The media and adtech landscape will undergo seismic shifts by the early 2030s, propelled by rapid advancements in artificial intelligence (AI), evolving consumer behaviors, and corporate consolidation driven by tech giants. These changes will reshape industries, from television to advertising, and redefine how content is created, distributed, and monetized. To predict the macro environment, we must examine the key lanes of evolution — TV, AI, compute power for media, and mega tech companies — and their interplay with broader economic and societal trends. This essay outlines these transformations, grounded in the following assumptions and projections:
1. AI will advance rapidly, transforming media through generative content creation, automated media planning, real-time campaign optimization and more. AI will enable cost-efficient production of video ads and personalized Performance CTV campaigns, helping brands evolve from reach and frequency to driving measurable outcomes. AI will drive continuous optimization and personalization, creating a performance flywheel effect similar to what platforms achieve today with Meta.3. Programmatic display advertising will decline in favor of video, mobile, and Performance CTV, with cookies and last-click attribution models phasing out and AI-driven attribution models emerging. First-party data and contextual targeting will replace cookie-based systems, enabling precise measurement for Performance CTV campaigns.
4. Large language models (LLMs) will reduce search-driven traffic to publishers by delivering direct answers, forcing new business models. Publishers will adopt microtransactions, asynchronous ads, and content licensing to LLMs to sustain revenue as traffic declines.
5. Last-click attribution will be obsolete by 2030, replaced by AI-driven multi-touch models, boosting Performance CTV and social platforms while challenging mobile app marketing and display ads. As attribution intelligence improves, digital advertising budgets will reallocate to match true value creation. Performance CTV excels in demand creation, and modern attribution systems based on incrementality will reveal this.
6. Ad agencies will evolve to prioritize outcome-driven strategies (e.g., conversions, incremental sales lift/ROAS) over reach and frequency, leveraging AI automation; those that fail to adapt will risk irrelevance.
7. Performance CTV will overtake search as the dominant performance advertising channel, driven by its scale, superior media format, and precise ROI measurement. With a reach of 121 million U.S. CTV households by 2027 alone, Performance CTV will leverage real-time personalization and incrementality testing to outpace search’s last click attribution and ROI.
8. Streaming CTV CPMs will hit bottom by 2028 and double from there by 2030, driven by a dramatic change in buy-side advertiser participation from the more than 9M search and social advertisers that will migrate to CTV advertising. By 2035, we will see $100 average CPMs across the tier one publishers, which will be supported by true ROAS.
9. Quantum computing + AI: When quantum computing meets AI, our encryption systems, media platforms, healthcare diagnostics, energy grids, and financial markets all face a seismic shift — every industry must prepare.
The television industry will experience disruptive change by 2030, driven by AI and the rise of Performance CTV. Two key shifts will define this evolution:
Shift 1: AI-driven cost transformation
AI will drastically reduce the cost of TV production. Advanced generative AI tools will enable creators to produce high-quality content from text prompts, slashing budgets for scripting, editing, and visual effects.
For example, a small studio could input a prompt like, “A futuristic cityscape with autonomous vehicles, narrated by a synthetic voiceover,” and receive a polished draft in minutes. These platforms will integrate with performance analytics, allowing real-time optimization of content for viewer engagement or advertiser goals like brand lift or conversions.
Shift 2: Performance CTV as the new search
Performance CTV will emerge as the dominant performance advertising channel, surpassing search and social media. Thanks to AI-driven optimization and attribution technology and low barriers to ad creation, Performance CTV offers measurement superior to current search and social platforms. AI-powered tools will enable millions of businesses, small and large, to produce TV ads with minimal investment, leveling the playing field.
Tech platforms like Amazon will be major players in Performance CTV, leveraging their scale, data, and infrastructure to outmaneuver traditional media companies. Amazon’s aggressive investment in content acquisition and advertiser onboarding will shift ad dollars from search and social to Performance CTV, making it the go-to channel for performance-driven campaigns.
While Amazon will be a key player, Jeff Bezos and his mega tech company peers will not dominate Performance CTV because they are not aligned with advertiser goals.
Amazon is too draconian with their ad customers, preventing them from receiving customer info, using their data to compete with them, and squeezing their margins to the breaking point. The Amazon ethos of “your margin is my opportunity” will be a structural ceiling for the Amazon ad business. Thus, advertisers will increasingly invest in non-walled garden storefronts and ad platforms to drive their business independently from the self-interested mega media companies. This opens the door for new entrants in Performance CTV.
Traditional cable and broadcast companies will likely struggle as viewers turn to streaming. Their reliance on a shrinking pool of top-tier advertisers and failure to attract performance-driven advertisers from search and social will accelerate their decline. These companies will increasingly pivot to being infrastructure providers—“pipes” for content delivery—while tech giants like Amazon capture a significant share of Performance CTV revenue from the top 500 advertisers.
