Industry Insights: Workforce transformation, challenges in AI usage – NewscastStudio

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Technology vendors examine how artificial intelligence affects workforce development and industry collaboration in this final installment of the Industry Insights roundtable on AI and emerging tech.

The discussion explores the evolving skill requirements for broadcast professionals as AI automation reshapes traditional roles. Industry experts address implementation challenges, from infrastructure costs to staff training needs, while highlighting the importance of partnerships between broadcasters and technology developers.

The conversation also examines often-overlooked aspects of AI integration, including ethical considerations, data governance and the need for clear standards in handling AI-generated content.

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Key takeaways from this Industry Insights roundtable

• Workforce evolution: AI automation of routine tasks creates opportunities for broadcast professionals to focus on creative work and develop new technical skills.
• Training: Organizations must develop comprehensive training programs and foster a culture of continuous learning to help staff adapt to AI-driven workflows.
• Implementation: High costs, technical complexity, and lack of specialized expertise remain significant barriers to AI adoption in broadcast operations.
• Collaboration: Direct partnership between broadcasters and technology developers enables creation of practical solutions that address real-world production challenges.
• Standards: Industry requires clear frameworks for data governance, ethical usage, and intellectual property rights related to AI-generated content.

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What impact do emerging technologies have on job roles and skills required in production teams?

Bob Caniglia, director of sales operations, Americas, Blackmagic Design: The goal of AI-powered technology should be to empower creativity, not replace creatives. By using AI and machine learning to streamline workflows and eliminate repetitive tasks, production teams will have more bandwidth to learn new skills and focus on the creative aspects of the job, including storytelling. Time is a scarce resource in the broadcasting world, and these tools help make it more plentiful.

Ken Kobayashi, business manager, Sony Electronics: It can be challenging to hire skillful camera operators in a short period or train existing operators in a short period. AI-powered camera tracking is becoming more and more accurate and trustworthy, with enhanced automated capture options like tracking multiple people or registered face tracking, which supports higher production values, provides additional engagement, and simplifies operation.

Costa Nikols, strategy advisor, media and entertainment, Telos Alliance: The rise of AI and machine learning places new skills demands on production professionals. While traditionally manual-intensive processes like quality control can be assisted by machine learning tools, users are beginning to take ownership of more data-driven tasks that require them to engage with, and understand, new data outputs and manage automated and virtualized workflows. This evolution demands a blend of digital-ready intuition and deep technical expertise — teams should blend forward-thinking technology adoption with trusted, reliable systems to carve a balanced innovation roadmap.

Simon Parkinson, managing director, Dot Group: Technology is meant to facilitate jobs and automate a lot of the mundane activities, so that employees can be freed up to work on more complex or creative tasks. Technology must shrink the skill gap rather than widen it in order for businesses to make the most out of their technological investments. Many technologies, especially within AI, are focused on the user, thus designed to work alongside the colleague, rather than instead of them, helping businesses to scale and truly make the most of their AI investments.

How can broadcasters prepare their workforce for these new tools and technologies?

Peyton Thomas, product manager, Panasonic Connect: Broadcasters can prepare their workforce for new tools and technologies by adopting software-defined platforms and new transport protocols like ST2110 today. The industry is moving to network-based solutions and broadcasters should start implementing these emerging solutions from manufacturers and the AI technology will closely follow in development.

Bob Caniglia: Promoting continuous education ensures teams can keep pace with technological advances and the latest updates, building confidence and expertise in adopting these solutions. Additionally, encouraging a mindset of innovation and adaptability empowers staff to creatively leverage new tools, enhancing production quality and efficiency as new products come to the market.

Jordan Thomas, marketing manager, QuickLink: The most effective way to prepare workforces for new tools and technologies is to provide hands-on training with platforms, highlighting how these tools streamline the efficiency of often mundane and difficult tasks. At QuickLink, we are committed to providing up-to-date information on the QuickLink Knowledge Base and University tools — available 24/7 for broadcasters to fully prepare, train and educate workforces.

