TV Industry’s Challenge & Motivation
- Declining Traditional Ad Spend
Broadcast and cable television ad revenues are under pressure. For example, U.S. broadcast and cable ad spending is projected to decline ~15.5% in 2025. - Growth of Streaming & Connected TV (CTV)
In contrast, connected-TV ad spending is growing, forecasted to rise by ~13.2% in 2025 in the U.S. Also, CTV ad revenue globally is expected to hit ~$51 billion by 2029. - Big Tech’s Dominance & Appeal to Advertisers
Platforms like Google, Meta, Amazon, and similar players benefit from large scale, very fine targeting, strong measurement metrics (clicks, conversions), self-serve tools, and low production costs. TV’s more expensive creative, less precise measurement, and higher barrier to entry have made many advertisers stick with Big Tech.
How AI Is Being Used by TV/Streaming Companies
To compete, the TV/media/streaming players are deploying AI and ad tech innovations to lower production cost, improve targeting & measurability, and appeal especially to small and medium businesses (SMBs). Some of the key strategies:
- Self-Serve Ad Platforms + AI Creative Tools
- Comcast’s Universal Ads platform is launching an AI Video Generator (with Creatify) that allows advertisers to generate video creative via AI.
- Channel 4 in the UK introduced a generative AI service that can cut the cost of producing a 30-second commercial by ~90%.
- Targeting & Precision Using CTV Data
- Using subscriber data and other forms of viewer behaviour, streaming/CTV platforms aim to allow advertisers to target specific audiences (geographically, interest-based, etc.), closer to what digital platforms do.
- Roku, for example, helps turn social media posts or existing low-quality videos into ads that work on TV screens via AI upscalers and tools like Spaceback, increasing creative reuse.
- Democratization of TV Advertising
- By lowering creative costs and offering simpler tools, smaller businesses that earlier couldn’t afford or manage traditional TV ad buys are being courted.
- Self-service and managed-service models that are akin to what Big Tech has offered (e.g. Meta Ads, Google Ads) are being developed or expanded.
- Better Measurability & Performance Metrics
- Since Big Tech’s strength is precise metrics (clicks, conversions, immediate direct response), TV companies are working to improve attribution, real-time tracking, connecting ad exposure with outcomes (e.g. sales). Comcast, for instance, is working with partners to connect ads to purchase behaviour.
- Performance-oriented advertisers are crucial for shifting ad dollars, so more tools are being built to satisfy that need.
- AI to Improve Creative Efficiency & Quality
- Aside from cutting costs, AI tools are being developed to allow faster and more iterations of creative, to adapt to audience feedback, perhaps to generate multiple variants for A/B testing.
- Also, AI upscalers to enhance video quality so content produced with more modest resources still looks good on large screens.
Strengths, Opportunities & Risks
Strengths / Advantages
- Lowered entry barrier: Small-business advertisers can more easily enter TV ad channels if creative production is cheaper and simpler.
- Audience scale + prestige: TV/streaming content still reaches wide audiences; the prestige / reach of TV content (especially for brand building) remains valuable.
- Shift in viewer habits: As more viewers shift to on-demand and streaming services, with connected TVs, the opportunity for targeted ad delivery in TV-style environments is growing.
- Regulatory/taste advantage: TV companies may have more control over brand safety, content environment etc., which some advertisers prefer over social media platforms.
Challenges / Risks
- Proving ROI & Measurability: For advertisers accustomed to digital metrics, TV/streaming has to catch up with metrics that are immediate and precise (clicks, installs, etc.). There remains skepticism on whether smaller, AI-produced creative will deliver as well.
- Ad Quality & Brand Fit: Not all AI-generated ads will match the polish that big brands expect. If creative is too low quality, it could damage brand perception.
- Viewer Experience: There’s a risk that more ads, or low-quality ads, reduce viewer satisfaction. Also, viewers may be less tolerant of ads in streaming contexts (especially with subscription models).
- Competition from Big Tech responding: Meta, Google etc. are already developing tools that automate creative or simplify ad production; they also have massive infrastructure & data leverage.
- Regulation / Ad Fraud / Data Privacy: Use of viewer data, subscriber data etc. must comply with privacy laws (GDPR, CCPA etc.), which may limit targeting. Also, attribution across devices and platforms can be tricky.
Impact & What’s Likely Moving Forward
- Shift of Ad Dollars from Purely Digital to Hybrid / CTV/Streaming: Advertisers may allocate a higher share of their budgets to CTV/streaming platforms, especially once cost and measurement hurdles are addressed.
- More Self-Service Tools from TV Platforms: TV / streaming platforms will increasingly offer ad buying / creative tools that mimic/adapt digital-ad seller models.
- Greater Use of Generative AI: For both creative generation and optimization (e.g. dynamic creative variants, localization, personalized creative).
- Smaller Advertisers Getting Access to TV‐style Reach: Niche, local or SMB advertisers who previously couldn’t afford spot buys or high creative costs might start using streaming/CTV options more.
- Evolution of Metrics & Standards: TV/CTV platforms will need to standardize measurement (e.g., viewability, attribution, conversion), find ways to be more transparent and performance-oriented.
- Possible Consolidation or Partnerships: Between streaming platforms, ad-tech firms, startups (for creative tools, measurement), to build end-to-end pipelines.
- Creative Quality Differentiators: As AI creative becomes more common, differentiation through creativity, storytelling, brand voice, and content environment may become more important.
Case Examples
- Comcast / Universal Ads: launching AI Video Generator via Creatify; working on measurement etc.
- Channel 4 (UK): generative AI service cutting production cost ~90%.
- Roku: AI upscaler, using social media content; new ad tools; targeting SMBs.
- tvScientific: An ad-tech startup raising funding to make buying and measuring TV/CTV ad easier; its mission is explicitly to make ad dollars flow back into TV/streaming.
- PwC’s Outlook: Forecasts that AI-powered ads and digital formats (including CTV) will make up increasing portions of ad revenue globally.
Conclusion
AI gives the TV/streaming industry a credible path to compete more effectively against Big Tech in the advertising space. The core levers are:
- reducing creative and production costs via generative AI tools,
- enhancing targeting & measurement to satisfy performance-driven advertisers,
- and offering self-service ad buying channels that lower friction for advertisers, especially small/medium ones.
However, success depends on maintaining ad quality, proving return on ad spend, navigating regulatory and data privacy constraints, and retaining viewer trust. If these bets pay off, TV/streaming could reclaim a meaningful slice of ad spending that otherwise goes to digital platforms.