Agility, automation and AI are key to launching faster, reducing TCO, and accelerating innovation for broadcasters and operators.
From content creation to distribution, established ways of working are being challenged. We are no longer living in a linear paradigm of occasional improvements coming once or twice a year. Now we live in one of constant change. The five-year roadmap has now become a five-month roadmap at best.
In this new media landscape, companies cannot afford long release cycles or slow decision-making. Agility is critical, and the ability to iterate quickly, adapt to change, and roll out updates continuously is essential. The platforms and services that can launch, upgrade, and innovate faster will be the ones able to seize new opportunities and maintain relevance in an AI-disrupted market.
It’s not just about consumer-focused advances either. These create neat headlines but, if anything, it is the acceleration of internal processes that is becoming more critical as companies turn a laser focus onto their bottom line. The imperative is to reduce TCO (Total Cost of Ownership) and maximise operational efficiencies. The media companies that can adopt and adapt to the new paradigm of accelerated software development lifecycles will be able to develop faster, iterate quicker, and reduce TCO at greater speed. This will give them a significant competitive advantage.
There are three main pillars to being able to deploy faster, whether we are talking about external services or internal development tracks. These are Agility, Automation, and AI.
Agility - This provides the engine of the new approach. Rather than seeing upgrades as annual events, an agile model sees organisations shifting to shorter release cycles with faster rollouts and a constant, rolling process of improvement.
Automation - Automation adds the means to rapidly scale. The idea is to develop and standardise deployment blueprints within an organisation and then align workflows according to these templates during updates. A game-changing degree of automation can then be brought to the upgrade process, which simplifies complexity and helps to eliminate the chances of human error. Templatized deployments, allied with CICD toolchains, cloud native architectures, and next generation software deployment methods such as Canary and Blue-Green can scale across infrastructures. This supports testing in production, leading to a faster release cycle with reduced risk of disruption.
AI - While the headlines regarding GenAI in particular have tended to concentrate on creative use cases such as content generation and personalisation, there is an equally important story developing in the background. AI is adding further impetus to the whole Launch Faster process, in particular via the introduction of the AI-aided software development lifecycle (SDLC)
AI transforms the SDLC by automating tasks, accelerating development, and improving quality across all phases, from requirements gathering and design, to testing, deployment, and maintenance. In short, AI tools enhance productivity, streamline workflows, and enable better and faster application deployment.
This is important, and not just for competitive means. As an example, the introduction of new regulations such as the NIS2 in EU will make it necessary to modernize tech stacks and replace deprecated, vulnerability-riddled software components. An increasingly active regulatory environment combined with accelerating progress and market pressures means that the constant, iterative improvement of technical stacks is becoming mission critical.
At Viaccess-Orca (VO) we foresee a future where systems in place at broadcasters and operators are composite architectures that combine the flexibility of a microservices approach with the stability of legacy, often monolithic systems.
This is a key point. A pure microservice approach is not always a fit for the broadcast industry. Service providers should adopt pragmatic architectural designs that offer the best of both monolith and microservices worlds. The importance of legacy in TV service provider systems has to be acknowledged. While monolithic systems are harder to maintain, they remain robust and reliable, providing the foundation service providers need to cope with peak time traffic. It would be extremely unwise to compromise system stability, scalability, and optimization purely in the name of speed and faster deployments.
The 3 ‘A’s outlined above can contribute massively to converting this architecture approach into future-proof reality. The goal is to launch faster but not to imperil company operations while doing so, so at VO we see modernization rather than wholesale replacement as the key to updating platform software components in the current environment.
Media companies will gain from partnering with vendors that master the modern, AI-aided SDLC, reducing technical debt and freeing engineering teams to focus on higher-value innovation. What is interesting to note is that we are only at the start of this journey, with much interest being shown in autonomous agentic AI systems. These will increasingly take over complex maintenance tasks, such as replacing deprecated software libraries.
We are working to make it even faster as well, providing tools to let broadcasters and operators automate deployments to get to market faster than ever before and with tools that are improved continuously. Indeed, continuous AI-supported deployment of new and/or optimised features could perhaps be one of the most profound changes in how TV and video platforms operate since the advent of the digital era.
This aligns extremely well with the broader industry need for agility, adaptability, and resilience in a market where disruption is rapidly becoming the new normal rather than the exception.