Sorin MS Krammer from the University of Southampton investigates the problems posed by automated academic writing.
Until recently, the role of AI in research felt like a helpful assistant. Summarize papers, clean datasets, create abstracts, and more. Researchers were still in charge of that thinking.
In late 2025, the situation changed with the arrival of a cutting-edge “frontier.” A.I. Models can now reliably reason and plan on their own. The main features of these models are: “Tool call” – The ability to interact with external tools to not only describe the world, but to act on it.
this is, agent AI: A system that not only responds to instructions, but can also execute independently. Plan, Execute, Iterate. In science, as in other fields, chatbots have become colleagues who can autonomously complete real-world tasks end-to-end.
One example is Tokyo-based Sakana AI. AI scientist. Announced in mid-2025 and currently in its second version, the Japanese technology company is touting it as “the first comprehensive system for fully automated scientific discovery.”
AI scientists scan existing literature, generate hypotheses, write and run code, and analyze results to write complete research papers, with little human involvement. Just like any young scientist, you reason, make mistakes, and revise.
What’s the evidence? AI Scientist academic paper will be released in 2025. International Conference on Learning Representations. This represents something truly new. Autonomous AI systems develop a gentler version of turing test By demonstrating scientific quality, if not machine intelligence (yet). In addition, the AI Scientist system A paper has been published in Nature In March 2026.
Other significant achievements include a live demonstration by Singapore-based startup Analemma. Fully automatic research system (Phallus) in February. I wrote 166 complete machine learning research papers in about 417 hours. This equated to one paper every two-and-a-half hours, costing approximately US$1,100 (£810) each.
Recently announced Google Cloud AI Research paper orchestratakes a researcher’s raw experiment logs and rough notes and transforms them into a submission-ready manuscript with figures and verified citations. In a blind evaluation by 11 AI researchers, it easily outperformed existing autonomous systems in this area.
spent twenty years Research on disruptive innovationI think we’ve crossed a significant threshold. Although AI systems still have a long way to go to match the best achievements of humans, the era of fully automated research has arrived.
Impact on academia
The advent of autonomous research systems is impacting academic systems that are under severe strain in many countries. Over the past decade, the number of articles submitted to academic journals has grown much faster than in the past. Group of qualified reviewersleading to the suggestion that the scientific publishing system looks like this: “Overwhelmed”.
If a system like Fars can produce thousands of papers per year, the scientific publishing infrastructure will be faced with volumes of papers it was never designed to handle. Some academic reviews are already confirmed to be in use. AI-generated content. As the number of submissions continues to grow, the role of published academic papers as definitive signals of the quality and skill of human researchers may change.
The optimistic view is that AI has the potential to move academia away from a heavy reliance on volume-based metrics and toward a focus on the impact and innovation of publications. this is reform People who criticize the current system I’ve been looking for it for a long time.
Less optimistically, as AI research expands, an academic system designed for consistent and methodologically defensible contributions may lead to an increasing proportion of incremental rather than fundamentally novel scientific contributions. As a result, both the quality and originality of the research can be compromised.
Science has always needed heretics to advance. Galileo, the Italian astronomer, is known as the “father of modern science.” withdraw his defense of heliocentric theory Before the Inquisition of the Catholic Church. Hungarian doctor Ignaz Semmelweis died in a psychiatric hospital after failing to convince his colleagues that: Hand washing can save lives.
But historically, the ability of scientific institutions to encourage radical approaches has also been a mainstay of scientific progress. To maintain this, AI systems must be trained to maximize novelty and transformation, rather than relevance and incremental progress.
How AI will impact creative industries
The transformative effects of this new kind of AI go far beyond scientific research. A notable example is epstein file. This fully AI-generated podcast topped the UK Apple Podcasts and Spotify charts in early 2026, collecting 700,000 downloads in its first week.
The music evolves further and more conflicts arise. By mid-2025, there will be bands entirely generated by AI. velvet sunset It was attracting more than 1 million monthly Spotify listeners. In 2026, AI tracks began replacing human music in popular playlists, forcing platforms to introduce artist protection features. Deezerfaces around 50,000 AI-generated uploads every day and has started filtering them out of its curated list.
Ownership remains the elephant in the room. US courts are dominated AI-generated works are not copyrightable, as human authorship remains a legal requirement. AI can be produced on an industrial scale, but the product cannot be legally owned.
This is important far beyond intellectual property law. In the creative industries, it threatens the royalty streams, licensing agreements, and catalog valuations upon which artists, labels, and publishers have built their entire business models for generations.
Meanwhile, in science, the entire incentive structure based on the fundamental assumption that knowledge is generated and owned by humans has been destabilized. When that assumption collapses, so do many of the institutional logics that have defined how expertise is produced, rewarded, and trusted.
Across all these fields, the question is no longer whether AI can produce the work. Rather, it’s about whether you’ve given enough thought to what you’ll gain and what you’ll lose when it happens.
Sorin MS Cramer
Sorin MS Cramer is Professor of Strategy and International Business at the University. University of Southampton Visiting Professor Otto Monsted at Copenhagen Business School. His research focuses on various aspects of strategy and management in international comparative contexts and has been published in the Journal of Management, Journal of International Business Studies, Research Policy, Academy of Management Learning and Education, Journal of World Business, Journal of Product Innovation Management, Leadership Quarterly, Organization Studies, and Journal of Business Ethics.
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