Change in the live production industry is being pushed from two sides: economics and audience reality. Budget constraints and new technology are driving the most change, while multiplatform delivery and audience expectations are applying pressure to adapt daily workflows.

A lot of barriers to producing content have vanished. In the past, broadcasters had the advantage of scale, but live production has been democratized to some extent. That’s a big driving force.

Near term, respondents believe those drivers will materialize in their workflows as AI-powered automation and decentralized production teams, enabled by hybrid-cloud production platforms with improved latency and connectivity.

This mix reflects the pragmatic play demanded by budget constraints: move to cloud compute where it enables elasticity and reach, and add assistive AI to multiply output per operator.

Our experts broadly agree that the pressure to do more with the same resources will drive us towards more assistive automation and distributed productions enabled by cloud-native tools, better connectivity, and orchestration that doesn’t turn every show into a science project.

Looking further out, our survey respondents chose “IP overtakes SDI” as the decade’s defining change, followed by “AI as a production assistant” and a “transition to more distributed teams using software-defined tools.”

Respondents charted a path where the plumbing of live production will evolve to enable more software-defined production tools and AI assistive-automation, which is consistent with the responses on AI that we expand on later.

Producers are under no illusions, with budgets favoring the plumbing and the people that use it. IP-based media transport was the biggest investment priority for our respondents, followed closely by training and upskilling.

Efficiency levers like remote or decentralized production, AI-assisted tools, and orchestration automation also tie directly to the change drivers we saw earlier. Storytelling enablers like graphics, data visualization, and Augmented or Virtual Reality are more targeted investments.

Participants forecast a substantial but not total shift to cloud-based production, aligning with the hybrid end-state theme. Around half believe that the majority of workflows will be cloud based.

This is consistent with the growing desire for burst capability and portability, but we can expect edge hardware to persist wherever timing, bandwidth, or human performance are decisive factors.

Despite that substantial shift, we are not quite ready to bridge the gap to cloud. Less than a quarter of respondents believe they could run a totally virtual production today. There’s still caution about virtualizing critical infrastructure, particularly from top-tier properties.

The “edge stays physical” signal is explicit. But we expect the lines between on-prem and cloud to blur, with operators adapting workflows to each show’s demands.

Performance-critical and latency-sensitive productions are likely to lean on local hardware and talent, while more basic infrastructure and content services are likely to become increasingly virtualized.

Respondents expect pressure on traditional video infrastructure, with on-prem hardware for control and creative becoming less common. However, a meaningful segment expect all these technologies to remain part of our workflows, reminding us that technology persists when it solves a problem elegantly.

AI is beginning to find a home in day-to-day production. Right now, metadata and clip tagging are the most common uses, with some early moves in templated graphics and captioning, but it’s important to point out that almost half of respondents aren’t using AI at all yet.

The areas predicted to benefit most from AI map directly to the demands of multiplatform publishing: translation, captioning, metadata, and replay packaging. These are the workflows that determine how quickly a production can version, push, and personalize content for different audiences.

Operators will likely benefit most when AI integrates into familiar control surfaces, until eventually it is just another tool running in the background that enables them to do more, aligning with the theme of more consolidated, multifunctional roles.

Concerns around AI lie in exactly where you might expect: Reliability in live settings, displacement, ethical concerns, and loss of creative control. Only a small group reported no major concerns.

Provenance is another underpinning theme. It’s already increasingly difficult tell what content is genuine, so brand perception and establishing trust will likely matter as much as the technology powering it. Although there’s currently no clear path to establishing provenance, the need for a solution is paramount.

While nearly two-thirds of respondents agree that sustainability is important, the majority are not making key decisions based on sustainability alone.

That pattern is consistent: teams optimize for cost, reliability, and output first. But as we saw earlier, sustainable infrastructure is a priority investment for over 17% of respondents, reflecting outcomes-driven investment rather than blanket sustainability efforts.

An increasingly remote, distributed workforce reduces travel costs and environmental impact. Hybrid productions with shared compute or memory resources could also drive sustainability gains, which may be required to balance the huge energy costs of AI-workloads.

Looking across the data, there’s very little appetite for “big bang” reinvention. Production teams aren’t chasing the shiniest object. They’re looking to modernize the foundation: move only what makes sense to IP, lean into hybrid operations for elasticity, and bring in AI where it helps them process data and ideate faster, and version content without doubling the workload.

They’re just as clear that many operations like live switching, robotics, storytelling, and editorial judgement stay in human hands. The most successful operations will be the ones that treat new technology as scaffolding for creativity, rather than a replacement for it. Over time, those capabilities become part of the fabric: operators still direct shots and stories, but the system around them takes care of the heavy lifting.