The creator economy doesn't have a scale problem, it has an evidence problem
The figure is tempting: $480 billion by 2027, according to Goldman Sachs. A market that within four years would double the size it had in 2023. The most aggressive projections speak of surpassing one trillion dollars by 2034. With those numbers on the table, any boardroom wants a slice. The problem is that no one can say with certainty exactly what they're buying.
That is not an operational detail. It is the structural fracture of the entire industry.
Agung Dwi Sandi, founder of rankpillar Group and frequent voice on the Forbes Technology Council, recently articulated this with a precision worth retaining: the central problem brands face is not a lack of creators, but the high cost of trust. The phrase sounds simple, but it conceals a reality that marketing departments have spent years patching together with spreadsheets and subjective judgment. The market has millions of players, growing budgets, and increasingly sophisticated monitoring technology. What it lacks is any certainty about whether what it measures represents something real.
That tension — between data visibility and opacity about its authenticity — is the core of the debate that Sandi opens. And it is, curiously, one of the few diagnoses of the sector that holds up to scrutiny without requiring anyone to buy anything from it.
What the seven-figure budget cannot verify
When a brand allocates a seven-figure budget to a campaign with opinion creators, it is not buying reach in the technical sense of the term. It is buying access to a community perceived as real, engaged, and aligned with its values. The nuance matters because that perception can be completely false without any metric on the campaign dashboard revealing it.
Bot farms are not a marginal anomaly. AI-generated digital personas can simulate human behavior with sufficient fidelity to deceive both platforms and brands. And the ecosystem of vanity metrics — followers, likes, and declared reach — was designed to capture attention, not to verify commercial impact. The result is what Sandi calls the illusion of influence: more data than ever, less certainty than ever.
This is not abstract. It has concrete financial consequences. When marketing teams cannot causally connect a post with an increase in conversions, investment in creators remains in a questionable accounting category: too large to ignore, too opaque to optimize. The CMOs who have scaled these budgets over the past five years have done so largely on the basis of correlations, not causality.
The sector continues to operate, in Sandi's words, on manual spreadsheets, unverified screenshots, and "vibes." The word is colloquial, but the description is accurate. And if one adds to that the fact that the performance data of a single creator is fragmented across platforms, agencies, and past campaign files with no unifying thread, the picture that emerges is not that of a mature $480 billion market. It is that of a market that invoices like an adult but operates with the infrastructure of an adolescent.
The leap the sector has yet to make
The proposal articulated in Sandi's article can be distilled into a single underlying idea: we must stop treating creators as independent service providers and start treating them as infrastructure within the marketing value chain. The language may sound grandiose, but the mechanics behind it are more mundane — and more demanding — than they appear.
The analogy the author uses is helpful for understanding the maturity leap being described. The early years of the internet operated on IP addresses: technical identifiers, machine-readable, invisible to the user, and with no trust architecture behind them. DNS was not a magical invention. It was a governance layer that made the system navigable, scalable, and verifiable. The creator economy is still in its IP-address phase. It has millions of players identified by their social media handles, but it has no system that answers the question of whether that handle corresponds to who it claims to be, with the audience it claims to have, and with the performance history it presents.
The protocol Sandi proposes is structured around four components. First, a verified identity registry: a canonical profile per creator, with cross-platform authentication via official APIs — not screenshots. Second, a performance ledger that records metrics such as CPM, CPA, and conversion rates associated with the creator's identity, rather than scattered across past campaign files. Third, an audience quality layer with updated signals on authenticity, including bot ratios, geographic alignment, and estimated purchasing power. And fourth, a compliance column that centralizes contracts, disclosures, tax documentation, and brand safety verifications, portable across each collaboration.
From a data architecture perspective, none of these components is technologically impossible. Some already exist in fragmented form across influencer marketing platforms. What does not exist is the articulated whole — governed internally by the brand and treated with the same discipline as CRM data. That is the operational gap Sandi identifies, and it is, in all likelihood, harder to close for political reasons than for technical ones.
Internal friction and the real problem of adoption
This is where the diagnosis begins to reveal its less comfortable face. Implementing a unified identity layer for creators is not a product problem. It is a problem of internal governance and the alignment of incentives among brands, agencies, and platforms.
Large brands typically have multiple teams with their own creator lists, their own tools, and their own definitions of what counts as a performance metric. Consolidating all of that into a single database with a canonical identifier per creator requires forcing a conversation about who controls that asset, what data is shared between teams, and which agencies need to adapt their delivery workflows. Sandi acknowledges this explicitly: resistance must be anticipated. Teams defend their lists. Platforms measure engagement differently and have no incentive to standardize outward. Agencies have less interest in submitting to stricter data delivery standards unless contractually required to do so.
That friction is not an implementation detail. It is the variable that explains why the market has spent years producing the same diagnosis — more fragmentation, more opacity, more spend based on perception — without the technical solution materializing at scale. Sandi's proposal is coherent in its architecture. Its weak point lies in the fact that adoption depends on brands exercising sufficient purchasing power to impose standards on agencies and platforms. And many brands, even those with seven-figure budgets, have not built that negotiating position because they have delegated creator management almost entirely to intermediaries.
The case for building in-house creator data management capabilities is, fundamentally, a case for reducing dependency. Whoever controls a creator's performance history controls the reinvestment decision. Whoever delegates that to an agency negotiates at a disadvantage each time a contract is renewed.
There is an analogous pattern already documented in the programmatic advertising market. For years, brands delegated digital media buying to trading desks and DSPs without visibility into margins, real inventory, or actual efficiency. When some large brands decided to internalize capabilities and demand contractual transparency, the business models of many intermediaries were exposed. The creator market is several cycles behind that point of maturity, but the underlying mechanics are the same.
Identity is not an authenticity solution, it is a business condition
It is worth separating two readings of the same problem, because they have distinct implications for those making budget decisions.
The more widely circulated reading presents the identity layer as a response to the authenticity crisis: bots, synthetic personas, inflated metrics. It is a valid reading, but it situates the problem primarily on the supply side — with creators who misrepresent themselves or with platforms that enable fraud. That reading produces defensive solutions: detection tools, audience audits, blacklists.
The more uncomfortable reading — which Sandi's analysis gestures toward without fully articulating — is that the problem also exists on the demand side. Brands have been willing to invest without demanding verification because creator spend historically served diffuse objectives of brand awareness or affinity, where measurement difficulty was convenient for everyone. If impact is hard to measure, it is also hard to question. That shared comfort among brands, agencies, and creators has sustained a market built on narrative rather than evidence.
What changes when a brand builds a performance ledger is not only the ability to detect fraud. It is the ability to demand accountability and, with that, to renegotiate the terms of the market. A creator with a verified track record of demonstrable conversion is worth more than one with millions of followers and zero impact data. That difference in value should translate into a difference in price. But as long as the market lacks the infrastructure to sustain that distinction, it will continue to pay rates based on declared reach — which is the metric easiest to inflate and the least relevant to any measurable business objective.
The underlying argument is structural: the identity layer is not primarily an anti-fraud tool; it is the minimum condition for the market to be able to assign prices on any technical basis whatsoever. Without it, the marketing budget remains a transfer of value from brands to intermediaries and creators, with scant certainty about which portion of that transfer produces verifiable commercial results. With it, the industry could begin to operate with the same discipline it has applied for decades to other digital acquisition channels.
The $480 billion market does not have an ambition problem. It has a verification infrastructure problem. The brands that choose to resolve that problem internally — before some external standard compels them to — will not only gain efficiency: they will gain the scarcest asset in the sector, the ability to know what they are buying.