AI will reshape the media landscape in ways comparable to the Industrial Revolution, automating processes and unlocking efficiencies across the economy. In media, AI’s impact will be most pronounced in search, creative development, and vertical applications.
AI search and advertising
By 2030, I predict AI-driven search will fragment into specialized vertical engines, each tailored to specific industries or user needs, potentially unified under a single platform. LLMs already provide superior user experiences by delivering direct answers rather than link-based results, challenging Google’s dominance.
However, monetizing AI search poses a challenge: intrusive ads risk alienating users, while high-intent search remains a lucrative channel. To address this, advertising will shift away from the LLM interface, delivering intent-based ads asynchronously via integrations with social platforms or Performance CTV, where AI-driven attribution models, such as automated incrementality tests, will outperform today’s search and social metrics. Google’s market share in search advertising, currently 80-90%, could drop to 50-60% as competitors leverage LLMs and vertical specialization.
Creative automation and optimization
AI will revolutionize creative development by enabling marketers to produce tailored video ads for Performance CTV from text prompts. For instance, a Ford marketer could input: “2030 Ford F-150 driving on Pacific Coast Highway, cherry red, with a white female driver and a golden retriever in the back seat, ending with a hike in the redwoods.” Within seconds, a draft ad would appear, editable in real time. These platforms will integrate with media execution systems to optimize creative elements—such as color schemes or messaging—for specific KPIs, like brand lift or cost-per-lead. This automation will democratize high-quality ad production, enabling smaller brands to compete with industry giants.
Building on creative automation, AI will drive continuous optimization and personalization, creating a flywheel effect similar to what platforms achieve today with Advantage+ and PMAX.
The death of last-click attribution
Last-click attribution, or crediting conversions solely to the final touchpoint, will be obsolete by 2030. This model has long undervalued upper-funnel efforts (e.g., awareness ads on TV or social), leading to misallocated budgets and underinvestment in brand building. With zero-click searches projected at 60% of queries and fragmented journeys spanning dozens of touchpoints, accurate measurement demands multi-touch models, AI-powered incrementality testing, and marketing mix modeling (MMM).
As AI attribution intelligence improves, digital advertising budgets will reallocate to match true value creation. Performance CTV excels in demand creation, and modern attribution systems based on incrementality will show this.
In media, this shift will empower Performance CTV and social platforms, where real-time AI attribution enables precise ROAS tracking across devices. Mobile app marketing (which is largely based on last click attribution) and display ads will suffer further traffic and revenue losses without robust first-party data strategies, while agencies like Publicis that pivot to holistic, AI-driven planning will thrive. Overall, the death of last-click attribution will foster a more equitable ecosystem, rewarding integrated campaigns over siloed tactics.
Vertical AI applications
AI agents will proliferate, handling specialized tasks from content recommendation to audience targeting. These agents will operate across media platforms, optimizing Performance CTV campaigns in real time based on user behavior and market trends.
For example, a retail brand could deploy an AI agent to adjust ad placements across Performance CTV, social, and mobile, ensuring maximum ROI without human intervention. In 2025, the industry is already moving towards fully agentic advertising with the introduction of AdCP.
Compute power will be the backbone of media innovation by 2030, with edge computing enabling real-time optimization on smart TVs, mobile phones, and IoT screens. By analyzing viewer behaviors (e.g., taking action on a Performance CTV ad) in milliseconds, edge AI will be able to dynamically adjust creatives or placements, and buying agents will be able to ingest vastly more bid requests. They’ll apply highly selective ML models to identify and bid appropriately on the ad most likely to drive an outcome.
All of this optimization against massive datasets will be enabled by huge increases in compute power and data processing efficiency.
The global edge computing market is projected to reach $155.9 billion by 2030, growing at a 36.9% CAGR from 2024, driven by AI integration for low-latency applications like real-time ad optimization. Similarly, the AI in marketing market will expand from $20.44 billion in 2024 to $82.23 billion by 2030 (25% CAGR). For Performance CTV, ad spend is forecasted to hit $46.9 billion by 2028, with the installed base of CTV devices reaching 4.2 billion globally by 2030.
The fate of mega tech companies will hinge on their ability to adapt to these technological and market shifts. Here’s how I predict key players will fare by 2030:
Amazon: Amazon’s media business will thrive, driven by its leadership in ecommerce. However, its restrictive tactics will continue to alienate advertisers (“your margin is my opportunity”), pushing them to invest in open web alternatives. This will limit their growth, and marketers will just use them for Amazon’s ecosystem.
Walmart: Walmart will aggressively challenge Amazon in retail media with a rational, advertiser-friendly approach, leveraging transparency, first-party data, and CTV partnerships to capture performance ad dollars without margin squeezes.
Microsoft: Microsoft will focus on AI-driven search and LinkedIn’s media platform, leveraging its cloud infrastructure to power enterprise-grade AI solutions.