Steve Taylor, chief product and technology officer, Vizrt: Building awareness and trust is important for any new technology or tool. There is a lot of hype about AI replacing nearly every human in the creative workflow, and that naturally makes people nervous or defensive. Seeing it as more of an enabler, or “time generator” — speeding up the less interesting or repetitive parts of the creative process and leaving the content creator to focus on the compelling storytelling — is a more positive way of looking at how it can benefit teams in broadcast.

How will AI and other emerging technologies further impact jobs in the industry?

Jordan Thomas: While some roles may become redundant due to advancements in AI, new opportunities will emerge in areas like AI management, content optimization, data analytics and virtual production. Platforms like QuickLink StudioEdge and StudioPro are already reshaping the skills broadcasters need for the future.

Noa Magrisso, AI developer, TAG Video Systems: AI and emerging technologies will reshape broadcasting roles, shifting the focus from manual tasks to strategic expertise in AI tools. By automating repetitive tasks like transcription, AI frees professionals to concentrate on creativity and strategy, while also leading to the emergence of new, specialized roles, such as AI operators and machine learning engineers. This shift necessitates adaptability and ongoing skill development to ensure professionals can effectively develop and implement AI solutions.

Simon Parkinson: Whilst there is hesitation around AI impacting the job market, the reality is that there will be a shift in the job market that will result in new jobs being created within the information sector. According to the World Economic Forum, by 2025, it is expected that 85 million jobs may be displaced by automation, as well as the creation of 97 million new jobs, with data and AI, content creation and cloud computing as a large portion of those job creations. As media continues to be consumed through different channels, the most popular at the moment being short-form content, the potential for AI-powered enhancements creates more promise for the industry rather than concern.

What are the training and development strategies for staff in adopting new technologies?

Kathy Klinger, CMO, Brightcove: Businesses must invest strategically in both technology and talent. Developing a robust data infrastructure is essential, as high-quality, diverse datasets enable AI to generate relevant and ethical content tailored to audience needs. Organizations should also cultivate a culture of continuous learning, equipping teams with the skills to use AI tools effectively while understanding the ethical implications and regulatory frameworks that govern their use.

What are the biggest barriers to adopting AI in broadcast production?

Siddarth Gupta, principal engineer, Interra Systems: Adopting AI in broadcast production often requires extensive infrastructure and specialized talent, both of which drive up implementation costs. Models trained on limited or non-representative data can often struggle with real-time scenarios, leading to out-of-distribution (OOD) errors. These compounding technical and financial hurdles have forced broadcasters to rigorously scrutinize and justify their potential ROI before committing to AI implementation.

Yang Cai, CEO and president, VisualOn: The biggest barriers to adopting AI in broadcast production include high implementation costs, the complexity of integrating AI with existing workflows, and a lack of technical expertise among staff. Additionally, concerns about data privacy, reliability, and resistance to change within organizations can hinder adoption. Overcoming these challenges requires investment in training, infrastructure, and building trust in AI solutions.

Kathy Klinger: Ensuring quality and authenticity remains a challenge, as AI lacks the nuanced understanding and emotional depth of human creators. Ethical and legal concerns, including intellectual property, data privacy, and bias, further complicate its adoption, particularly in news and fact-based content. To navigate these issues, the industry must balance AI’s efficiency with human creativity, establish responsible frameworks, and uphold transparency to maintain trust and content efficacy.

Jordan Thomas: Often, a lack of technical expertise and concerns about job displacement may hinder full-scale adoption, however, this can be overcome by preparing and providing insightful training to workforces. One misconception is often the barrier of cost and complexity of integrating AI-driven tools. However, this isn’t always the case. Solutions like QuickLink StudioEdge utilizes AI-technology powered by Nvidia to enhance video and audio quality of remote guest contributions, offered at no additional cost, and can be seamlessly integrated into workflows.

Ken Kobayashi: One of the biggest barriers in camera operation is the “skills transfer.” Customers already have their own established or inherited skills, and sometimes they don’t want to use automated features such as auto-focusing. If AI cameras have room to train or implement customer’s skills about PTZ speed/framing etc. through deep-learning algorithms in the future, they would be more widely used in broadcast production.

