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From Algorithms to Assets - How AI Reshapes Enterprises’ IP Investment Strategies and Legal Protection

Guadagni, Arianna LU and Vasile, Vito LU (2026) HARN63 20261
Department of Business Law
Abstract
This thesis examines how the rise of artificial intelligence (AI) is reshaping the
protection of inventions, with a focus on patents and trade secrets at the
international and, particularly, European level, based on the findings’ data.
It begins by defining AI from technical, legal, and economic perspectives,
emphasising the growing importance of intangible assets in the modern economy,
where AI-related resources such as algorithms, data, and software increasingly
drive firms’ value and competitive advantage, underscoring the strategic importance of intellectual property (IP) protection.
The thesis then explores how enterprises leverage patents and trade secrets within
the European legal framework, primarily governed by the... (More)
This thesis examines how the rise of artificial intelligence (AI) is reshaping the
protection of inventions, with a focus on patents and trade secrets at the
international and, particularly, European level, based on the findings’ data.
It begins by defining AI from technical, legal, and economic perspectives,
emphasising the growing importance of intangible assets in the modern economy,
where AI-related resources such as algorithms, data, and software increasingly
drive firms’ value and competitive advantage, underscoring the strategic importance of intellectual property (IP) protection.
The thesis then explores how enterprises leverage patents and trade secrets within
the European legal framework, primarily governed by the European Patent Convention (EPC) and the Trade Secrets Directive.
The analysis shows that AI challenges traditional IP legal regimes, particularly
regarding inventorship and patentability of AI-assisted or AI-generated inventions, and uses empirical evidence to highlight the evolution of firms’ IP strategies in choosing between patents and trade secrets to protect inventions, leading to the conclusion that enterprises increasingly adopt hybrid IP solutions, combining them to maximise protection and economic returns.
Ultimately, the thesis argues that the evolution of AI necessitates a more flexible and integrated approach to IP protection. It underlines the need for potential legal adaptations to address emerging issues of authorship and technological autonomy, ensuring that the international IP framework remains effective in fostering innovation and competitiveness in an AI-driven economy. (Less)
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author
Guadagni, Arianna LU and Vasile, Vito LU
supervisor
organization
course
HARN63 20261
year
type
H1 - Master's Degree (One Year)
subject
keywords
Artificial Intelligence (AI), Intellectual Property (IP), Patents, Trade Secrets, Intangible Assets, Inventorship, Hybrid IP Protection, Innovation.
language
English
id
9233764
date added to LUP
2026-06-09 11:50:28
date last changed
2026-06-09 11:50:28
@misc{9233764,
  abstract     = {{This thesis examines how the rise of artificial intelligence (AI) is reshaping the
protection of inventions, with a focus on patents and trade secrets at the
international and, particularly, European level, based on the findings’ data.
It begins by defining AI from technical, legal, and economic perspectives,
emphasising the growing importance of intangible assets in the modern economy,
where AI-related resources such as algorithms, data, and software increasingly
drive firms’ value and competitive advantage, underscoring the strategic importance of intellectual property (IP) protection.
The thesis then explores how enterprises leverage patents and trade secrets within
the European legal framework, primarily governed by the European Patent Convention (EPC) and the Trade Secrets Directive.
The analysis shows that AI challenges traditional IP legal regimes, particularly
regarding inventorship and patentability of AI-assisted or AI-generated inventions, and uses empirical evidence to highlight the evolution of firms’ IP strategies in choosing between patents and trade secrets to protect inventions, leading to the conclusion that enterprises increasingly adopt hybrid IP solutions, combining them to maximise protection and economic returns.
Ultimately, the thesis argues that the evolution of AI necessitates a more flexible and integrated approach to IP protection. It underlines the need for potential legal adaptations to address emerging issues of authorship and technological autonomy, ensuring that the international IP framework remains effective in fostering innovation and competitiveness in an AI-driven economy.}},
  author       = {{Guadagni, Arianna and Vasile, Vito}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{From Algorithms to Assets - How AI Reshapes Enterprises’ IP Investment Strategies and Legal Protection}},
  year         = {{2026}},
}