The media industry stands at an unprecedented inflection point as artificial intelligence transforms every aspect of content creation, distribution, and consumption. The global AI in media and entertainment market size was estimated at $25.98 billion in 2024 and is expected to reach $33.68 billion in 2025, representing a remarkable 30% year-over-year growth that signals the rapid acceleration of AI adoption across the sector.
This transformation extends far beyond simple automation, fundamentally reshaping how media organisations operate, create content, and engage audiences. In 2024, investment in generative AI businesses reached over US$56bn, as major players seek to harness its speed, scale, and creative potential, demonstrating unprecedented capital commitment to AI-driven media innovation. A recent survey by Stripe, the leading online payment processor, revealed that content generation is currently one of the biggest drivers of the AI economy, including data synthesis tools, moderating and verifying content, summarisation and insight tools, plus assistants and chatbots.
However, this revolution comes with significant challenges and implications for the workforce. At the top of the list of people most likely to have their job affected by the rise of generative AI are interpreters and translators, followed closely by historians, writers and authors, highlighting the particular vulnerability of traditional media roles.
The most significant shift in 2024-2025 has been the mainstream adoption of generative AI for content creation. In 2025, generative artificial intelligence will shift from a behind-the-scenes tool to a central driver of innovation in marketing, marking a fundamental change in how media companies approach content production.
This transformation is evident across multiple content formats:
Text and Editorial Content : AI-powered writing assistants and content generation tools have become standard in newsrooms and publishing houses. These systems can produce first drafts, generate headlines, create summaries, and even write entire articles on routine topics such as financial reports or sports scores.
Visual Content Creation : AI image generation and video synthesis tools have democratised high-quality visual content production, allowing smaller media organisations to compete with larger rivals in terms of visual appeal and production values.
Audio and Voice : AI voice synthesis and music generation have opened new possibilities for podcast production, audiobook creation, and personalised audio content at scale.
Fifty-three percent of surveyed executives say they are regularly using gen AI at work, compared with 44% of mid level managers, indicating that AI adoption is being driven from the top of organisations. This executive-level enthusiasm is translating into significant budgetary commitments, with 30% anticipating a significant increase of more than 10% in marketing budgets for 2025, much of which is being allocated to AI-powered initiatives.
The emergence of innovative platforms like LettsNews and LettsCore represents a new paradigm in media infrastructure. LettsNews is a simple, yet powerful AI-powered newsroom platform for independent journalists, PR's and content managers that enables quality "story idea to publish in minutes," demonstrating how AI is compressing traditional content creation timelines.
LettsCore is a blockchain platform redefining how content is managed, monetised and delivered. It is the first Web3 platform that lets creators control their content and reputation, maximising digital content revenue in the age of generative AI. This platform addresses critical challenges in the AI era, particularly around content attribution and monetisation.
The integration of blockchain technology with AI addresses several pressing concerns:
Content Provenance : LettsCore's blockchain and AI innovation for managing content, solves some of the biggest issues surrounding information - provenance, trust and verification. As AI-generated content becomes ubiquitous, the ability to verify authentic human-created content becomes increasingly valuable.
Creator Attribution : LettsNews is looking at adopting LettsCore to implement atom level author attribution to news pieces at considerable scale, enabling granular tracking of content creation and fair compensation for contributors.
Monetisation Innovation : Micro-monetisation built into content, enabling frictionless syndication and distribution represents a new economic model for content creators in an AI-dominated landscape.
The media industry faces significant workforce challenges as AI capabilities expand. According to the World Economic Forum's 2025 Future of Jobs report, 41% of employers worldwide intend to reduce their workforce in the next five years due to AI automation, with media organisations being particularly affected.
However, this disruption is creating new opportunities alongside job displacement. AI and automation could displace 85 million jobs by 2025, but also create 97 million new roles more aligned with the division of labour between humans, machines, and algorithms. In media, this means evolving roles that combine human creativity with AI capabilities rather than simple replacement.
LettsNews is solving the disinformation crisis. Its AI-powered news platform for high quality, democratised news, highlights how AI is being deployed not just to create content but to combat misinformation and improve information quality.
The challenge of maintaining trust while leveraging AI capabilities has become central to media strategy. There are still plenty of unresolved risks and unanswered questions that come with AI adoption: copyright litigation, accuracy issues, privacy and bias concerns, and other ethical dilemmas.
The current market landscape is characterised by intense competition for AI supremacy in media. Major technology companies are investing billions in generative AI capabilities, while traditional media companies are scrambling to integrate these technologies into their existing operations.
Technology Giants : Companies like Google, Microsoft, and OpenAI are developing foundational AI models that power media applications, positioning themselves as infrastructure providers to the industry.
Traditional Media Companies : Legacy players are adopting AI technologies for content creation, audience analytics, and operational efficiency, but face challenges in cultural adaptation and technical integration.
Emerging Platforms : Innovative companies like LettsCore are creating entirely new paradigms that combine AI, blockchain, and traditional media functions which redefine content storage, management and seamless integration with content-to-content interactions.
Media organisations are implementing AI across three primary dimensions:
Content Creation : From ideation to final production, AI tools are accelerating and enhancing creative processes.
Audience Engagement : Personalisation engines and recommendation systems are becoming more sophisticated, enabling hyper-targeted content delivery.
