On 5 February 2026, Preiskel & Co convened policymakers, legal experts and publishers at the Inner Temple to examine how generative AI and dominant technology platforms are restructuring journalism’s economic foundations. The event confirmed that AI-enhanced search constitutes structural transformation with material implications for media plurality and market power.
From Gateway to Destination
Search engines are transitioning from gateways that direct users to publisher websites into destinations that resolve queries directly through AI-generated summaries. For ad-funded publishers, which constitute the bulk of the UK sector, traffic drives reach, revenue and commercial viability.
Panellists reported severe reductions in click-through rates following deployment of AI Overview features, with some independent publishers recording traffic losses approaching 96 per cent. This represents systemic diversion of user attention from original sources into platform-controlled environments.
Leveraging Dominance Through AI
Anti-competitive concerns extend beyond traffic displacement. Dominant search platforms rely on publisher content to train and refine AI systems whilst simultaneously prioritising their own AI-generated outputs in prominent positions on results pages. This raises risks of anti-competitive bundling and self-preferencing, leveraging market power in general search into adjacent AI and information services.
By controlling ranking, interface design and display hierarchy, platforms determine whether economic value flows to independent publishers or is captured internally. The combined effect is upstream appropriation of editorial input and downstream diversion of demand, reinforcing barriers to entry whilst weakening the commercial base of news production.
Established news and specialist publishers perform vital public interest functions. If AI features systematically erode their visibility and revenues, the outcome is fewer independent voices, reduced investigative capacity and greater exposure of users to low-quality or unverified material.
Limits of Copyright
Discussion identified a structural mismatch between traditional copyright doctrine and AI system design. In relation to the training of AI systems, known as Large Language Models (LLMs), copyright is often an incomplete safeguard against what has been characterised as “cultural strip-mining”. The issue is not conventional piracy but the use of journalism as functional input. Value arises through large-scale aggregation and optimisation rather than identifiable copying of discrete works.
“Opt-out mechanisms” were characterised as illusory in markets where refusal may mean effective exclusion from dominant discovery systems. Levy and blanket licence models were criticised for treating differentiated journalism as interchangeable repertoire, ignoring the role of news as time-sensitive infrastructure underpinning AI accuracy and relevance.
Competition Law Lens
Competition law provides tools suited to this context. It examines whether a dominant undertaking extracts value whilst degrading the competitive position of trading partners on whom its services depend. Benchmarking and hypothetical negotiation models can infer fair value where platforms function as unavoidable trading partners.
Recent developments in user damages reinforce this approach, supporting recovery where a dominant platform derives value by interfering with control over valuable assets such as data or content. The Gormsen v Meta (2024) ruling confirmed that when a dominant platform invades a right to control valuable assets, damages may be recoverable. The focus shifts from narrow copying claims to systemic value extraction and competitive distortion.
Transparency as Foundation
Any effective regime depends on transparency. Technical systems for tracing content used in AI training and outputs have been considered feasible by technical experts for some time. Standardised tracing, mandatory disclosure of training datasets and auditable reporting to regulators would be essential. Without such measures, platforms can internalise value whilst publishers lack visibility into how their material underpins AI functionality.
Integrated Regulatory Response
Policy models under discussion include collective licensing, levies and final offer arbitration. However, no single mechanism is sufficient. A credible framework must combine competition-based valuation of content use, safeguards against discriminatory loss of visibility, fast-track dispute resolution and robust statutory transparency obligations.
Conclusion
AI-enhanced search is reconfiguring the information economy. Where a small number of platforms both depend on publisher content and control user access, there is sustained risk that value is extracted from journalism whilst monetisation remains within platform environments. Coordinated action across competition, copyright and media regulation is required to restore bargaining balance, ensure transparency and preserve journalism as economically sustainable activity central to democratic resilience.
Preiskel & Co advises on competition law, abuse of dominance and regulatory matters affecting digital markets. For enquiries regarding AI-related competition issues, platform conduct or media sector disputes, contact the firm’s antitrust practice.
Please contact Tim Cowen if you have any questions
The material in this article is only for general review of the topics covered and does not constitute legal advice. No legal or business decision should be based on its content. This article is written in the English language. Preiskel & Co LLP is not responsible for any translation of all or part of its content into any language.