2026 Outlook: Moments Lab’s Fred Petitpont on AI’s implementation gap and archive monetization

The broadcast industry stands at a crossroads between AI’s potential and its practical deployment. Fred Petitpont, co-founder and CTO of Moments Lab, sees 2026 as the year when this gap becomes the industry’s defining challenge.

Petitpont referenced comments from Jon Roberts, CTO of ITN, who described a disconnect between AI’s “genuinely transformational” potential and “the day-to-day practical experience” in production. Roberts noted that most production work continues without AI contributing significantly to core operations.

“The opportunity is massive: organizations that deploy production-ready agentic AI systems, not pilot programs, will unlock entirely new revenue streams from archive monetization while dramatically reducing time-to-air,” Petitpont said.

He added that success will belong to organizations that implement AI with clear human-in-the-loop frameworks rather than extended planning processes.

Why most AI projects will fail

Petitpont predicted that most broadcasters will not successfully integrate AI tools into workflows in 2026, despite financial investment. He identified three factors that will contribute to these failures.

First, teams expect AI to deliver improved results using the same limited data approaches, such as video search that relies on keywords and metadata. Second, some organizations may select AI tools that require substantial changes to media asset management systems or existing workflows. Third, broadcasters may lack the infrastructure to move on-premises legacy content into cloud environments for AI processing.

“Failure to address all of these three concerns will cause the downfall of many AI projects in 2026,” Petitpont said.

He noted that despite institutional failures, individual workers will continue adopting AI tools independently, citing an MIT report that describes a growing “shadow” AI economy.

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Petitpont also predicted that production companies will monetize archives more quickly than traditional broadcasters, converting cost centers into revenue sources. He attributed this to production companies operating with less legacy IT infrastructure and fewer compliance processes.

From efficiency to new capabilities

Petitpont said automation will shift from accelerating existing tasks to enabling previously impossible workflows.

“Gen AI and now Agentic AI are incredible productivity tools, but we tend to forget about creating new use cases,” he said. “It’s easy to make AI deliver on cost savings but we don’t spend enough time to scope out new possibilities.”

He identified fully autonomous AI video creation as overhyped, noting that removing human creative direction results in repetitive content and reduced audience engagement.

Petitpont said AI is transforming workflows through agentic content discovery that understands narrative context, multi-agent coordination in live production, archive-to-air automation and metadata generation. All these applications maintain human oversight.

Moments Lab’s customers have moved from evaluating AI capabilities to planning deployment at scale. Petitpont described three shifts in customer priorities: integration over innovation, with companies seeking workflow compatibility rather than standalone tools; compliance and governance over features, particularly regarding biometric data handling; and monetization over efficiency.

“They’re not asking ‘Can we search faster?’ but rather ‘Can we create 50 versions of this content for different platforms and demographics?'” Petitpont said.