Why You Should Automate Your Post-Production Workflow with AI

According to Nielsen’s estimates for the 2018-19 TV season, there were 119.9 million TV homes in the US. During the 2018 FIFA World Cup, a combined 3.572 billion viewers tuned in – more than half of the global population aged four and over. Driven by digital, the television industry is quickly expanding, including boosts in TV viewership in developing countries. Add to this, digital media is no longer just an additional distribution platform. It is quickly emerging as one of the big revenue generation engines.

[“Gen Z and Millennials are more likely to watch TV across multiple devices and outside of typical peak TV hours.” Source: GlobalWebIndex, “The State of Broadcast TV in 2019”]

With changing consumer appetites, new platforms and growing demand, there is an increased need for all-encompassing technologies like artificial intelligence (AI) and machine learning (ML) to augment traditional media models. The broadcasting companies who harness these technologies are finding even greater success.

THE INCREASING NEED TO STAY RELEVANT

A recent Deloitte study found that US consumers now pay approximately $2 billion monthly for subscription-video services. And the technologies and capabilities needed to compete with these dominating digital media services are more diverse and agile than ever before. For instance, Netflix employed AI efficiently in its recommendation engine, reducing routine workload through automation. Since AI efficiently organizes and manages content, it helps solve significant issues due to unstructured video and audio data. From navigating through a bewildering mass of online content to personal recommendations, AI helped impact Netflix’s customer preferences. The company saved around $1 billion per year with the smart engine’s ability to reduce customer churn.

The Broadcasters’ Ultimate Guide to AI-Assisted Production

Like in the example above, AI and ML are critical components of any successful digital media strategy. The broadcast and media companies adopting AI/ML into their organizations are already benefiting from streamlined operations. This optimization affects every stage of the production workflow, from content creation to distribution, to build a complete viewer experience.

DRAWBACKS OF MANUAL POST-PRODUCTION WORKFLOWS

Often post-production teams are given increasingly large workloads and expected to deliver content in shorter time frames – and most of them are still relying on manual workflows. Under these constraints, they are forced to choose between missing deadlines, producing lower quality work, or streamlining processes to make the content compliant with IMF/OTT standards.

Each OTT platform requires content adheres to their custom specifications. Even a single error in a file or misaligned audio results in the rejection of the entire content package. To this end, it’s vital for broadcasters to make sure distributed content meets conformance requirements for all devices, channels, languages, and additional formats to support new form factors, which are emerging all of the time.

From the audience perspective, there are latency and bandwidth considerations as well. Content owners must ensure visual assets are smooth and accurate. Traditionally, all of these quality assurance processes lead to an increased need for manual resources, thus, leading to higher costs and operational inefficiencies.

<< Get the calculator to see how much you could improve in ‘The Broadcasters’ Ultimate Guide to AI-Assisted production here >>

AUGMENTING POST-PRODUCTION WITH AI

AI can automate up to 80% of manual processes, leaving employees open to manage strategic and creative tasks. This equates to hours saved from manually going through content to identify problems or compliance issues. A workflow augmented with AI can provide richer metadata for each scene and shot. It can also pinpoint potential discrepancies. Instead of sacrificing quality and missing deadlines, teams can now leverage AI to improve the core stages of their workflows.

ENHANCED CONTENT CREATION

AI allows for quick production of deliverables. As well as options to incorporate custom fixes to smooth out bumps in the workflow, it also adds new capabilities to editing tools. Content owners are enabled to narrow the gap between skilled and semi-skilled creative editors while adding more detailed tags and properties.

Data-heavy TV shows can also use AI to automate and speed up much of their backend work. Production houses can then keep up with the growing demand for content from global audiences. As AI promises to enhance human content creation and eliminate the guesswork of TV and film, it also presents new business opportunities for creative professionals who are willing to adapt to advanced technologies.

FUTURE-PROOF YOUR MEDIA BUSINESS

AI has already significantly impacted the media landscape, and it’s showing no signs of slowing down. Soon AI will be at the center of the media industry as a key force driving the creative process and audience behaviors. The media companies who continue to invest in AI will be at the forefront of this transformation. Those who adopt the technology will benefit from increased efficiencies and a better understanding of their customers – leading to an overall boost in customer loyalty and revenue.

It’s time to make your post-production even better with AI. Download our “Broadcasters’ Ultimate Guide to AI-Assisted Production” to get started.

The Broadcasters’ Ultimate Guide to AI-Assisted Production

AI-POWERED SMART WORKFLOWS

Smart Workflows is an AI-assisted end-to-end automation managed service for content transformation and QC processes leveraged by broadcasters, production houses, and content aggregators across the media supply chain. This integrated, modular and scalable solution based on active learning workflows enables effective utilization of the workforce providing an ability to adapt to changing demands in media production, faster speed to market and accelerated readiness for OTT and international distribution.

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