Intellectual Property Law Dissertation Topics 2026-27

The March 2026 U-turn in the UK's Report on Copyright and Artificial Intelligence (DSIT, IPO, DCMS, CP2602959) is the single most important thing to read this year. It kills the earlier direction of travel on a broad TDM exception with opt-out and instead opens up five live research fronts: licensing markets, opt-out mechanisms, transparency duties, digital replica rights, and whether copyright should apply to purely AI-generated works. If you're an LLM student and you want a supervisor's attention, a jurisdictionally tight doctrinal analysis of any one of those five fronts, cited against the 2026 Report, is the strongest opener.

The tier-1 journals are already crowded on this. Adam Buick's Copyright and AI training data, transparency to the rescue? in JIPLP March 2025 (20(3), 182 to 192) sets out the transparency-duty side but explicitly leaves open how those duties should actually be enforced across jurisdictions and what they'll do to emerging licensing markets. That's your dissertation-sized gap, not the abstract question of whether transparency matters. Pair the Buick paper with the 2026 UK Report and you have a defensible LLM thesis in one sitting.

Thomas Meitinger's short but sharp piece in JIPLP November 2025 (20(11), 697 to 698) flags a legal-gap almost nobody has written about at length: prior art published on the same day as a patent filing cannot be used to attack novelty under section 3(1) of the German Patent Act, and AI now makes same-day appropriation dramatically more likely. A comparative UK and German analysis of this same-day gap, with data pulled from EPO Register and DPMA filings, would sit comfortably at PhD level and is genuinely unclaimed.

The trade-secret side has its own live gap. Ozcan and colleagues in Strategic Change (2025) write that there is "an urgent and significant gap in existing trade secret management practices and academia regarding the mitigation of trade secret misappropriation," and that gap is now colliding head-on with the EU AI Act's transparency obligations for general-purpose models (see also Uroš Ćemalović in JIPLP Feb 2026, 21(2), 104 to 113). How do you protect a proprietary algorithm when the same law demands you disclose meaningful information about it? Empirical work here, with interviews inside UK firms subject to the EU AI Act's extraterritorial reach, is exactly what supervisors are asking for right now.

One quantitative anchor to keep in mind: plaintiffs filed 4,547 patent cases in US district courts in 2025, a 19.6% increase on 2024 and the highest total in the 2016 to 2025 window (Lex Machina 2026 Patent Litigation Report, 6 August 2026). Patents are not going quiet. They're getting louder.

The transatlantic policy strand is now genuinely comparative. Bernd Justin Jütte and Paulina Ryszkowska in JIPLP September 2026 (21(9), 654 to 659) map the parallel March 2026 reports of the European Parliament and the UK House of Lords on AI and copyright, which together frame the next legislative round in both jurisdictions. If you want a live comparative LLM thesis with primary policy documents on both sides, that's your reading list for chapter one.

Doctrinal analysis of the three regulatory routes the UK Government now has, with a policy recommendation.

Gap: The March 2026 U-turn left three live options on the table and no consensus on which to legislate.

Methodology: Doctrinal legal analysis of the Report on Copyright and Artificial Intelligence and the Data (Use and Access) Act 2025, plus comparative reading of the EU AI Act (August 2026 phased implementation).

Data source: gov.uk publications; EUR-Lex; JIPLP; House of Commons Library.

Source: UK Government, Report on Copyright and Artificial Intelligence (CP2602959), 18 March 2026.

Compares how UKIPO and the EPO Boards of Appeal are treating inventiveness where AI contributed to conception.

Gap: The AI Overview identifies AI-assisted inventorship as a top four dissertation theme, and no settled Board doctrine yet exists.

Methodology: Doctrinal case analysis of at least 30 EPO Board decisions since 2022, cross-referenced with UKIPO Hearing Officer decisions.

Data source: EPO Boards of Appeal case law database; UKIPO decisions register.

Source: Google AI Overview, September 2026; Meitinger, JIPLP Nov 2025 (20(11), 697 to 698).

Doctrinal and normative analysis of whether the UK needs a statutory personality right to sit alongside passing off.

Gap: Elton John and Dua Lipa's public interventions in early 2026 preceded the March 2026 U-turn but statutory reform has not followed.

Methodology: Doctrinal analysis plus comparative UK, US (right of publicity), and Indian High Court personality-rights case law.

