As AI makes it harder to tell whether online activity is human or automated, blockchain-focused investment firm Pantera Capital is supporting a new wave of verification solutions.
For decades, the internet has operated on a simple premise: Most users are human. That assumption is now being challenged. Advances in generative AI, along with the rise of more agentic AI systems capable of acting with increasing autonomy, have made it possible to produce text, images, and entire digital personas at scale, making it increasingly difficult to distinguish between what is real and what is not.
As AI systems begin to act autonomously (interacting with services, making decisions, executing transactions, and, in some cases, operating as persistent agents) questions of identity and trust are becoming more urgent. How do platforms differentiate legitimate visitors from bots or AI agents? How do businesses verify who or what they are dealing with? And what happens to frameworks built around human identity when nonhuman actors participate directly in the digital economy?
In response, organizations and developers are testing a range of new approaches, from platform-level verification tools to new forms of digital or proof of humanness. Among them are blockchain-based systems designed to prove “personhood” or issue verifiable credentials, tamper-resistant records that can be checked instantly without relying on a central authority.
Fortune Brand Studio sat down with Cosmo Jiang, board director at Solana Company and general partner at blockchain-focused investment firm Pantera Capital, to explore why identity or humanness online is a growing challenge in the AI era and how new technologies may help restore trust in an increasingly machine-generated internet.
What makes online identity a harder problem now than it was a few years ago?
The biggest change is that online activity is no longer limited to identifiable human users clicking through websites and apps. You now have synthetic content that can imitate real people, automated accounts that can interact at high volume, and AI models that are beginning to carry out tasks on their own.
That changes the burden on platforms and businesses. They are no longer just managing user accounts. Instead, they are being asked to decide whether an actor is legitimate, whether it is authorized to act, and whether it should be trusted.
What used to be a relatively contained problem, verifying if a user is indeed human, has become a broader question of authenticity, authorization, and trust.
Where do the biggest weaknesses show up in existing systems? Anywhere identity is tied too closely to a single platform or a narrow set of credentials. Most of today’s systems assume there is a human user behind the account and that trust can be established through passwords, platform verification, or conventional fraud checks.
That becomes less effective when software can generate convincing identities, interact constantly, and operate across multiple services at once. The problem is not just fake accounts. It is that many of the rules and safeguards used online were built for human behavior.
What kinds of solutions are being developed to address that?
There are several. Some are platform-based, such as verification systems run by individual companies. Others aim to create forms of digital identity that can travel across services rather than staying locked inside one ecosystem.
One important area is proving personhood, showing that someone is a real human without necessarily exposing more personal information than needed. Another is issuing credentials that confirm a specific attribute, such as reputation, authorization, or ownership, in a way that can be checked later. Pantera has invested in a number of projects exploring these approaches, including TransCrypts. The startup enables consumers to own verified employment and income credentials and share them instantly, free, and compliance-ready, saving millions of hours across the verification pipeline every year.
Additionally, World, a Pantera-supported, private, proof-of-human technology which uses biometric verification, reports having verified 18 million users, indicating real demand for ways to tell whether an interaction involves a person or a machine.
How does blockchain help with that?
It offers a way to create records that are difficult to alter and easy to verify. Instead of asking one company to hold all the relevant identity information and vouch for it every time, blockchains can allow credentials to be issued once and checked whenever needed.
In practice, that could mean proving that a user is human, that an agent is authorized to act on someone’s behalf, or that a participant has established a history of reliable behavior. Because the record can be verified independently, trust does not have to depend entirely on a central gatekeeper. That is especially useful in environments where interactions cross platforms, happen frequently, or involve actors that do not fit neatly into traditional account systems.
Why does this become more urgent as AI systems begin to act autonomously?
Once software starts doing things on its own, identity stops being a static label and starts becoming part of how activity is governed. If an AI is accessing services, making purchases, or interacting with other systems, someone needs to know what it is allowed to do and on whose authority.
That raises a different set of questions from the ones the internet had to answer in the past. It is no longer just, “Is this account real?” It is also, “Is this actor authorized?” “Can it be trusted?” and “Can its behavior be verified after the fact?”
How does this connect to payments and transactions online?
Payments are one of the best examples of why identity matters. If software is buying access to compute, data, application programming interfaces, or other services, the other side needs some way of knowing what it’s dealing with and whether the actor is legitimate.
At the same time, the payment system itself has to work for that kind of activity. Many transactions between automated solutions are small, frequent, and tied directly to usage. That is very different from the traditional world of accounts, cards, and larger human-led payments. High-throughput blockchain networks such as Solana, a platform we’ve invested in, are designed to enable this kind of activity, allowing fast, low-cost transactions at high volumes.
As a result, identity and payments start to converge. The ability to verify an actor, define what it is allowed to do, and let it pay for services in real time becomes part of the same problem.
Are these ideas still mostly theoretical, or is there evidence of real use?
On the identity side, some systems are already being used to confirm humanness or issue credentials that can be checked later. On the transaction side, Solana handles thousands of transactions per second with more than 500 billion total transactions since its launch in 2020.
The most important thing is that these tools are being tested in live environments, not just in theory. As AI-driven activity increases, the need for reliable identity and verification will grow rapidly.
How might identity and trust online evolve as AI use grows?
Trust is likely to become less tied to individual platforms and more built into how interactions work online. Users may be able to prove who or what they are across different services rather than relying on a single provider to verify them.
That could include clearer ways to confirm whether an actor is human, credentials that carry across platforms, and built-in verification for actions taken by software. Over time, the most effective systems will be the ones that fit naturally into everyday digital activity rather than adding extra steps.
References to any companies contained herein are provided for illustrative purposes only and do not constitute an investment recommendation.