Brad Danks | CEO, OUTtv Media Global
Part 4 of 7 – CARTT Series: Beyond the Walled Garden
Artificial intelligence doesn’t solve Canada’s media problem – it reframes it.
For decades, Canada’s structural challenge wasn’t a shortage of creative talent, it was the limitations of a small domestic market. The US dominated global television because its domestic revenues were large enough to support production values that travelled. Canada couldn’t match those economics, but Canadian content did find international markets when funded by the Walled Garden cross-subsidy. Profits from US content (supported by concentration of ownership and vertical integration) flowed into Canadian broadcasters and supported Canadian production. That system worked.
What’s breaking it now is a two-sided squeeze: streaming is eroding the linear revenues that funded the cross-subsidy, while simultaneously opening new international distribution opportunities and expanding global revenue streams for Canadian content. The government has been topping up the CMF to offset the shortfall, keeping the system functional, but also preventing the underlying problem from being addressed.
AI accelerates both pressures at once: it further erodes the economics of the old linear model while collapsing the cost of production, localization, and reaching global audiences. The opportunity is real and growing. But capturing it requires paying more attention to export – toward the expanding markets that streaming and AI are opening – rather than patching a funding model whose commercial foundation is crumbling.
But AI is also creating a new challenge. Making things gets cheaper and easier – for Canadian creators and for everyone else. AI can democratize creativity, but it won’t democratize audiences, revenue, or ownership.
The issues from the first three articles – misaligned incentives, diffusion failures, the content trap – aren’t new. AI didn’t create these problems, but it will make the cost of ignoring them much higher. The right systems will build on their advantage, while the wrong ones will fall behind faster than ever.
This is the real AI equation for Canadian media: it’s not about using new tools, but about steering the whole system toward where value is going. The direction is clear. The real question is whether Canada will be ready for it.
AI isn’t here to replace creators – it’s here to replace inefficiency. That makes it even more costly to keep supporting a system that’s out of sync.
From Scarcity to Abundance – and a New Problem
The shift isn’t happening everywhere at once. Shooting with cameras, sets, and on-location talent is still largely unchanged for now. But everything that turns a Canadian show into a global asset is already getting cheaper: localization, dubbing, subtitling, versioning, post-production, metadata. Companies at the distribution layer are already seeing it in their numbers. The barrier that kept Canadian content local is giving way. But what replaces it isn’t automatic global reach – it’s a new problem. As production costs fall and content volume rises, the bottleneck moves. The scarce resource is no longer the content itself. It’s getting found.
More Canadian content will be produced – AI lowers the barriers for everyone. But without redesign, that abundance works against Canada: volume increases while value retention declines. A system still directing capital primarily toward production is compounding a structural problem with diminishing resources. Individual productions can succeed brilliantly, but the audience relationship is the asset that compounds across them. The current system funds the former and underinvests in the latter.
Where Scarcity Moves
Technological change in media has always followed a recognizable pattern: new technology lowers production costs, supply expands, and economic value migrates away from production toward whoever controls the emerging bottleneck. In the broadcast era, scarcity lived in the spectrum and channel carriage. In the streaming era, it moved to platform relationships and recommendation algorithms. In the AI era, it is migrating further – toward IP ownership, distribution intelligence, and audience data.
AI is reducing the marginal cost of tasks that previously required scale: localization, dubbing, subtitling, versioning, marketing asset production, metadata generation – the tagging and classification that determine whether content surfaces on global platforms or disappears into the catalogue – and audience analytics. What once required a large team or a large budget now requires infrastructure and good data. This is not a future scenario. It is happening right now across the industry.
A Canadian company without visibility in those systems doesn’t just have a discovery problem, it has a monetization problem. Content that AI systems can’t find, classify, or surface doesn’t generate audiences or revenue, regardless of its quality. Metadata infrastructure is the new distribution layer: how content is tagged, classified, and indexed determines whether it reaches global audiences or disappears into the catalogue. Learning to navigate that terrain – and investing in the capability to do so – is now a strategic imperative, not a technical afterthought.
Canadian companies are already demonstrating what this looks like in practice. OUTtv Media Global distributes across 16 countries on five continents with a team that would have been considered impossibly small just to run a single Canadian broadcast channel twenty years ago. AI is collapsing the cost barriers that once made global distribution impossible for smaller players. The gap between owning IP and not owning it is growing, and AI is accelerating that divergence.