Data source: BAILII; Westlaw UK; Manupatra for Indian High Court cases.

Source: Lewis Silkin analysis of the UK Copyright and AI Consultation, 24 March 2026.

Evaluates the deterrent effect and technical durability of dynamic blocking orders granted by the High Court.

Gap: The AI Overview flagged digital piracy and dynamic injunctions as a top four theme, but the empirical evidence on effectiveness is thin.

Methodology: Doctrinal review of at least 20 Football Association Premier League Ltd and UEFA blocking orders, plus interviews with three UK ISPs.

Data source: Rolls Building filings; BAILII; PIPCU public reports.

Source: PIPCU funding renewed at £3m per year, April 2026 to March 2029 (IPO / DSIT).

Empirical study of how UK firms are updating reasonable-steps policies after ChatGPT-style tools entered the workplace.

Gap: Ozcan et al. (Strategic Change, 2025) name "an urgent and significant gap" in trade-secret management practice.

Methodology: Mixed-methods: doctrinal review of the Trade Secrets (Enforcement, etc.) Regulations 2018 plus 15 to 20 semi-structured interviews with in-house counsel.

Data source: Interview data; Practical Law policy templates; ICO guidance.

Source: Ozcan et al., Strategic Change, 2025.

Doctrinal analysis of sections 22 to 27 CDPA 1988 applied to trained model weights.

Gap: Adam Buick (JIPLP March 2025) opens transparency but leaves the "is the model itself a copy?" question unresolved.

Methodology: Doctrinal analysis, plus a comparative reading of Dornis on "making available" and IIC 2025 European approaches.

Data source: CDPA 1988; Getty Images v Stability AI filings; JIPLP; IIC.

Source: Adam Buick, JIPLP March 2025, 20(3), 182 to 192.

Empirical analysis of specification-width in UK trade mark applications before and after the Supreme Court's SkyKick judgment.

Gap: SkyKick reset the doctrine but the filing-behaviour data is only now emerging.

Methodology: Quantitative analysis of at least 500 UKIPO trade mark applications 2023 to 2026, coded for specification width and bad-faith challenges.

Data source: UKIPO trade mark register; UKIPO Hearing Officer decisions.

Source: UKIPO Corporate Plan 2025 to 2026 (IPO), which prioritises one-IPO transformation and register quality.

Analyses whether section 3(d) meaningfully filters incremental patents or simply delays generic entry.

Gap: India query cluster is the second-strongest keyword family for this subject, and no page-1 competitor answers it doctrinally.

Methodology: Doctrinal analysis of 40 pre-grant opposition decisions 2020 to 2026, cross-referenced with Novartis v UOI progeny.

Data source: Indian Patent Office decisions; Manupatra; SpicyIP archive.

Source: WIPO IP Statistics Data Center, 2025 filings by India office.

Empirical study of whether GIs registered under the 1999 Act are being enforced against post-registration quality drift.

Gap: The IPR-in-India cluster is under-served, and post-registration control is where GI policy actually breaks down.

Methodology: Mixed-methods: doctrinal review plus semi-structured interviews with GI registered proprietors' associations.

Data source: GI Registry (Chennai); Manupatra; interviews.

Source: WIPO Treaty on IP, Genetic Resources and Associated Traditional Knowledge (adopted 2024).

Tests whether the transparency template under Article 53 EU AI Act actually helps rights-holders enforce.

Gap: Adam Buick names this as the unresolved practical question in JIPLP March 2025.

Methodology: Doctrinal analysis of Article 53 EU AI Act plus at least 10 semi-structured interviews with UK collecting societies.

Data source: EUR-Lex; EU AI Office templates; interview data with PRS for Music, PPL, ALCS.

Source: Ćemalović, JIPLP February 2026, 21(2), 104 to 113.

Comparative doctrinal analysis of section 3(1) DPatG and section 2 UK Patents Act 1977, plus quantitative sampling of same-day EPO and DPMA filings 2020 to 2026.

Gap: Prior art published on the same day as a patent filing cannot be used to attack novelty, and AI substantially raises the odds of same-day appropriation.

Methodology: Comparative doctrinal analysis plus quantitative sampling of same-day EPO and DPMA filings.

Data source: EPO Register; DPMA Register; PATSTAT.

Source: Thomas Heinz Meitinger, "What difference does one day make?" JIPLP November 2025, 20(11), 697 to 698.

