Gocha Kumsiashvili, Director of Production and Technical Support at the Georgian state broadcaster Georgian Public Broadcasting, in the TKT1957 survey «The year 2030: AI or engineer?».
- How will the broadcasting industry and broadcast technologies change in the next 5 years?
- If we model the world of broadcasting and broadcast tech in 2030, what role will AI play?
- How will AI change your business segment?
- Which professions will AI displace in the broadcasting technology industry by 2030?
- In my opinion, the film, television broadcasting, and broadcast technology industries will undergo significant changes over the next five years. These changes will be driven by technological advancements, evolving consumer behavior, and the corresponding shift in the landscape of content creation and distribution.
The key trends and changes that may shape these industries are as follows:
- Further Expansion of Streaming Platforms
– Continued Growth and Dominance of Streaming Services: Traditional broadcasting (DVB-T, S, C) is rapidly losing its audience and will continue to cede ground to interactive streaming platforms like Amazon, Netflix, Disney+, Apple, Google, and new competitors. Consumers increasingly prefer on-demand content (COD/VOD) over scheduled programming.
– Subscription Fatigue and Bundling: Subscription fatigue, caused by the novelty wearing off in some countries and oversaturation in others, will lead to more widespread bundling. As streaming services continue to proliferate, consumers may experience subscription fatigue, leading to the rise of bundle offers from aggregators that combine multiple subscriptions into one package.
– Growth of Local and Niche Content: There will be a continued surge in local and niche content as streaming platforms seek to differentiate themselves and cater to diverse audiences worldwide in the face of both local and global competition.
- Advancements in Broadcasting Technology and Distribution
– Widespread Adoption of 5G: The implementation of 5G will provide faster and more reliable streaming, including 4K content. This will further drive the growth of mobile viewing for both VOD and live broadcasts, increasing content consumption on the go and on smaller screens.
– AI’s Crucial Role in Content Creation and Curation: AI will play a significant role in content creation, curation, and recommendation. Automated systems will enhance personalized viewing experiences and optimize production processes, such as editing, visual effects, and even scriptwriting.
– Expansion of Virtual Production and XR Technologies: As quality and realism improve, virtual production methods and XR (Extended Reality) will become more widespread. Augmented Reality (AR) and Virtual Reality (VR) technologies will be increasingly integrated into live broadcasts, offering more immersive experiences.
- Changes in Content Creation and Distribution
– Short-Form and Interactive Content: Platforms like TikTok and YouTube, which lead in this area, will continue to see growth in short-form and interactive content. Interactive content, including live streams with viewer-driven storylines, will become increasingly popular, especially among younger audiences.
– Decentralized Content Distribution: Blockchain technology could lead to decentralized content distribution models, giving creators more control over their work and enabling direct monetization through NFTs or other digital assets. This could fulfill the long-standing dream of content owners for universal accessibility and protection of their content.
– Sustainable Production Methods: As environmental concerns grow and tax incentives increase, the film and television industries will increasingly adopt sustainable production methods. Successes will be declared from reducing carbon emissions to using renewable energy sources and eco-friendly materials.
- Changes in Consumer Behavior and Regulation
– Cord-Cutting Trend: The trend of consumers canceling traditional cable or satellite TV subscriptions in favor of streaming services will continue to grow. This will force traditional broadcasters and aggregators to adapt or face declining viewership. IPTV networks and streaming services will continue to expand.
– Localized Content Growth: While global content like blockbuster films, international series, and global sports will continue to thrive, there will be a strong push toward localized content that resonates with specific regional niche audiences. Streaming services, due to their flexibility, will invest significantly in content that aligns with local tastes and personal preferences.
– Evolving Business Models and Regulation: As the digital media landscape evolves, governments are likely to introduce new regulations regarding content distribution, data privacy, and intellectual property. Platforms will need to navigate these regulations while balancing content freedom, copyright, and security.
- Emergence of New Business Models
– Ad-Supported Streaming (FAST): Free Ad-Supported Streaming TV (FAST) services will grow as a complement or alternative to subscription-based models, offering consumers more choices while generating revenue through targeted advertising.
– Direct-to-Consumer (DTC) Models: More content creators and studios will bypass traditional distribution channels, opting for direct-to-consumer (DTC) models, allowing them to retain greater control over their content and revenue.
– Integration of Traditional Broadcasting and the Metaverse: The integration of traditional broadcasting with the emerging metaverse will open new opportunities for content consumption, with virtual events, concerts, and shows becoming more common in the digital space.
In conclusion, the next five years will be a period of rapid transformation for the film, television broadcasting, and broadcast technology industries. This era will be marked by innovation, increased competition, and a growing emphasis on content and advertising personalization, sustainability, and immersive consumer experiences. Companies that can adapt to these changes and leverage new technologies will be best positioned to succeed in this rapidly evolving environment.
