintelligenceact.eu)

🛡️ NCSC Guidance on AI Security:
The UK’s National Cyber Security Centre provides guidance on secure AI system development and deployment, emphasising secure design, robust data management, and transparency.
https://www.ncsc.gov.uk/search?q=AI&sort=date%2Bdesc

🌐 Framework Convention on Artificial Intelligence:
An international treaty initiative from the Council of Europe, aligning AI with fundamental human rights and the rule of law.
https://www.coe.int/en/web/artificial-intelligence/home

🔐 eIDAS Regulation:
The EU’s regulation for secure, interoperable digital identity and trust services across Europe.
https://digital-strategy.ec.europa.eu/en/policies/eidas-regulation

🇺🇸 NIST AI Risk Management Framework:
A US National Institute of Standards and Technology voluntary framework for managing AI risks and supporting responsible AI use.
https://www.nist.gov/itl/ai-risk-management-framework

🇺🇸 White House Executive Order on Safe, Secure, and Trustworthy AI (2023):
The first US-wide Executive Order on AI, setting out principles for safety, security, privacy, civil rights, and transparency.


https://www.federalregister.gov/documents/2023/11/01/2023-24283/safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence

Note: This is a fast-moving area… details and URLs may change as US AI policy evolves. For the latest updates, see https://www.whitehouse.gov/?s=AI  

What’s Still Missing:
Despite these advances, no current framework fully addresses identity handover or ownership post-breach, appeals and recovery for LLM-based identity theft, or the reality of identity drift due to medical or personal change.

As we move into this space, governance must evolve in tandem with capability. Industry, regulators, and users all have a role to play.

Regulatory Fragmentation: Global Gaps and Geopolitical Risks

Despite recent advances, the international regulatory landscape remains fragmented. Laws and guidelines vary significantly between regions, and users are often exposed to cross-border risks or “regulatory arbitrage”, where companies exploit weaker protections in some jurisdictions.

Moreover, in countries lacking strong legal safeguards, or those using AI for surveillance or exclusion, AI-driven identity can easily be turned against vulnerable populations. Harmonising standards and protecting digital rights globally will be an ongoing, urgent challenge.

Emerging Challenges: What’s Next for AI Identity?

As technology races forward, other crucial questions remain open:

• How do we ensure neurodiverse, disabled, and ageing users aren’t left behind?
• What legal frameworks will govern digital legacy, inheritance, and succession?
• Can AI identity systems resist insider threats, adversarial attacks, and model poisoning?
• Will regulation keep up, especially across borders?

What Industry Still Isn’t Solving

Despite regulatory momentum and rising awareness, several critical gaps remain on the path to trustworthy, user-centric AI identity systems:

1. Transparent Decision-Making & Redress
   AI IdPs, especially those using LLMs and behavioural biometrics, are often opaque. If you’re denied access, can you find out why? Will you have a fair appeals process, or will decisions be hidden behind a “black box”? Future systems must prioritise explainability, mandated by regulation, so every user understands their digital fate.
2. Cross-Provider Identity Portability
   Today, losing access to your primary identity provider (whether Google, Apple, or OpenAI) is like losing your passport, except you often cannot “move” your digital identity elsewhere. The industry needs open, interoperable standards for identity portability, including robust recovery and revocation procedures.
3. Adversarial and Insider Threats, Supply Chain Security
   While AI IdPs are raising the bar for attackers, they also create new supply chain risks: manipulated model updates, compromised training data, or rogue insiders. Industry must build in transparent audit trails, third-party review rights, and continuous integrity checks.
4. Coercion and Consent Signals
   AI may detect duress or abnormal interaction, but who decides what counts as “coerced” or “authentic”? What happens if this detection is abused by employers or governments? Robust frameworks for consent, duress handling, and “proof of life” must be co-developed by industry and civil society.
5. Global Human Rights and Digital Citizenship
   As digital identity becomes a prerequisite for accessing services and rights, exclusion from the system could amount to “digital statelessness”. International frameworks should treat digital identity, and its recovery/appeal, as a core human right, on par with freedom of movement or due process.
6. Legacy and Inheritance, AI Persona Succession
   Who manages your AI persona if you die, move, or become incapacitated? There’s still no consensus on digital inheritance or “winding down” an AI identity. The legal system, industry, and users need to develop clear, compassionate succession processes.

Closing: The Beautiful Trap

The seduction of convenience is powerful. AI IdPs offer frictionless sign-ins, personalised experiences, and a world that just knows you. But the deeper you integrate, the harder it becomes to walk away.

When your AI becomes your ID, the loss of access is more than technical, it’s existential. You’re not just locked out of services… you’re locked out of your digital self.

If the system forgets you, or worse, confuses you for someone else, what recourse will you have?

Because when your AI becomes your ID, the question isn’t just “can it prove who I am?”
It’s “will it still recognise me when I’m no longer the same?”
And more importantly: will it let me become someone new?

The real trap isn’t just technological dependence… it’s surrendering the right to change, to grow, or to recover when things go wrong.

Your Voice Matters: Join the Dialogue

This post isn’t a final answer… it’s a prompt for deeper conversation.

Whether you’re an engineer, a policymaker, an ethical AI researcher, or simply a concerned user, I’d love to hear your views:

• Do you see AI IdP as a promising future or a dangerous overreach?
• Are there safeguards you believe should be built in from day one?
• How would you design identity recovery, continuity, and consent?

Drop your thoughts below, challenge the assumptions here, and let’s co-create what the future of digital identity should be… not just what it could become.