Comparative case-law analysis of German, French, and Italian first-instance rulings on generative AI outputs, cross-referenced with UK Getty Images v Stability AI.

Gap: National courts will read "making available" differently for AI models, and it's unclear whether a harmonised EU approach is even feasible.

Methodology: Comparative case-law analysis across German, French, and Italian courts.

Data source: Juris; Legifrance; EUR-Lex; BAILII.

Source: Tim W. Dornis, "Generative AI, Reproductions Inside the Model, and the Making Available to the Public," IIC 2025, 56(5), 909 to 938.

Doctrinal analysis of Articles 3, 4 CDSM Directive, plus survey of 40 UK and EU academic AI researchers on their perceived legal risk.

Gap: The interaction between the research exceptions and the Article 4 CDSM TDM exception is not settled, and this uncertainty chills academic AI research specifically.

Methodology: Doctrinal analysis plus survey of 40 UK and EU academic AI researchers.

Data source: EUR-Lex; UKRI-funded project documentation; survey data.

Source: Senftleben et al., "Towards a European Research Freedom Act," IIC 2025, 56(7), 1329 to 1358.

Doctrinal analysis plus FOI-request data from UK Border Force on IP seizures in transit 2021 to 2026.

Gap: The controversy over goods in transit is unresolved, and post-Brexit UK Border Force practice has not been benchmarked against EU customs.

Methodology: Doctrinal analysis plus FOI-request data from UK Border Force.

Data source: HMRC and Border Force FOI disclosures; EU Customs IP Enforcement Report.

Source: S. Pengoriya, "A case against enforcement of patent rights in transit," Journal of World Intellectual Property, March 2025, 28(1), 303 to 320.

Quantitative patent-family analysis of the top 20 global cosmetics filers 2015 to 2026, with pre- and post-Treaty subsamples.

Gap: How biopiracy concerns are addressed in patent disclosure-of-origin requirements, and whether the WIPO Treaty will actually change corporate filing behaviour.

Methodology: Quantitative patent-family analysis of the top 20 global cosmetics filers.

Data source: PATSTAT; Espacenet; WIPO PATENTSCOPE.

Source: D. J. Jefferson and D. F. Robinson, "Biopiracy and beauty brands?" Journal of World Intellectual Property, 2025, 28, 640 to 664.

Whether the renewed Police Intellectual Property Crime Unit funding produces measurable increases in IP-crime prosecutions and disruption operations.

Gap: The renewal was confirmed in 2026 but no independent evaluation of the previous funding period has been published for LLM-level testing.

Methodology: Mixed-methods: quantitative analysis of PIPCU annual reports 2015 to 2026 plus 8 to 10 interviews with brand-protection counsel.

Data source: PIPCU annual reports; City of London Police FOI disclosures; interview data.

Source: PIPCU funding renewed at £3m per year, April 2026 to March 2029 (IPO / DSIT press release, 2026).

Whether the UK's specialist FRAND rate-determination track and the EU's withdrawn SEP Regulation produce different licensing outcomes for implementers.

Gap: The UK is consulting on transparency and rate determination in 2026 while the EU has just withdrawn its proposed SEP Regulation. This natural divergence has not yet been analysed for LLM audiences.

Methodology: Doctrinal analysis plus quantitative analysis of at least 30 English Patents Court FRAND rate determinations 2018 to 2026.

Data source: BAILII; UKIPO SEP consultation responses; European Commission SEP proposal archive.

Source: UKIPO SEP consultation and EU SEP Regulation withdrawal, 2025 to 2026.

Whether the confidentiality carve-outs in the EU Data Act (Regulation 2023/2854) meaningfully protect algorithmic trade secrets in mandated business-to-business data sharing.

Gap: The Data Act's confidentiality provisions have not yet been stress-tested doctrinally against Directive (EU) 2016/943.

Methodology: Doctrinal analysis of the Data Act and Trade Secrets Directive, plus scenario-based case studies drawn from IoT and connected-vehicle contexts.

Data source: EUR-Lex; European Commission implementing acts; industry submissions on Data Act implementation.

Source: EU Data Act entered application on 12 September 2025.

Whether the £2,250 grant produces measurable increases in trade mark and patent filings by recipient SMEs compared to a matched control group.

Gap: The scheme is running but there is no independent evaluation of its downstream filing effect.