Netflix: Netflix will remain a viable independent streaming service, bolstered by its global subscriber base and investments in original content.
Apple: Apple will stay a niche player in advertising, prioritizing privacy and premium content over mass-market ad revenue.
AppLovin: AppLovin will face challenges as advanced attribution technologies expose inefficiencies in its ad model, reducing its market share.
Meta: Meta will remain a social media powerhouse, integrating AI-assisted advertising to maintain relevance.
Google: Google’s search dominance will erode as LLMs and vertical search engines gain traction, reducing its market share significantly. They also suffer from innovator's dilemma, precluding them from delivering clean LLM results. In CTV, they will continue to focus on YouTube and YouTubeTV.
Comcast: As a traditional media giant, Comcast will face ongoing challenges, with ad revenues dropping as consumers cut cords and shift to CTV.
OpenAI: OpenAI will drive AI-powered media innovation, from screenless devices to LLM-driven content creation. It will continue challenging search and enabling Performance CTV, though privacy concerns may limit ad monetization.
Roku: Roku will capitalize on Performance CTV dominance via Amazon DSP integration and ad-tech investments, but must culturally shift from brand-centric (e.g., upfronts) to outcome-driven models for sustained growth.
Streaming consolidation: The next wave
Just as railroads, auto companies, radio stations, and broadcast TV consolidated for scale and efficiency, streaming platforms will follow suit by 2030, driven by profitability pressures and subscriber fatigue. Expect 20+ services to merge into 4-5 super-players, with bundles reducing churn and sharing costs. Likely deals include:
Netflix absorbing niche competitors: Netflix will acquire targeted services like BritBox (UK drama) or Drama Bar (Israeli content) to fill global gaps, leveraging its $18B content budget for low-cost tuck-ins.
Paramount continuing aggressive buys: Paramount (post-Skydance merger) will pursue Warner Bros. Discovery in a $70B+ deal, combining Paramount+ and Max for 200M+ subs and IP like DC Comics and Star Trek. If/when this is done, they will continue to roll up additional content + distribution assets.
Disney + Fubo: Disney's 70% stake in Fubo evolves to full acquisition by 2026, bundling Hulu Live with sports for 40M+ live subs.
Comcast spin-off + AMC Networks: Comcast offloads cable networks to merge with debt-laden AMC, creating a mid-tier bundle with Peacock and AMC+ for horror/drama niches.
These mergers will accelerate efficiency but raise prices. Ultimately, the market will favor adaptable giants like Netflix and Amazon.
Some of the more macro technology impacts (outside of media, for example) will come from the combinations of quantum computing and AI. The concept of “Quantum AI” — using quantum computers to accelerate or enable new kinds of AI models, or using AI to help design quantum algorithms/hardware — is gaining traction.
Some of the near-term practical applications include:
Healthcare & drug discovery: With quantum simulation + AI, one might discover new molecules, personalize medicine at higher fidelity, and simulate interactions at the quantum level.
Finance & risk modeling: Real-time portfolio optimization, fraud detection with quantum-enhanced AI models.
Energy / materials / climate modeling: Faster simulation of complex physical systems, improving battery tech, optimizing power grids, materials for energy storage etc.
Cybersecurity & encryption: Quantum computing will impact encryption (both breaking some classical schemes and enabling new ones), and AI will be necessary for adaptation. Given the geopolitical tensions that already exist, this will become a potentially decisive driver of the new tech arms race.
Media: Advanced audience analysis & targeted marketing driven by quantum computation of massive datasets (we’re 3-5 years out from this future)
“Quantum Image Processing” (e.g., encoding/image/video processing using quantum algorithms) is already a theoretical field focusing on optimizing and personalizing media. The potential for hyper-personalization and media optimization using this technology is profound.
By 2030, the media and tech landscape will be unrecognizable, driven by AI, Performance CTV, social platforms, and advanced compute infrastructure like edge computing.
New entrants and open platforms will thrive in Performance CTV advertising by aligning with advertiser goals, while tech giants like Meta, TikTok, and Netflix will dominate social advertising and content distribution. Traditional media companies will struggle to adapt as ad dollars shift to performance-driven channels. AI will lower barriers to creative production and optimize performance, reshaping how brands engage with consumers.
Publishers will need to find new ways to attract users outside of Google. Search referrals (dominated by Google) consistently account for between 20% and 40% of referral traffic to most major publishers. For advertisers, reliance on Google Ads can represent a significant portion of customer acquisition outcomes, which is at risk as LLMs erode Google search traffic.
Startups that innovate in the LLM + advertising and Performance CTV categories could become the next crop of mega unicorns.
As advancements in computing power continue, we can expect an accelerated pace of innovation across most business tech-driven media categories, from hyper-personalized media algorithms to new business models around the next generation of search. The winners will be those who embrace the waves of change, leveraging technology to redefine the media experience and advertiser strategies in a rapidly evolving world.
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