Media companies are finally getting serious about artificial intelligence… by focusing on the bottom line
The executives who gathered in Amsterdam for September’s Devoncroft Summit spoke in a language that would have been foreign at previous broadcasting conferences: activity-based costing, workflow orchestration, and FinOps discipline. The shift from discussing AI’s creative potential to its operational necessity signals that the media’s technology transformation has entered a new, more serious phase, less Silicon Valley evangelism, and more fiscal responsibility.
The transformation reflects harsh economic realities. Production volumes are down 20-30% in some segments, according to service providers at the conference. Meanwhile, advertising revenues remain under pressure and audiences demand content delivered faster across more platforms than ever. In this environment, AI’s appeal lies not in generating flashier graphics or more compelling storylines, but in automating the complex workflows that currently require significant human oversight to move content from production to screen.
Follow The Money
The applications attracting genuine investment bear little resemblance to the generative AI tools that dominate technology headlines. Instead, broadcasters are focusing on what industry insiders call «orchestration.» Orchestration means software systems that can automate the mundane but critical tasks of moving content through production pipelines. These include logging footage, transcribing interviews, ensuring regulatory compliance, and reformatting content for different platforms. In essence, orchestration serves as the invisible conductor of modern broadcasting, automating repetitive processes so humans can focus on creativity and strategy rather than shepherding files between systems.
The economic logic is compelling. A typical broadcaster might employ dozens of people whose primary job is managing content between different systems. Each handoff represents both a potential bottleneck and a source of human error. AI orchestration platforms promise to automate these transitions while providing what executives now consider essential: detailed visibility into costs.
This emphasis on financial discipline, dubbed FinOps in the industry, represents perhaps the most significant cultural shift in broadcasting technology. Leading broadcasters report achieving 10-15% annual efficiency improvements by embedding cost accountability directly into engineering decisions. The approach involves tracking expenses down to individual workflows, creating what amounts to activity-based costing for media production.
«There is nothing more important to unlock media technology budgets than FinOps,» said one executive, capturing the summit’s prevailing mood. The statement would have seemed absurd at previous conferences, where technical prowess and creative capability dominated discussions.
The Hybrid Reality
This newfound financial rigour is reshaping how media companies approach cloud computing. The pandemic-era rush to cloud infrastructure has given way to more calculated hybrid strategies. Mission-critical live operations, including covering elections, sporting events, and breaking news, remain largely on-premise due to reliability concerns. Meanwhile, routine production tasks migrate to cloud platforms where costs can be optimised and scaled dynamically.
The shift creates opportunities for a new category of vendors focused on orchestration rather than individual applications. These companies promise to integrate dozens of media software tools without requiring extensive custom coding, essentially providing what amounts to an operating system for modern broadcasting operations.
The Automation Dividend
For viewers, these changes may be largely invisible. The content they consume will still depend on human creativity and editorial judgment. But the infrastructure delivering it will increasingly run on algorithms designed to minimize costs and maximize efficiencies.
The implications extend beyond broadcasting. Media represents one of the first major industries where AI is moving from experimental applications to core operational infrastructure. The lessons learned, both successes and failures, will likely influence how finance, retail, and other industries approach similar transformations.
Consider the economics facing Versant, the newly spun-out division of NBCUniversal comprising MSNBC, CNBC, Golf Channel and several entertainment networks. The company must separate from its parent, optimize operations, and build new direct-to-consumer capabilities within 24 months. Its strategy emphasizes activity-based costing «down to operator level» and replacing «bespoke, over-customized systems» with standardized, interoperable alternatives.
The Discipline Dividend
This unglamorous work of process standardization and cost visibility may prove more transformative than any individual AI application. By treating technology spending as an operational discipline rather than a creative investment, media companies are positioning themselves to make more rational decisions about where automation can genuinely add value.
The irony is palpable: an industry built on storytelling may find its most important story in the quiet automation of the machinery that brings stories to screens.
The accountants, it seems, are having their revenge.
