Quality control (QC) has long been a gatekeeper of technical fidelity. Editors and technicians have adhered to a simple, disciplined checklist: bitrate, resolution, volume, and caption presence. The objective was to ensure every file met the specs that distributors require. But with the adoption of Artificial Intelligence (AI), a new requirement is emerging: authenticity. AI-generated or manipulated content enters professional workflows with increasing regularity, often indistinguishable from conventional material. Organizations must verify not only that a file meets spec, but that it can be trusted. QC is expanding from technical compliance to a broader mandate of trust verification.
Take the recent criticism of a social media platform AI chatbot. Its image-generation capabilities created non-consensual sexual and deepfake imagery of real people. So it's no wonder that a recent Gallup poll found that Americans' confidence in the media is at a new low, with just 28% expressing a great deal or fair amount of trust. This is down from 40% five years ago. While confidence levels vary internationally, global action is needed to rebuild trust and tackle disinformation.
Why authenticity now?
The urgency around authenticity is driven by several converging forces:
Tampering and synthetic content are more accessible and convincing than ever.
The low public trust in mass media elevates the consequences of even small missteps.
Enormous volumes of user-generated content amplify the risk of unvetted material slipping through.
Growing scrutiny around disinformation is prompting platforms, broadcasters, and regulators to demand verifiable provenance.
Archives and redistribution workflows increasingly require documented provenance to ensure long-term integrity and rights management.
Authenticity is now a core competency to protect brand integrity, preserve audience trust, and safeguard historical record. Authenticity becomes as operational as resolution or loudness: a functional requirement woven into day-to-day production and distribution.
Ensuring content provenance
Not everything is a deliberate deepfake. Andy Borowitz's satirical columns, The Borowitz Report, are frequently mistaken for real news. It may seem laughable, but a March 2017 column titled Trump Orders All White House Phones Covered in Tin Foil was picked up in print and online by China's Reference News, a publication of the state-run Xinhua News Agency.
AI models can provide false information with high confidence, rather than admitting they do not know. Helpful but incorrect answers can align with what models think the user wants, rather than neutral facts. AI tools often fail to accurately attribute or interpret information from reputable sources, blending context from unrelated, unverified, or satirical content.
Provenance is crucial for authenticity. The basic, trustworthy facts about a digital asset's origin, Content Provenance, is established by the Coalition for Content Provenance and Authenticity (C2PA). This open technical standard ensures each file includes:
Creation details: Who created the content, when, and under what conditions
Edit history: What changes were made, by whom, and when
Chain of custody: The lifecycle of the file through storage, transfer, and processing
Evidence of modification: indicators of AI usage, visual effects, or edits
This industry-backed initiative combats disinformation by providing provenance and clear signals about when an asset was altered. C2PA brings verifiable provenance into media workflows. That's why Telestream supports this standard and the C2PA ecosystem.
Closing the workflow gap: Introducing C2PA support
Even when C2PA metadata exists, validation at scale remains a major hurdle. Manual inspection is labor-intensive, slow, and unsustainable given modern distribution volumes. The gap lies in automated, scalable detection of missing C2PA metadata, invalid credentials or unsanctioned modifications, as well as tampered provenance data or inconsistent chain-of-custody signals.
QC checkpoints are the natural places to embed authenticity validation, ensuring every handoff from ingest to playout retains integrity. C2PA's promise is substantial, but an automation-first approach is required for high-volume pipelines.
Telestream Qualify is our award-winning solution that streamlines QC to accelerate content delivery. As part of its 2026 roadmap, Telestream is integrating C2PA metadata extraction and compliance workflows within Qualify.
Qualify will detect missing C2PA metadata and flag invalid or tampered credentials. Surface provenance insights alongside traditional QC checks, expanding QC to content trust. With these capabilities, Qualify becomes the first widely available File QC solution to contain C2PA Content Credential validation. In other words, authenticity is now a first-class consideration within QC, not an afterthought.
Part of a broader AI-powered QC evolution
Qualify's 2026 enhancements act as a second set of eyes across automated pipelines, catching issues that previously required human review, including:
AI-assisted speech and caption synchronization validation reducing manual reviews
Lip-sync AI capabilities (currently file-based with a live roadmap ahead)
Expanded codec and delivery format support to cover more pipelines
HDR validation and precise loudness monitoring for modern deliverables
Region-specific compliance checks to accommodate global requirements
Continuity across discrete assets and real-time streams for both file-based and live environments
Authenticity checks now complement established QC. Broadcasters and streamers can validate assets before distribution to mitigate risk and protect trust. News and sports organizations safeguard editorial standards by verifying all