How can collaboration between tech developers and broadcasters drive innovation?

Stefan Lederer, CEO and co-founder, Bitmovin: Collaboration across the media technology space is the key to identifying the unique challenges and opportunities that AI can bring the industry. Always a firm believer in the power of collaboration to drive the industry forward, Bitmovin launched the AI Accelerator Community in November 2024 to help advance AI-led innovations in the media and entertainment technology sector. The initiative provides industry professionals with a collaborative space where they can come together to exchange ideas, share insights, and break new ground in media technology.

Bob Caniglia: Direct feedback and collaboration spurs innovation by combining technical expertise with real-world production insights to create meaningful solutions. When broadcasters share hands-on feedback, developers can incorporate that feedback into their product design process to better address industry challenges and enhance workflow productivity. This joint effort enables the creation of advanced technologies tailored specifically to evolving broadcast needs, driving progress and creativity.

Costa Nikols: Collaboration thrives when broadcasters and technology partners work hand in hand to address real-world production challenges. Technology for technology’s sake never really solves the issues that matter. Enabling greater scale, creativity or efficiency, and having a pinpoint use-case focus, are always more important than inventing something brand new and hoping it sticks.

Steve Taylor: I would say that collaboration between users and technology experts is absolutely vital for any product ideation and creation process in any industry. It is very rare that the requirements for a new product or workflow are so well defined in advance that a tech developer can go away, build it, and then present it as a fait accompli. Experimentation, iteration and openness to failure, which is a learning experience, is crucial to help produce the best outcome for a customer’s needs in a more effective way.

Sam Bogoch, CEO, Axle AI: It’s an amazing time for tech developers in this industry, as there is an unprecedented tidal wave of AI and machine learning technology occurring which can be funneled into making video workflows better. If anything, it takes a new approach focused on filtering the almost unlimited possibilities into focused solutions targeting real-world problems that broadcasters face. It’s the collaboration between broadcasters and tech developers that will ensure a payoff today, as well as faster and more efficient innovations tomorrow.

Noa Magrisso: By working closely, developers gain a deeper understanding of broadcasters’ specific challenges, enabling them to create tailored AI solutions. Developers bring specialized technical skills, such as expertise in AI and data analytics, which can address broadcasters’ unique challenges in ways they may not have the resources to explore independently. Combining developers’ technical knowledge with broadcasters’ insights, allows them to co-create tailored solutions that enhance workflows and content delivery.

What is missing in the conversation on AI in broadcast?

Zeenal Thakare, SVP, enterprise solutions architecture, Ateliere: We must consider ethical implications and bias in algorithms, especially since there is a lack of transparency in how AI algorithms make decisions. In the world of “fake news” preserving integrity and trust is paramount, especially with news networks. On those lines, security and data concerns become critical issues that need attention. Overall, the conversation must shift from short-term benefits to the more long-term structural impact of this technology on the industry and the business model itself.

Jordan Thomas: In the conversation of AI in broadcast, the focus is often on technical capabilities, overlooking the human aspect, such as preparing staff for AI-driven workflows or addressing ethical concerns. Tools that utilize AI-technology, like QuickLink StudioEdge and StudioPro, need to be complemented by industry-wide discussions on governance, fairness and inclusivity.

Costa Nikols: AI offers tremendous potential but many practical questions are still to be addressed. Broadcasters need to invest in robust data governance to ensure accuracy and ethical usage, particularly when dealing with generative models. The industry also needs clear standards and frameworks for handling intellectual property and copyright issues surrounding AI-generated content. Expect grounded debate, more practical discussions — and modest, use-case driven adoption in 2025.

Steve Taylor: I would say there is definitely a lot of conversation about AI in broadcast, but perhaps still largely on how it can present risks. We need more positive examples that start to build a trusted foundation for the technology. Whilst we are still talking about AI specification, it will remain the focus rather just another tool for the solution.