AI as a Policy Instrument
For Canadian policymakers, AI creates something genuinely new: the ability to measure outcomes that were previously unobservable. Retention rates, repeat engagement, export penetration, catalogue performance, and learning velocity across titles – all of these can now be measured directly. The last technical excuse for relying on inputs rather than outcomes has disappeared.
Continuing to rely on spend-based metrics – dollars committed, hours produced, creative jobs filled – is no longer a necessity. It is a choice. A deliberate decision to measure inputs rather than outcomes, because inputs are legible to existing institutions and outcomes require new frameworks. That choice is becoming more expensive every year.
What AI Enables for Canadian Companies
The opportunity is real. For Canadian media companies, AI lowers the barriers to global participation without requiring the surrender of ownership. A Canadian streamer will soon be able to localize its catalogue to major markets worldwide at a cost previously prohibitive. It can run audience analytics across multiple territories, adapt formats for different markets, optimize metadata for AI-driven discovery, and manage SVOD (subscription video on demand) and FAST (free ad-supported streaming) channel operations across a dozen platforms – all with a fraction of the overhead that global scale previously required.
But the deeper shift isn’t operational, it’s strategic. When production costs fall and localization becomes cheap, the question stops being which single project to back. It becomes how many experiments to run, how fast to learn from audience response, and which signals to scale. That’s the opposite of how the current funding system works. Project-by-project assessment, multi-year development cycles, and single-title commissioning made sense when production was expensive, and failure was potentially catastrophic. In a world where AI enables many more shots on goal per dollar, a system built for caution isn’t just inefficient, it’s actively selecting against the behaviours that build lasting advantage.
Canada’s opportunity has always been at the edges – in the content that dominant platforms overlook and general broadcasters underserve. Schitt’s Creek found a global audience by being unapologetically itself. Orphan Black built a cult following across dozens of countries. Heated Rivalry proved there is an international appetite for queer storytelling. These are not accidents of quality. They are signals of underserved demand. Canada’s content strengths – multilingual, culturally specific, drawn from communities the algorithmic mainstream was never built to reach – travel precisely because of that specificity, not despite it. AI-enabled distribution makes the economics of serving those audiences viable in a way that simply was not possible even five years ago.
But AI-driven discovery cuts both ways. Recommendation algorithms are built for engagement and retention, not cultural diversity or national origin – which means owning IP and building distribution capability still isn’t enough if your content can’t be found.
The Institutional Gap
Other countries have already started acting on this. Finland explicitly recognizes that the line between technology company and media company has collapsed, and structures its R&D incentives accordingly. A Canadian streaming service building recommendation systems, audience analytics, and metadata intelligence is, by any reasonable definition, doing R&D. It just isn’t treated that way. That’s a policy choice, not a technical limitation. A media company that owns IP, builds audience intelligence, and runs AI-driven distribution is competing in the same layer as a technology company and should have access to the same kind of support.
The policy question is straightforward: Does the Canadian system reward companies for building this capability, or does it continue to reward the behaviours it was designed for in a different era? The answer to that question will determine whether AI accelerates Canadian advantage or Canadian irrelevance. Notably, Canada’s primary funding bodies have yet to integrate AI as a first-order strategic variable. The CMF’s 2026–2029 Strategic Plan – the institution’s defining four-year policy document – does not mention AI once. That is not a minor oversight. It is a signal about institutional readiness. The universe the CMF was built to navigate has shifted. The North Star has moved with it but the 2026–2029 Strategic Plan does not yet reflect that. A plan that doesn’t name AI isn’t neutral – it’s a choice. And it’s the same choice that has defined Canadian media policy for decades. That specific gap is examined in detail in a companion piece in this series.
In Brief
AI didn’t create Canada’s media problem. It made the cost of ignoring it much higher. As production costs fall and content volume rises, value redistributes – making things still matters, but ownership of IP, control of distribution, and audience intelligence increasingly determine whether that value stays in Canadian hands. Canada’s opportunity is real – but capturing it means pointing the system at where value is going, not patching a funding model whose commercial foundation is fading.
Brad Danks is CEO of OUTtv Media Global and an Adjunct Professor of Law at the University of Victoria. He is a frequent writer and speaker on the evolving media landscape. He represents OUTtv’s interests as a member of industry groups, including Beyond Mainstream – a global alliance of independent streaming companies advancing innovation and competition in digital media, and Streaming for Australia. Brad also sits on Numeris’ Board and is a faculty advisor at the Center for Digital Media in Vancouver.
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