2. By 2030, AI is likely to be deeply integrated into nearly every aspect of the film, broadcasting, and broadcast technology industries, shaping how content is created, distributed, and consumed. Here’s a vision of the roles AI might play:
- Content Creation and Production
– AI-Assisted Scriptwriting and Story Development: AI will collaborate with human writers to develop scripts, storylines, and dialogues that are both original and tailored to specific audience preferences. AI-powered story generators may produce multiple plot variations to suit different cultural contexts or viewer tastes, resulting in several adapted versions of the final product.
– Creation of Realistic Virtual Actors and Digital Doubles AI will enable the creation of highly realistic virtual actors, digital doubles, and deepfake technology capable of replicating or reviving well-known actors for new roles, past performances, or interactive experiences. These virtual actors could evolve into AI-driven personalities that adapt based on viewer interaction, potentially developing unique traits. However, there may be phases where consumers reject digital personas and revert to preferring real human actors.
– Automated Video and Audio Editing AI will take over much of the video and audio editing process, including selecting the best takes, performing color correction, and adding special effects. AI tools will significantly accelerate post-production, enabling the faster and potentially cheaper delivery of high-quality content.
– Enhanced Virtual Production Techniques AI will improve virtual production methods, allowing for real-time adjustments to environments, lighting, and effects. AI could also predict and automate complex shot planning, reducing the need for detailed pre-planning and configuration.
– Restoration and Enhancement of Archival Materials: AI will be used to restore and enhance archival materials, bringing them up to new high standards, making them suitable for modern broadcasting and consumption.
– Comprehensive Metadata Indexing of Archives: AI will scan all previously accumulated digital archives to extract factual information related to sound, speech, visual objects, meanings, and other details. This process will result in extensive, indexed metadata databases that facilitate quick and efficient searching.
– Historical Context Analysis AI will attempt to analyze and compare informational backgrounds with social events from historical periods, offering new insights and perspectives on past content, potentially deepening our understanding of historical media.
- Personalized and Adaptive Content
– Real-Time Adaptive Content: AI will enable the creation of content that adapts in real-time to the preferences, emotions, and behavior of individual viewers. For example, a movie could have multiple endings or even different plotlines, and AI could select the most suitable one based on who the viewer is and how they respond throughout the film. In this sense, films will resemble today’s first-person video games.
– Advanced AI-Powered Recommendation Systems: These systems will become even more sophisticated, offering highly personalized content recommendations that consider not just viewing history but also mood, time of day, and even biometric data from wearable devices.
– Interactive Storytelling: AI will support interactive narratives where viewers can influence the storyline through their decisions and actions. In VR and AR environments, AI could create adaptive virtual worlds that evolve based on user interaction, offering a personalized storyline.
– Use of Immersive Headsets: More viewers will use AI-powered immersive headsets and panoramic glasses, blending the real world with the virtual, creating a more interactive and engaging viewing experience.
– Future Possibilities: In the event of a breakthrough in transmitting information directly to the brain, bypassing vision and hearing, the industry could experience another AI revolution, though this remains closer to science fiction for now.
- Broadcasting and Distribution
– Optimized Live Content Scheduling: AI will optimize the scheduling of live broadcasts, ensuring that programs align with viewer habits and peak viewing times, thereby maximizing audience engagement. This will include real-time adjustments based on viewership data.
– Real-Time Translation and Dubbing: AI will facilitate real-time translation and dubbing of content into multiple languages, making global content more accessible. AI will also handle localization, adjusting cultural references, footnotes, humor, and other elements to suit different regions.
– Virtual News and Sports Anchors: Virtual anchors, powered by AI, will likely become common, offering personalized choices where the same program could be hosted by different virtual presenters tailored to different viewers.
– Dynamic Content Distribution: AI will optimize content distribution across platforms, determining the best medium (e.g., streaming, broadcast, mobile) for specific content based on audience analytics. AI will also dynamically manage bandwidth and quality to ensure a smooth viewing experience.
– Shift from Viewer to User: The concept of the viewer as a passive subject will be widely replaced by the idea of the consumer or user, emphasizing the increasing interactivity in content consumption.
- Audience Engagement and Analytics (Potential Concerns)
– Real-Time Audience Analysis: AI will analyze audience reactions in real time, including facial expressions, voice tone, biometric data, and social media engagement, to gauge content perception and adjust broadcasts accordingly. This could involve altering live streams based on viewer feedback.
– Content Trend Prediction: AI will likely predict content trends, helping creators and broadcasters anticipate which types of shows or films will resonate with audiences. This could lead to content creation and marketing strategies driven by highly representative data.