Methodology: Quantitative matched-pairs analysis of grant recipients against non-recipient SMEs, using UKIPO register data 2022 to 2026.

Data source: UKIPO register; CITMA and GJE published data; UKIPO grant recipient list (FOI where necessary).

Source: UKIPO IP Audit Scheme, grants up to £2,250 for eligible SMEs (CITMA; GJE).

Whether the March 2026 Report's opening on removing copyright from purely AI-generated works can be reconciled with section 9(3) CDPA 1988.

Gap: The Report opens the question but does not resolve it, and no doctrinal analysis of the section 9(3) interaction has yet appeared in mainstream UK journals.

Methodology: Doctrinal analysis of section 9(3) CDPA, plus comparative reading of US Copyright Office guidance (2023, 2025) and Chinese Beijing Internet Court rulings.

Data source: CDPA 1988; UK Government gov.uk publications; US Copyright Office; Beijing Internet Court press summaries.

Source: UK Government, Report on Copyright and Artificial Intelligence (CP2602959), 18 March 2026.

Doctrinal analysis of the legal status of shadow libraries (Anna's Archive, Library Genesis, SciHub) as intermediary sources of copyrighted works used in AI training, and the secondary-liability route to reach them under UK CDPA 1988 and Article 8(3) InfoSoc Directive.

Gap: Rademeyer & Selvadurai (JIPLP Jan 2026) explicitly frame this as an under-analysed area: "there has been limited analysis of the legal status and treatment of the underlying shadow libraries, which facilitate such infringement."

Methodology: Doctrinal analysis of UK and EU liability regimes plus case-mapping of at least 10 injunction proceedings against shadow-library operators 2022 to 2026.

Data source: BAILII; EUR-Lex; Elsevier v Sci-Hub filings; JIPLP archive.

Source: Rademeyer & Selvadurai, JIPLP January 2026, 21(1), 22 to 35.

Q1. "any ideas for intellectual property law dissertation or corporate crime?" (The Student Room)

Yes, and the honest answer is you should pick one, not both. If you want the IP side, the strongest 2026 entry point is the interaction between the UK Government's March 2026 Report on Copyright and Artificial Intelligence and section 9(3) CDPA 1988 on computer-generated works. That gives you a defined regulatory moment, a defined statutory provision, and a defined jurisdiction, which is exactly the trio your supervisor is looking for. If the corporate-crime pull is really about IP crime rather than fraud, look at PIPCU: funding was renewed at £3m per year for April 2026 to March 2029, and there's no independent LLM-level evaluation of the previous funding period yet. That's a live gap. It's doctrinal at the edges and empirical at the centre, and it lets you keep both interests inside one dissertation. Whichever you pick, name your right (copyright or a criminal IP provision), name your jurisdiction (UK), and name your method (doctrinal, comparative, or mixed) in the first paragraph of your proposal.

Q2. "How can I write a research paper on intellectual property rights?" (Quora)

Start by narrowing hard. "Intellectual property rights" is a subject area, not a research paper. Pick one right (copyright, patents, trade marks, designs, or trade secrets), then pick one legal test inside that right (fair use, inventive step, bad faith, reasonable steps, or novelty), then pick one jurisdiction (UK, EU, India, US, or a specific comparative pair). Your title should let a supervisor see all three. For structure, most IP papers work on a doctrinal spine: introduce the legal test, trace its statutory basis, walk through the leading cases, identify the current controversy, propose a resolution. If you're going empirical, add a defined data source (UKIPO register, PATSTAT, WIPO Lex, HeinOnline for scholarship, interviews with a named counsel population) and defend your sample size against a threshold your supervisor will accept. The single most common rejection reason is scope creep. If your title still contains the words "role of" or "impact of" without a named legal test, your supervisor will send it back.

Q3. "What are the new topics in copyright or IP law in the internet environment to write about in a dissertation?" (Quora)

The five internet-facing copyright topics I'd rank highest for 2026 are: generative AI training and copyright under the March 2026 UK Report; whether a trained AI model itself is a copy under UK secondary infringement rules; dynamic website-blocking injunctions against live sports streaming; platform liability for user uploads under Article 17 of the EU CDSM Directive; and AI voice cloning as a case for a statutory UK personality right. Each of those has a defined 2025 to 2026 source you can cite in the proposal: Adam Buick in JIPLP March 2025 for the transparency angle; Tim Dornis in IIC 2025 for the "making available" question; the AI Overview and PIPCU funding renewal for the piracy side; and Lewis Silkin's March 2026 analysis of the UK Copyright and AI consultation for the personality-right side. Avoid framing your topic as "impact of the internet on copyright." That was fresh in 2005 and is now generic.

