Executive Summary
Generative AI (GenAI) emerges as a transformative strategic lever for European industry, representing a profound opportunity to reinvigorate economic competitiveness, and drive innovation and productivity across multiple sectors. The technology promises a significant GDP boost, spanning critical business functions from product design to customer operations.
The path to realising this potential is complex and multifaceted. European companies confront various challenges, most notably a profound skills deficit, along with implementation barriers such as high development costs, lack of trust, and a fragmented regulatory landscape. Delivering on its potential requires a holistic approach that integrates technological capabilities, workforce development, and responsible innovation. The global race for AI leadership is accelerating and Europe cannot afford to stand still.
Key Strategic Challenges and Opportunities:
- Boosting Industry Players’ Adoption and Scaling of Generative AI: The integration of GenAI requires strategic identification of promising use cases across functions such as office productivity, software engineering, customer service, content creation, and product design. Organisations must overcome barriers related to developing clear business cases, measuring value, and managing high costs.
- Developing and Adapting Skills in Europe: Workforce transformation is critical to GenAI adoption. This involves addressing skills shortages, managing potential job displacement, and creating comprehensive training programmes. Companies need to develop change management strategies that help employees view GenAI as an opportunity for professional growth rather than a threat.
- Building Robust and Efficient Foundations: Successful GenAI implementation requires addressing fundamental challenges in data preparation, model training, and deployment. This includes ensuring data availability and quality, sufficient computing power, and developing cloud & connectivity infrastructure.
- Building Trusted and Responsible GenAI: Creating trustworthy AI systems necessitates a comprehensive approach to risk management, cybersecurity, and ethical considerations. To support industry in this journey and provide legal certainty, it is key to ensure the consistent and harmonised implementation of the AI Act and related legislation across the EU.
- Building Sustainable Generative AI: Environmental considerations are crucial in GenAI development. Organisations must balance technological potential with sustainability goals, understanding and mitigating the environmental impact of data centres and computing infrastructure while exploring how GenAI can support broader sustainability initiatives.
Introduction
Generative AI (hereafter “GenAI”) presents a considerable opportunity for European industry. It promises applications across sectors and functions, from supporting and improving decision-making to expanding creative possibilities and driving efficiency gains through timesaving and automation. It will enable businesses to rethink what is possible, with the potential to improve productivity across the economy.
European businesses see the opportunity and are moving to seize it: more than half (57%) of European executives rank AI and Generative AI among the top technology investment priorities for the next 12–18 months, making it the top priority of European companies among other digital technologies.
Fully capitalising on the opportunity of GenAI is crucial for the European economy, contributing to the urgent goal of improving Europe’s waning industrial competitiveness. Europe’s growth has been sluggish compared to other parts of the world and boosting our competitiveness is the vital strategic objective identified in the report by Mario Draghi and being pursued by the European Commission under President Ursula von der Leyen’s leadership.
Mario Draghi emphasises that “the EU’s competitiveness will increasingly depend on the digitalisation of all sectors and on building strengths in advanced technologies, which will drive investment, job and wealth creation.” His report stresses that while Europe largely missed out on the first digital revolution, Europe still has an opportunity to capitalise on the next digital revolution triggered by AI, and in particular Generative AI.
However, Europe and European companies face numerous obstacles and challenges in developing and scaling industrial GenAI solutions, while other players press ahead in advancing their capacities, as illustrated by the announcement of the Stargate Project to massively boost AI infrastructure in the U.S. and the significant Chinese advancements made with the DeepSeek AI model. This paper outlines what is needed and what those challenges are, and the actions that public authorities and private companies can take together and in concert to capitalise on the opportunities presented by GenAI. The annex includes a series of stories illustrating existing use cases from companies led by the Members of ERT.
“More than half (57%) of European executives rank AI and Generative AI among the top technology investment priorities for the next 12–18 months, making it the top priority of European companies among other digital technologies.”
1. Boosting Industry Players’ Adoption and Scaling of Generative AI
Since it came to the fore in late 2022, adopting GenAI has become a strategic priority of a large majority of companies – according to research, some 80% of organisations have increased their investments in GenAI in 2024 compared to the year before. They have invested heavily in efforts to develop and deploy GenAI – some $110M on average. The opportunity for Europe is considerable, with some studies estimating a potential 8% boost to Europe’s GDP over 10 years if GenAI is widely adopted.
Moreover, the opportunity is broad in nature, with use cases implemented across a broad spectrum of corporate functions, as diverse as HR, IT and logistics to sales, finance and product design. Generative AI will also contribute to the next wave of Agentic AI, enhancing decision-making and autonomous capabilities of agents. As illustrated in Mario Draghi’s report, fully exploring this breadth will be a key factor in capitalising on the opportunities presented by GenAI for European competitiveness.
However, most organisations are still in the pilot phase. In most cases, they are yet to identify which use cases offer the most promise and can be scaled. Both while prototyping or scaling a solution, there are some points of attention to consider in order to create value.
Identifying promising use cases
The market is currently focusing on several main areas that hold most promise:
General office productivity
GenAI can be used to enhance office productivity by automating repetitive tasks like drafting emails, summarising documents, and creating reports, saving time for employees to focus on strategic work. It can also provide quick insights and suggestions, streamline workflows, and support decision-making through data analysis and trend identification.
Software engineering
GenAI can boost software engineering productivity by automating code generation, debugging, and refactoring, saving time for developers to focus on complex problem-solving and innovation. It can also assist in testing and documentation, reduce errors, and provide real-time suggestions, ultimately accelerating development cycles and enhancing code quality.
Knowledge retrieval and synthesis
GenAI can quickly retrieve and synthesise information from large data sources, providing concise, contextually relevant summaries that streamline knowledge management.
Customer and employee service and experience
GenAI can enhance customer and employee service by providing instant, personalised responses to inquiries, streamlining support processes and reducing response times.
Content creation and localisation
GenAI can streamline content creation by generating text, images, and multimedia assets tailored to specific audiences. It can also be used to quickly adapt content across languages and cultural contexts. Moreover, it enables hyper-personalisation by customising content to individual preferences and behaviours, enhancing engagement and effectiveness.
Multilanguage work and translation
Multilanguage work and translation can stimulate the European market, lowering languages barriers between citizens and for business: GenAI could really simplify an access to all European countries market for companies without experts in the different European languages.
Product design and R&D
Use of GenAI can accelerate product design and R&D by generating design prototypes, simulating scenarios and analysing performance data, potentially speeding up innovation cycles. It can also be used in identifying trends, optimising designs, and suggesting novel features, enabling teams to make data-driven decisions and enhance product functionality. However, some organisations find that it is not always capable of tackling the most complex problems in product design.
Back-office process automation
GenAI can automate back-office processes by handling routine tasks like data entry, document processing, and report generation, reducing manual effort and improving accuracy. It can also be used for more advanced purposes to streamline workflows, for instance by aiding in categorising information, routing tasks, and identifying inefficiencies.
This list is just an initial snapshot of the current state of play; with even more promising use cases expected to emerge over time.
