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.  

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.

Meta's China risk is overstated: the spend from Chinese advertisers is diverse and resilient to everything short of a full-blown trade war. 

Apple (and Tesla) are in the more precarious position of selling directly in-market, and face sharpening domestic competition.

Amazon's exit from selling in China still leaves it exposed: its marketplace strategy is built on Chinese sellers, whose potential routes to market are proliferating with local platforms going global.  

Online retail is a prime arena for AI implementation, with a high degree of tech involvement and proximity to the point of sale

Generative AI’s near-term prospects are inflated by the hype cycle; instead, improvements to product discovery and logistics will be the next frontiers for growth and AI-driven efficiency

Retailers risk their reputations as they jostle for early mover advantage: larger players Amazon and Shopify through major investments, and SMEs with specialised data and licensing

Despite its scale, YouTube can get overlooked. But its tremendous reach and impact across all demographics make it the internet's universal service provider. 

YouTube is still the golden child for creators who want to make a living from their content. For YouTube, this broad base of suppliers ensures a position of strength from which to claim a large revenue share. 

Competition from TikTok took some of the shine off YouTube's usage, and forced it promote lower-monetising Shorts. YouTube is pushing heavily into subscriptions, TV sets, and premium content via sports rights to boost the money it makes per minute spent. 

As younger viewers continue to migrate from linear TV to online video-sharing platforms, engaging with the audiences on these platforms is no longer simply an opportunity, but a necessity.

However, this ecosystem offers broadcasters limited monetisation opportunities, reduced audience data and worse attribution than the more lucrative broadcast TV model.

In this fragmented media landscape, broadcasters must maximise their digital reach and exploit incremental revenue opportunities, although linear channels and owned-and-operated platforms will continue to provide the bulk of revenues.

We forecast broadcaster viewing to shrink to below half of total video viewing by 2028 (48%)—down from 64% today—as streaming services gain share of long-form viewing time.

On the key advertising battleground of the TV set, broadcasters will still retain scale with a 63% viewing share by 2028, even as SVOD and YouTube double their impact.

Short-form video will continue to displace long-form as video-first apps (e.g. YouTube, Twitch, TikTok) gain further popularity and others (e.g. Facebook, Instagram) continue a relentless pivot to video. This will expand the amount of video watched and transition habits—even amongst older demographics.

Recent developments in AI have ignited a frenzy in the tech world and wider society. Though some predictions are closer to sci-fi, this new phase is a real advance.

We view AI as a ‘supercharger’, boosting productivity of workers. The impact is already being felt across media sectors, including advertising and publishing.

Firms thinking about using AI should assess which tasks can be augmented and what data is required. Be prepared for unpredictable outputs and a changing legal and tech landscape.