– Revolutionizing Advertising: AI will revolutionize advertising by creating highly personalized ads that align with viewers’ interests and behaviors. AI-driven algorithms will place ads in a way that maximizes relevance and effectiveness, potentially even generating customized ads on the fly. Advertising content will consider the user’s psychotype and adjust to their psychomotor responses.
– Increased Ad Impact through Feedback Data: As feedback data accumulates, AI analysis will further enhance the effectiveness of advertising, making it increasingly targeted and influential.
- Ethics and Content Moderation
– Real-Time Content Moderation: AI will play a crucial role in moderating content, detecting and filtering inappropriate or harmful material in real time according to audience norms and age restrictions. This will extend to managing and identifying deepfake content, ensuring ethical standards are maintained in its use.
– Ethical Content Creation: AI can be programmed to adhere to ethical principles in content creation, ensuring that stories and characters align with societal values or legal standards, thereby reducing the risk of controversial content.
- Education and Training
– AI-Powered Education Tools: AI tools will be used to train the next generation of directors, broadcasters, and media professionals. Virtual mentors, tutors, AI-driven simulations, and personalized learning platforms will help students acquire skills more efficiently.
– Virtual Production Teams: AI will enable the creation of virtual production teams, where people can collaborate on projects in real time. AI will manage logistics, overcome language barriers, and even participate in the creative process, rapidly implementing creative ideas.
By 2030, AI is likely to become a fundamental driving force behind the evolution of the film, broadcasting, and broadcast technology industries. It will revolutionize how stories are told, how content is personalized and distributed, and how audiences interact with media. While AI will open up enormous creative possibilities and efficiencies, it will also require careful consideration of ethical implications, the role of humans in a rapidly changing media landscape, and the risks, opportunities, and methods of influencing users.
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AI’s Revolution in the Broadcasting Industry
AI is expected to revolutionize the broadcasting industry, particularly in key areas such as broadcast automation, media archiving, news production, and sports broadcasting. Here’s how AI might reshape these areas by 2030:
- Broadcast Automation
– Optimized Scheduling: AI will optimize broadcast schedules by analyzing viewer habits, content popularity, and real-time engagement data. It will automate decisions on when to air specific content, dynamically adjusting schedules to maximize viewer retention and advertising revenue.
– Dynamic Personalization The traditional broadcast schedule will be replaced with a dynamic, personalized schedule for each identified user, offering a tailored viewing experience.
– Real-Time Monitoring: AI will monitor live broadcasts in real time, detecting and correcting issues such as signal loss or content sequence errors. This will reduce downtime and ensure smoother, uninterrupted broadcasts.
– Enhanced Ad Placement: AI will analyze viewer data to insert personalized ads at optimal times, possibly adjusting ad content to better match viewer interests or even replacing traditional ads with interactive or dynamic ads based on viewer engagement.
- Media Archiving
– Detailed Metadata Generation: AI will enhance media archiving by automatically generating detailed metadata for content. This includes tagging scenes, identifying characters and objects, analyzing dialogues, and recognizing visual elements, making it easier to search and retrieve specific content from vast archives.
– Restoration and Preservation: AI-powered algorithms will play a crucial role in restoring and preserving old or damaged media materials, including films, videos, and audio. AI can identify and correct visual or audio degradation, ensuring that archived content remains accessible and of high quality for future generations.
– Intelligent Archiving Systems: AI will create smarter archiving systems that predict which content will be valuable for future use based on trends, historical data, and audience demand. These systems can also prioritize archiving content likely to be reused or monetized, with AI assigning ratings based on the content’s relevance and popularity.
- News Production
– Automated News Story Generation: AI will generate news stories and reports from raw data, such as financial reports, sports results, or special events. These AI-generated reports can be created instantly, allowing news agencies to provide timely coverage with minimal human intervention, nearly automatically.
– Virtual News Anchors: AI-powered virtual news anchors will become more common, delivering live news in multiple languages and even adjusting their tone and delivery style based on the audience. These virtual anchors can be available 24/7, providing continuous news coverage with customizable presenters.
– Fact-Checking Assistance: AI will assist journalists by fact-checking information on the fly, cross-referencing sources, and identifying potential misinformation in real-time. This will enhance the credibility and accuracy of news reports.
– Interactive Broadcast Support: During interactive broadcasts with guests, AI will help verify factual information and retrieve relevant media materials from archives, enriching the discussion with accurate and timely content.
– Personalized News Feeds: AI will create personalized news feeds tailored to individual viewer preferences, presenting stories based on interests, reading habits, and regional preferences. This customization will increase viewer engagement and satisfaction.
