From the UK’s new age assurance rules to the EU’s Digital Services Act (DSA) and beyond, regulations around protecting minors online are evolving quickly. The conversation around age assurance is increasingly being taken up by governments across Europe, but it’s no longer about IF age assurance will be required but rather HOW to implement it effectively and responsibly. However, before starting the implementation it’s crucial to understand the difference between age verification and age estimation? Age assurance is the umbrella term that covers both approaches, and knowing how they compare is essential for compliance, safety, and user experience.

In this article, we’ll break down the key differences between age verification and age estimation so you can decide which approach applies to your business.

What Is Age Assurance?

Age assurance is the broader framework for determining or confirming a user’s age online. It is designed to:

• Protect minors from harmful or inappropriate content
• Ensure compliance with legal and regulatory requirements
• Enable age-appropriate experiences on digital platforms
• Organisations have a responsibility to implement effective age assurance measures to comply with legal requirements and protect minors.

The EU’s Mapping Age Assurance Typologies and Requirements report identifies three main approaches to age assurance:

• Age verification – confirming age with certainty
• Age estimation – predicting a likely age or age range
• Self-declaration – users manually entering their age, which is the least reliable method

What Is the Age Verification Process and How Does It Work?

Age verification is the process of confirming whether an individual meets a specific legal age threshold before accessing restricted content, services, or products. Users are often asked to verify their age when purchasing age-restricted products or accessing certain online services. Unlike age estimation, which predicts a probability, age verification provides a clear yes/no result: once the process is complete, the user’s age is verified.

This certainty is essential in industries such as online gambling, alcohol and tobacco sales, e-commerce involving age-restricted products, adult content, and regulated financial services. Service providers are obligated to ensure only eligible users are granted access to age-restricted content. Moreover, age restrictions to products heavily depend on the country’s domestic laws, even within the EU, so from a business perspective, it’s crucial to implement a solution which takes them under consideration.

Methods of Age Verification

Generally speaking, we distinguish between five most-common methods of age verification. They are:

• Government-issued IDs – Passports, driver’s licenses, or national IDs checked against databases; the process often involves authenticating an id document or identity document using advanced technology
• Facial biometrics with liveness detection – Matching a selfie with an ID photo while confirming the user is real, not a spoof
• Credit card or payment verification – Using banking data or small transactions to verify age
• Digital IDs and electronic wallets – National identity systems or digital wallets that securely confirm age
• Third-party verification services – Providers that cross-check personal details against trusted sources

Why Age Verification Is Considered the Gold Standard

While age estimation provides useful signals, age verification is regarded as the most reliable and widely accepted approach. It relies on official documentation and technologies that deliver conclusive proof of identity and age.

• Provides definitive proof of age via government IDs or biometrics
• Resists fraud with liveness detection against spoofing/deepfakes
• Legally recognized by regulators and courts
• Can preserve privacy with decentralized ID or NFC tools
• Aligns with international standards (e.g., ETSI TS 119 461)

Limitations of Age Verification

Despite its reliability, age verification also presents challenges that can impact user experience and raise privacy considerations. These limitations highlight why some organizations may opt for lighter, estimation-based solutions in specific contexts.

• Users must share personal data, raising privacy concerns, though mitigated by on-device or decentralized solutions. Collecting sensitive information such as a user’s date of birth can increase these concerns, as birth date information, if not handled properly, could be misused for targeted promotions or other purposes.
• Requires active participation such as uploading documents or selfies
• May introduce friction into onboarding processes compared to lighter solutions

What Is Age Estimation and How Does It Work?

Age estimation is the process of predicting a user’s likely age or age range using AI-driven technologies. Estimating a user’s age accurately is crucial for compliance with regulations and for protecting minors online. Instead of providing definitive confirmation, it generates a probability score.

This approach is best used for age-appropriate experiences rather than strict compliance. For example, platforms may use it to tailor content for children versus adults.