Business Operations : Backend processes including scheduling, resource allocation, and financial management are being automated through AI systems.
Based on current trends and technological trajectories, several key developments are likely to reshape the media industry over the next three years:
By 2026, we expect to see the emergence of "AI-native" media organisations that are built from the ground up to leverage artificial intelligence. These companies will:
Operate with radically different cost structures : Traditional media companies spend 60-70% of their budgets on human resources. AI-native organisations may operate with 20-30% human costs, allowing them to produce content at unprecedented scale and efficiency.
Deliver hyper-personalised content : Rather than broadcasting the same content to mass audiences, these organisations will create individualised content streams for each user, adjusting tone, format, and subject matter in real-time.
Implement continuous content optimisation : Using real-time feedback loops, content will be continuously refined and adapted based on audience response, engagement metrics, and emerging trends.
The traditional separation between content creation and distribution will dissolve as AI enables:
Dynamic Content Assembly : Stories will be assembled from modular components (text blocks, images, video clips, audio segments) that can be recombined for different audiences and platforms simultaneously.
Platform-Optimised Delivery : The same core content will be automatically adapted for different platforms – from long-form articles for web to short-form videos for social media – without human intervention.
Audience-Responsive Narratives : Content will adapt its structure, length, and complexity based on real-time audience feedback and engagement patterns.
By 2028, we anticipate the development of comprehensive synthetic media ecosystems where:
Virtual Personalities Drive Content : AI-generated personalities will become major media figures, hosting shows, conducting interviews, and building audiences comparable to human celebrities.
Immersive Experience Integration : The boundary between traditional media consumption and interactive experiences will blur, with audiences participating in content creation through AI-mediated interfaces.
Real-Time Event Synthesis : Major events will be covered by AI systems that can generate multiple perspectives, languages, and formats simultaneously, providing comprehensive coverage within minutes of occurrence.
The next three years will see the establishment of comprehensive regulatory frameworks addressing:
Content Attribution Standards : Mandatory disclosure of AI involvement in content creation, potentially through blockchain-based verification systems similar to LettsCore's approach.
Creator Rights Protection : New legal frameworks protecting human creators from unauthorised AI training on their work, with compensation mechanisms for licensed use.
Quality and Accuracy Standards : Industry-wide standards for AI-generated content accuracy, with liability frameworks for misinformation and errors.
Immediate Actions (2025) :
Medium-term Strategy (2026-2027) :
Long-term Positioning (2028) :
Platform Strategy : Focus on building AI-native platforms that solve specific industry pain points, similar to LettsNews's approach to democratising newsroom technology.
Technology Integration : Leverage existing AI infrastructure while developing specialised applications for media use cases, rather than attempting to build foundational AI models.
Regulatory Compliance : Build compliance and ethical AI practices into core systems from the beginning, anticipating future regulatory requirements.
Skill Development : Invest in AI literacy and learn to work collaboratively with AI systems rather than viewing them as replacement threats.
Specialisation : Focus on uniquely human skills – investigative journalism, emotional storytelling, cultural commentary – that are difficult for AI to replicate.
Platform Diversification : Utilise platforms like LettsCore that provide attribution and monetisation for human-created content in an AI-dominated landscape.
Copyright infringement is looming front and centre as the new battleground for the 21st century as these massive machine bots trawl carefree over our painstakingly created content and media. The industry must address:
As AI-generated content becomes ubiquitous, maintaining information quality and combating misinformation becomes increasingly challenging. Solutions include:
The rapid transformation of media economics will have significant social implications:
The media industry is experiencing its most significant transformation since the advent of the internet. The convergence of generative AI, blockchain technology, and new platform models is creating unprecedented opportunities for innovation while fundamentally challenging traditional business models and workforce structures.
Success in this new landscape will require organisations to balance technological adoption with human creativity, efficiency with quality, and innovation with responsibility. The companies that thrive will be those that view AI not as a replacement for human creativity but as an amplifier of human potential.
The emergence of platforms like LettsNews and LettsCore demonstrates that the future of media lies not just in adopting AI tools but in reimagining the entire content ecosystem. These platforms address critical challenges around attribution, monetisation, and trust that will become increasingly important as AI-generated content becomes mainstream.
LettsNews users can write once and distribute to multiple different places, including their blog, at the push of a button, doing what used to take many hours in just a few minutes. This efficiency gain, multiplied across the entire media ecosystem, represents a fundamental shift in how information is created, distributed, and consumed.
The next three years will be critical in determining whether this transformation leads to a more diverse, accessible, and creative media landscape or one dominated by a few AI-powered giants. The choices made by media organisations, policymakers, and technology developers today will shape the information ecosystem for decades to come.
Organisations that start their AI transformation now, with careful attention to ethical considerations and workforce development, will be best positioned to thrive in the AI-native media landscape of 2028. Those that delay risk being left behind by competitors who have successfully integrated AI into their core operations and value propositions.
The revolution is already underway. The question is not whether AI will transform media, but how quickly and effectively organisations can adapt to harness its potential while preserving the human elements that make media compelling, trustworthy, and valuable to society.
This analysis is based on current market data, industry trends, and emerging platform developments as of August 2025. The predictions and recommendations should be regularly updated as the rapidly evolving AI landscape continues to develop.