By 2030, AI is expected to significantly transform the landscape of the broadcasting technology industry, replacing some routine and technical roles while enhancing others. Although certain professions may see a decline in demand, new opportunities will arise for roles focused on managing, refining, and ethically deploying AI technologies. The key for professionals in the industry will be adapting and developing new skills that align with this evolving technological landscape.
- Sports Production
– AI-Driven Camera Operation: AI will manage cameras during live sports events, automatically tracking players, the ball, or other key elements of the game. This will enable dynamic and consistent camera angles without extensive manual intervention.
– Instant Replays and Highlight Reels: AI will analyze live sports events to automatically generate instant replays and highlight reels. This technology will identify the most exciting or critical moments of the game, allowing broadcasters to quickly create and air thrilling highlight packages.
– AI-Enhanced Commentary: AI will provide real-time commentary and analysis during sports broadcasts, complementing or even replacing traditional commentators. AI-generated commentary could include advanced statistical analysis, player performance insights, and predictive outcomes based on the game’s dynamics.
– Immersive Viewer Experiences: AI will enhance viewer experiences with VR and AR, offering immersive and engaging viewing experiences. For example, AI could create virtual environments where viewers can watch games from any angle or provide augmented reality overlays with real-time stats and player information during live broadcasts.
– Predictive Game Outcomes: AI will generate possible scenarios and outcomes during matches and offer the desired result to the user (a light-hearted joke, thank you for reading this far).
4. AI’s Impact on Broadcasting Professions by 2030
AI will substantially influence various professions in the broadcasting technology industry. While some roles will be fully replaced, others will be partially replaced or augmented, leading to a shift in the required skills.
- Replaced Professions
– Broadcast Directors: AI-based broadcast automation systems will increasingly manage scheduling and sequencing of broadcast content, reducing the need for operators to manually perform these tasks. AI will oversee and adjust live broadcasts in real time, ensuring seamless and error-free transmission.
– Media Loggers and Metadata Taggers: AI will automatically generate detailed metadata for media content, including scene tagging, visual element identification, and audio transcription. This will diminish the need for human media loggers who traditionally catalog content.
– Routine News Reporters: AI-generated journalism will handle routine news reporting, such as financial updates, sports results, and weather forecasts. AI-driven systems can instantly create text and video content from data, reducing the demand for human reporters in these areas.
– Basic Video Editors: AI-powered editing tools will automate many aspects of video/audio editing, such as cutting footage, applying transitions, and basic color correction. This could replace the need for editors on low-complexity projects, particularly for news and short-form content.
- Partially Replaced or Augmented Professions
– Camera Operators and Directors of Photography: AI-driven camera systems will handle tasks like object tracking, focus adjustment, and optimal angle selection, especially in sports and studio settings. However, human operators will still be needed for creative decisions, complex shoots, and overseeing AI systems.
– Broadcast Engineers: AI will assist in monitoring and maintaining broadcast systems, diagnosing issues, and optimizing performance. While this will reduce the demand for traditional broadcast engineers, specialists with AI and machine learning expertise will be needed to manage and improve these systems.
– Journalists and News Producers: AI will complement journalists by automating fact-checking, data analysis, and initial content drafts. Human journalists will focus more on investigative reporting, storytelling, and editorial judgment, with AI supporting research and routine reporting.
– High-End Video Editors: While AI can handle basic editing tasks, human editors will still be required for high-end productions that demand complex and creative decision-making, such as feature films, documentaries, and commercials. AI will serve as a tool to speed up workflows but won’t replace the human touch.
– Sports Commentators and Analysts: AI systems will provide real-time analysis and commentary during sports events, offering statistical insights and predictions. However, human commentators will remain valuable for their charisma, ability to connect with the audience, and emotional intuition during broadcasts.
– Content Curators and Program Editors: AI will assist in curating and programming content by analyzing viewer preferences and optimizing schedules. However, human curators will still be needed to oversee AI recommendations, ensure content diversity, and maintain brand identity.
- New Professions
– AI and Data Specialists: As AI becomes more integrated into broadcasting, there will be a growing demand for professionals who can develop, manage, and refine AI systems. This includes AI trainers, data specialists, and machine learning engineers specializing in broadcasting technologies.
– Virtual Production Technicians: With the rise of AI-powered virtual production, new roles will emerge focused on managing virtual sets, digital environments, and AI-based content creation tools. These technicians will bridge the gap between traditional production and AI-enhanced workflows.
– AI Ethics and Compliance Officers: As AI plays more roles in broadcasting, ensuring ethical use and compliance will become critical. This will create a need for professionals who can oversee AI deployment, eliminate bias, and ensure transparency in AI-driven decision-making.
All the opinions of industry leaders can be seen in the survey “Year 2030: AI or Engineer?”.
