The erosion of the website’s centrality, and the rise of creators and influencers generates multiple challenges for media –people’s choices have grown enormously. This report highlights consumer behaviour: what people trust and value.

Through a series of case studies we demonstrate people’s needs are resilient: helpful and convenient services with personality that can be trusted, all enhanced by strong community.

Media brands continue to play a critical and trusted role for people to navigate marketplaces, interests and their work life. The role of product –and by extension, the leadership and structure of product development –has grown in importance.

This report is free to access

Trump II is already proving to be a more serious threat to an independent, robust news media than Trump I.

Trump’s direct power around news media is limited, but the threat comes from an unprecedented politicisation of federal regulators, enforcement and procurement—to favour friends and punish enemies.

Opposition to Trump II is weaker and more divided than the broad ‘resistance’ to Trump I. Big tech companies are going for a close embrace, hoping to steer policy to their advantage—while others bend the knee to avoid punishment.

Use of publisher content to train AI models is hotly contested. Unacknowledged scraping, licensing deals, and lawsuits all characterise the publisher-AI company relationship.

However, model training is not the whole story. More and more products rely on up-to-date access to content, and some are direct competitors to publisher offerings.

Publishers can’t depend on copyright to deliver them the value of their IP. They need to track which products are catching on with users for licensing deals to make sense for them, and to ensure their own products keep up with the competition.

UK news publishers are experimenting with generative AI to realise newsroom efficiencies. Different businesses see a different balance of risk and reward: some eager locals are already using it for newsgathering and content creation, while quality nationals hold back from reader-facing uses.

Publishers must protect the integrity of their content. Beyond hallucinations, overuse of generative AI carries the longer-term commercial and reputational risk of losing what makes a news product distinctive.

Far less certain is the role of generative AI in delivering the holy grail of higher revenues. New product offerings could be more of an opportunity for businesses that rely on subscribers than those that are ad-supported.

The UK’s choice of policy for rebalancing the relationships between news publishers and tech platforms is on the agenda of the CMA’s Digital Markets Unit for 2025. The UK is expected to steer clear of the pitfalls of Canada’s news bargaining regime, which led Meta to block news, crashing referrals.

In the UK, Google’s relationships with news publishers are much deeper than referrals, including advertising and market-specific voluntary arrangements that support a robust supply of journalism, and dovetail with the industry’s focus on technology (including AI) and distribution.

The rise of generative AI has also ignited the news industry’s focus on monetising the use of its content in LLMs. AI products could threaten the prominence, usage and positive public perceptions of journalism—this might require progress in journalism’s online infrastructure, supported by public policy.

AI integration into production tools throughout media industries will deliver increased productivity for professional content creation. Generally available tools will also improve quality and production speed for individual user-creators.

Roadblocks include the uncertain copyright status of models and their outputs, attitudes of creative workers and consumers, and the AI tech underdelivering versus what was promised. The need to integrate new tools into existing processes is perhaps the biggest brake.

There are stark differences by sector: the opportunities are greatest in games, where costs have ballooned and software engineering is core. Marketing is furthest in exploiting AI, while audiovisual production is more cautious.

TikTok has been dealt a devastating blow as a US bill has been signed into law forcing owner ByteDance to sell within a year or face its removal from app stores. 

The stakes are higher than in 2020—China's opposition to a divestment will make an optimal sale harder to conclude, so all sides must be prepared for a ban.   

The TikTok bill introduces extraordinary new powers in the context of the US and China's broad systemic rivalry, though online consumer benefits will be limited.  

Big news publishers are pursuing licensing deals with AI companies, chiefly OpenAI. Not all publishers will see a substantial return; while some news may be important for training AI models, not all publisher content will be

Litigation is a threat point when negotiations stall (see the New York Times), but the copyright status of Large Language Models (LLMs) is uncertain. In the UK, there has been no government intervention (on copyright or otherwise) that could facilitate licensing 

Publishers’ bargaining position is strongest when it comes to up-to-date material that could be important in powering some AI consumer products. They should seek deals to support their journalism, while bearing in mind the risk that new products may get between them and their readers

 

The US is intent on preventing the CCP’s goal of AI supremacy by 2030, banning exports of advanced AI chips to Chinese companies. So far, these bans have largely been shrugged off to create a new commercial dynamic in the region. 

Huawei wields a de facto monopoly on the manufacture and sale of advanced chips in China. Huawei also sells cloud services globally and threatens Apple's $70 billion in Chinese revenues through its premium handsets. 

China’s AI regulation is highly supportive of the training and deployment of Chinese-language LLMs developed by tech platforms, startups, and device makers, with meaningful revenue gains only appearing by H2 2024. 

Recent advances in 'Artificial Intelligence' have generated excitement, investment and improved valuations, on the plausible promise of greater efficiency in a range of areas, such as health and coding.

It is still not clear who will profit from this boom. Currently chip-maker NVIDIA is cleaning up, propelled by sales to model developers, also driving demand for cloud computing services.

Leverage in the AI value chain depends on differentiation and barriers to entry, which are high in the chips industry. AI services like chatbots have much lower barriers to entry, while deeper vertical integration of more stages of the value chain could shake things up.