Q4. "What do you recommend as good research topics for copyright law?" (Quora)

Four routes, in order of supervisor-friendliness for 2026. First, licensing versus opt-out versus exception for AI training under the Data (Use and Access) Act 2025, anchored to the March 2026 UK Report. Second, transparency-duty enforcement under Article 53 EU AI Act, testing whether the templates actually help rights-holders. Third, rights retention policies at UK universities and their effect on author copyright. Fourth, orphan works licensing and mass digitisation in UK museums, which is quieter but chronically under-researched. For the first three, your primary reading list is short and current: the 2026 UK Report, the EU AI Act, the JIPLP March 2025 Buick paper, and the JIPLP February 2026 Ćemalović paper. That's enough for a strong LLM proposal. Do not pad the reading list before you've read those four. If you want quantitative work, the Institute of Physics has published usable rights-retention adoption data by UK Russell Group members that you can code into a longitudinal analysis.

Q5. "What are the PhD options in patent law?" (Quora)

Three PhD-scale routes are open right now. First, the same-day prior art gap under section 3(1) DPatG and the UK section 2 Patents Act 1977 equivalent, following the November 2025 Meitinger piece in JIPLP: this is unclaimed and demands original comparative EPO and DPMA data. Second, sufficiency of disclosure for machine-learning inventions before the EPO Boards of Appeal, which is where the doctrine will settle in the next three years. Third, forum shopping between the Unified Patent Court and the English Patents Court after the UK's non-participation in the UPC, which is now generating enough decisions for empirical work. For any of these, plan your data access before you commit. FRAND rate data is almost never disclosed, industry interviews sit behind confidentiality obligations, and full patent-prosecution files are not always digitised. PATSTAT and EPO Register together will cover most quantitative needs, but confirm access through your institution's library subscription before your first supervisor meeting.

Q6. "What's the scope of IPR law in India, especially for an independent practitioner?" (Quora)

For a dissertation angle rather than a career answer, four Indian topics are undersupplied right now. Section 3(d) of the Indian Patents Act and incremental pharmaceutical innovation is the classic, and it stays fresh because the Delhi High Court keeps generating decisions. Pre-grant opposition procedure is the second: is it a genuine safeguard for access to medicines, or is it being used to delay generic entry? Third, personality rights and AI deepfakes before the Indian High Courts, where the case law is moving faster than statute. Fourth, post-registration quality control of Geographical Indications for handloom and handicraft products, which is the area where GI policy actually breaks down in practice. Data access is friendlier than students assume. The Indian Patent Office decisions are online, SpicyIP has a strong archive of pre-grant opposition analysis, and Manupatra covers most High Court judgments. For quantitative work, WIPO IP Statistics Data Center gives you India-office filing series free of charge.

Free database of IP treaties, national IP legislation, and court decisions from over 190 jurisdictions. Access is free at wipo.int/wipolex. This is the best first stop for any comparative or treaty-based IP dissertation, and the coverage of national implementing legislation for the WIPO Treaty on Genetic Resources is unusually strong.

Free global IP activity statistics: patent, trade mark, industrial design, and PCT filing series by office and by year. Access is free at wipo.int/ipstats. Use this for any quantitative framing sentence in an IP dissertation, particularly for India-office and China-office series where domestic databases are harder to reach.

The definitive dataset for bibliographic, citation, and legal-status data on patents. Access is through institutional subscriptions from the EPO. If your dissertation needs quantitative patent-family analysis, PATSTAT is what you want; Espacenet is fine for retrieval but not for statistical work.

UK-specific IP filing statistics, economic research, and the IPO Corporate Plan documentation. Access is free at gov.uk. UKIPO also publishes Hearing Officer decisions, which are essential for empirical work on UK patent and trade mark examination practice.

Full-text law journals including a strong IP collection. Access is through university library subscriptions at heinonline.org. HeinOnline is the fastest way to build a defensible reading list for the doctrinal sections of an IP thesis, and its historical coverage makes it superior to open-access aggregators for pre-2010 case commentary.

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