Common Methods of Age Estimation

There are several approaches that can be used to estimate a person’s age without relying on official documents:

• Facial analysis – AI scans facial features such as wrinkles and bone structure in an image to estimate a person’s age. The quality of the image, including lighting and pose, can affect the accuracy of age estimation.
• Voice analysis – Machine learning models analyze tone, pitch, and speech patterns
• Behavioral analytics – Age is inferred from online activity such as browsing habits, media consumption, and interaction styles
• Multi-modal estimation – Combining face, voice, and behavioral analysis for improved accuracy
• Social vouching – Other users confirm or vouch for someone’s age

Human review may also be used as an additional safeguard to ensure fairness and accuracy in age estimation.

Advantages of Age Estimation

Age estimation technologies offer several benefits that make them appealing to businesses, especially when it comes to ease of use and privacy:

• Deliver a fast, low-friction user experience
• Require minimal personal data compared to document-based checks
• Can be processed on-device for stronger privacy
• Useful when full verification would be intrusive or impractical, such as in gaming or social media, and can be seamlessly integrated into a platform to deliver age-appropriate experiences

Limitations of Age Estimation

Despite the aforementioned benefits, age estimation also comes with its limitations that can affect accuracy, fairness and regulatory acceptance.

• Provides only probabilities, not proof, which means minors can be misclassified as adults and vice versa
• Even advanced systems have error margins, requiring higher “challenge ages” to reduce false positives. Age estimation algorithms are often ranked based on their accuracy and reliability in scientific evaluations.
• Not legally recognized as sufficient proof in regulated industries
• Can be circumvented with deepfakes, manipulated images, or spoofing
• May show bias and uneven accuracy across demographics, raising fairness concerns

Privacy Considerations in Age Assurance

A privacy-first approach to age assurance means minimizing data collection, using on-device methods when possible, and deleting verification data once checks are complete.

Protecting users’ sensitive data must be a top priority, especially when verifying a user’s age for access to age-restricted content and services. Modern age assurance tools are designed to minimize the use of identity documents, instead leveraging facial features analysis to estimate a person’s age without collecting unnecessary personal information.

To further safeguard privacy, it is crucial that any data collected during the verification process is securely deleted once the process is complete, reducing the risk of data abuse. Organizations should be transparent about how age verification works, what information is collected, and the specific purposes for which it is used. By providing clear communication and robust privacy protections, businesses can build customer trust and demonstrate their commitment to responsible data handling. Confidence in age assurance solutions comes from knowing that user data is protected at every step, and that only those who meet the required age criteria can access age-restricted services.

Seamless Integration of Age Assurance Solutions

Seamless integration ensures that age assurance tools work smoothly with platforms, APIs, and apps, providing compliance without disrupting the user experience.

For age assurance solutions to be effective, they must integrate seamlessly with existing systems, platforms, and devices. Modern age verification tools like IDENTT’s Vision are designed with flexibility in mind, offering APIs, SDKs, and detailed integration guides to ensure a smooth onboarding process for both businesses and users. This allows organizations to quickly embed age assurance into their online services, apps, and sites, providing a streamlined experience that minimizes friction.

Seamless integration is especially important for industries that process large volumes of users, such as e-commerce, gaming, and social media. By making the verification process as efficient as possible, businesses can maintain compliance with age-restricted regulations while delivering age-appropriate content and services. Ultimately, well-integrated age assurance solutions help organizations focus on their core activities, confident that their compliance and user experience needs are being met.

Non-Discrimination and Ethical Considerations

Ethical age assurance requires reducing bias in algorithms, ensuring equal access for all users, and maintaining transparency about how data is used.

Ensuring non-discrimination and upholding ethical standards are fundamental when developing and deploying age assurance solutions. Age verification tools must be designed to provide equal access to age-restricted content and services for all users, regardless of background or demographic factors. This means actively working to eliminate bias in age estimation algorithms and ensuring that verification processes are fair and transparent.

