Will AI autonomy drive identity verification evolution next year?

One industry player is betting on trends such as reusable identities; continuous assessment; and multimodal defenses to address fraud, privacy challenges.

In 2026, as AI systems are granted more autonomy, Identity verification will need to evolve beyond traditional KYC protocols to handle reusable identities, continuous assessment and multimodal defenses against AI-driven fraud.

With regulations such as the EU eIDAS 2.0 setting precedents, our predictions for AI-powered identity verification point to six aspects, as listed below.

Identity security/management predictions for 2026

2. My AI Did It”: Accountability for autonomous systems in APAC
AI agents may soon handle tasks such as shopping, fund transfers, portfolio management, price negotiations and contract signing. Productivity gains appear likely, but accountability questions persist: when AI acts, who bears responsibility?​

Traditional KYC processes may prove insufficient for autonomous AI. Institutions may need to verify agent parameters and oversight.

Regionally, Singapore signals a path forward: their Monetary Authority of Singapore has touted FEAT principles, the Veritas initiative, and AI Risk Management Guidelines, emphasizing governance, human accountability and lifecycle controls. Autonomy requires oversight. AI agents may need verifiable identities linked to human biometrics, creating traceable chains from intent to execution across borders. Such measures could support trust in regional digital economies. Trusted players may lead APAC’s digital transformation, as AI integrates into financial and commercial activities. Verified human anchors could underpin digital trust.

AI agents may need verifiable identities linked to human biometrics, creating traceable chains from intent to execution across borders. Such measures could support trust in regional digital economies. Trusted players may lead APAC’s digital transformation, as AI integrates into financial and commercial activities. Verified human anchors could underpin digital trust.

2. Identity verification as a business differentiator

In 2026, identity practices could distinguish market leaders from those facing breaches. Proper AI adoption could transform both business operations and fraud tactics. Costs extend beyond revenue to reputation, regulation and customer trust. Many firms still use static data, passwords and fragmented KYC, while attackers leverage recent tools. This gap may separate leaders from others.

Identity verification could shift towards continuous, adaptive assessment, predicting risks before they materialize while minimizing user friction. It evolves from point-in-time checks to ongoing user profiling.

Combining identity, historical, behavioral and risk data could yield dynamic user views. Continuous background assessment adapts to new signals. Fraud victims typically blame brands, not criminals. Firms viewing identity as a core business element may scale securely and expand globally.

— Robert Prigge, CEO

3. Reusable identity as an authentication shift

Reusable identity may transition from concept to practice in 2026, reducing repeated onboarding. Verified high-assurance identities become portable across trusted networks. Authentication merges with initial verification, treating identity as a persistent asset.

Success depends on global coverage, data rights with consent, and multi-modal biometrics.

Markets may divide: networks with scale enable frictionless experiences, ecosystem fraud detection and cost reductions; others face repeated verifications, higher costs and missed signals. Reusable identity could form a trust foundation, reinforced by regulations. EU eIDAS 2.0 mandates digital identity wallets, with similar rules emerging elsewhere. Aligned organizations may contribute to global trust systems combining verified IDs and shared intelligence.

Reusable identity could form a trust foundation, reinforced by regulations. EU eIDAS 2.0 mandates digital identity wallets, with similar rules emerging elsewhere. Aligned organizations may contribute to global trust systems combining verified IDs and shared intelligence.

— Bala Kumar, Chief Product and Technology Officer

4. Identity verification approaches for social platforms

Social platforms use behavioral analytics for age verification, but privacy concerns will persist in 2026. Biometric tools may combine AI age estimation, liveness detection and deepfake prevention to confirm real users and ages. Digital identity wallets offer data minimization, proving age without full disclosure. Users increasingly resist sharing IDs or biometrics solely for age checks.

Amid heightened consumer awareness of privacy rights, firms may clarify data collection, storage and usage, enhance encryption, and decentralize storage to reduce risks. Privacy-focused shifts could improve compliance and security in 2026.

— Reinhard Hochrieser, SVP, Product and Technology

5. Beyond knowledge-based authentication

— Philipp Pointner, Chief of Digital Identity

Amid rampant AI fraud and privacy issues, knowledge-based authentication will fade next year: it creates friction and liability. Consumers will seek data protection without clunky questions or flawed ID scans. Verification methods must prioritize security and seamlessness. Reusable identity could rise in 2026, with broader adoption following, delivering the ease of use and portability that consumers demand.

Countering AI-driven fraud with layered strategies

AI enables fraudulent digital identities via camera injection attacks on biometrics. An arms race pits adversarial AI against defenses. Static defenses may fall short; continuous, collaborative systems across ecosystems could learn and adapt to threats.

Multimodal liveness detection combines visual, auditory and motion signals, integrated with fraud intelligence, behavioral biometrics and risk analytics to preempt patterns.

Resilient firms may adopt predictive models, leveraging all signals to counter sophisticated attacks.

— Ashwin Sugavanam, VP, AI & Identity Analytics

Next year, AI agents will lower barriers to personalized fraud schemes, automating complex attacks. Countermeasures may combine multimodal liveness detection, contextual intelligence and privacy techniques like zero-knowledge proofs to verify identities without exposing sensitive data.

Fraud prevention requires balancing security with user experience. Risk-based approaches tailor verification: low-risk users encounter minimal steps, while high-risk cases trigger deeper scrutiny. This maintains compliance without frustrating legitimate customers.

— Alix Melchy, VP, AI

6. Privacy and Compliance in data collection and biometrics

Businesses will face growing tension between regulatory demands for data collection to verify identities, and consumers’ rising expectations for privacy. Enterprises need to adopt purpose limitation, collecting only data strictly necessary for defined objectives. This approach minimizes over-collection, reduces security vulnerabilities from excess storage, and fosters consumer trust through transparent, needs-based practices.

As biometric authentication expands for identity verification, careful management of sharing and retention becomes essential. Enterprises require frameworks to handle biometrics securely amid sophisticated fraud risks and evolving privacy laws. Striking this balance will protect legitimate users while enabling compliance in an era of advanced threats and regulatory scrutiny.

— Joe Kaufmann, Global Head, Privacy & DPO