Ethical considerations also extend to protecting user privacy and preventing potential abuse of collected data. Organizations should clearly communicate the purposes and methods of their age assurance solutions, fostering trust and accountability. Regular review and assessment of these tools are necessary to maintain accuracy, fairness, and compliance with evolving regulatory requirements. By prioritizing ethical design and ongoing evaluation, businesses can ensure their age assurance solutions remain trustworthy, effective, and aligned with both customer expectations and legal standards.

What Are the Key Differences Between Age Verification and Age Estimation?

Age verification and age estimation differ when it comes to purpose they serve, methods of verification used, their overall outcome, usage and privacy matters.

• Purpose: Verification is designed to confirm legal age with certainty. Estimation predicts a likely age range to tailor experiences.
• Methods: Verification uses strong, official data sources like government IDs and biometrics. Estimation uses softer AI-driven techniques like facial, voice, or behavioral analysis.
• Outcome: Verification gives a binary “yes/no” result. Estimation provides a probability score, not definitive proof.
• Best for: Verification is required in compliance-heavy industries such as gambling, alcohol, and adult services. Estimation works better in low-risk contexts like parental controls, gaming, or content personalization.
• Privacy impact: Verification involves sharing sensitive data such as IDs and biometrics. Estimation generally collects less personal data, especially when processed on-device.
• Examples: Age verification is commonly used by online gambling platforms to comply with legal requirements and protect children’s rights. Age estimation, on the other hand, is often integrated into customer analysis systems for streaming services or social media platforms to personalize content and ensure age-appropriate experiences.

Which Method Should Businesses Use?

The choice between verification and estimation depends on:

• Compliance requirements – If you operate in a regulated industry, verification is essential
• Risk level – For lower-risk scenarios, estimation may be sufficient
• User experience goals – Estimation is smoother but less certain, while verification is more secure but requires user participation

Many businesses adopt a layered approach, using estimation first and triggering verification only when necessary.

To make an informed decision, businesses are encouraged to request demonstrations or see age verification and estimation solutions in action to better understand their capabilities.

What Do Regulations Say About Age Assurance?

Governments and regulators worldwide are increasingly mandating age assurance to protect minors online. While specific requirements vary by region, the overall trend points toward stronger, more consistent measures that balance child safety, user privacy, and industry compliance.

• EU Digital Services Act (DSA): Requires online service providers to implement appropriate and proportionate age assurance measures to protect minors and comply with regulations
• UK Regulations: Already moving beyond self-declared ages, requiring robust age checks for sensitive services
• European Standardization (BIK+ strategy): Ongoing work toward interoperable frameworks for age verification across borders

Key regulatory milestones for Age Assurance

The regulatory landscape has evolved rapidly over the past decade, with countries introducing stricter requirements to ensure safe and age-appropriate online experiences. Below is a timeline of major global milestones:

• 2018 – EU (GDPR): Introduced a digital age of consent between 13–16 for online services.
• 2019 – UK: ICO’s Children’s Code came into force, shaping online services for minors.
• 2021 – Australia: The Online Safety Act expanded eSafety powers, including protections for children.
• 2023 – UK: Online Safety Act passed, requiring stronger measures against harmful content.
• 2024 – USA: COPPA reinforced by multiple state laws (CA, UT, AR, TX) focusing on children’s online privacy and age checks.
• 2024 – EU: Digital Services Act fully enforced, requiring proportionate age assurance.
• 2025 – UK: Mandatory age verification for adult content under the Online Safety Act.
• Ongoing – Global: Brazil, Canada, Japan, and India are drafting legislation for age verification and child safety.

This regulatory trend makes it clear that both verification and estimation will be part of the future of online compliance.

Conclusion

Age assurance is becoming a central part of global digital regulation. Age verification provides certainty and compliance, while age estimation delivers lighter, privacy-friendly experiences.

The two approaches are not mutually exclusive. A layered model can balance compliance, privacy, and user experience.

At IDENTT, we help businesses implement both verification and estimation in a privacy-preserving, standards-based way, so they can comply with regulations while keeping online experiences safe for young users. Get in touch to find out more.