Artificial intelligence is neither a miracle solution nor an existential threat. It represents a major growth opportunity, comparable to the advent of information technology twenty years ago. For software publishers and IT service providers, the impact is clear: those who leverage it effectively could at least double their revenue within a decade.
Impact on EU GDP
An Additional Annual Growth of +0.7%
Philippe Aghion, Nobel Prize-winning economist, estimates that AI could increase the EU’s GDP by 0.7% annually over ten years. While significant, this impact remains manageable and is comparable to that of ICT in the 1990s and 2000s.
Source: Collège de France, lecture “Economic Opportunities, Legal Challenges, Societal Issues”
The EU’s GDP stands at approximately €18,000 billion (2024), representing the total value of all goods and services produced in the 27 Member States. Services account for 74% of the EU’s GDP (and even more in France).
An additional +0.7% per year translates to an extra €126 billion annually. This is substantial (comparable to the impact of ICT in the 1990s/2000s) but does not represent an unsustainable shock.
Two Key Takeaways:
- Risk of Concentration: The lack of competition due to the dominance of a few players (Nvidia, Amazon, Microsoft, Google, etc.) could limit the equitable distribution of created value, especially in Europe.
- Positive Impact on Employment: The automation of administrative tasks would be offset by an overall increase in productivity, creating new jobs in other areas.
Naturally, like any projection, these may be challenged by actual events. Yet, the experience and data gathered during the digital transformation of the economy seem strong enough to support these insight.
The key role of applications
Applications are integral to every professional activity. It is natural for them to gradually incorporate AI features to enhance productivity, simplify usage, and innovate with previously unimaginable functionalities.
Daily and growing usage
Professional applications are ubiquitous in the workplace. On average:
- An office employee uses 11 to 15 applications per day (Gartner, Stratapp).
- A salesperson uses 8 to 12, while a developer may use up to 15.
Examples:
➜ Administrative employeesuse 5 to 8 applications (email, ERP, Excel, video conferencing tools, etc.).
➜ Salespeople use 8 to 12 applications (CRM, PowerPoint, Excel, LinkedIn, prospecting tools, etc.).
➜ Developers use 10 to 15 applications (IDE, Slack, Jira, GitHub, monitoring tools, etc.).
Sector estimates suggest application usage ranges from 1.5 to 3 hours per day on average, depending on the role and sector. This can rise to 4-5 hours per day for highly digitalized professions (tech, data, marketing).
Analysis by company size
Research on application portfolios (SaaS + internal apps) shows:
- Very large organizations (≥1,000 employees) often have 200 to 500 applications in total.
- SMEs (10–250 employees) typically use 20 to 100 applications.
- Micro-enterprises (<10 employees) generally use fewer than 20 applications.
Even if an employee does not use all of them, a larger application portfolio mechanically increases the number of tools an employee is exposed to.
Software publishers concentrate economic impacts
Pooling resources
The purpose of a business application publisher is to pool expertise and R&D to accelerate deployment, facilitate updates, and reduce costs.
This specialization allows each company to benefit from the best technologies without having to acquire the skills or bear the associated costs themselves.
This pooling creates a powerful multiplier effect with a high impact on the economic fabric. A publisher’s customer base often includes hundreds of mid-sized companies, thousands of SMEs, and tens of thousands of micro-enterprises. All these organizations benefit automatically.
Reaching millions of users quickly
In France, SMEs and micro-enterprises account for over 50% of salaried employment. These companies are not interested in developing their own applications; for routine tasks, they rely on publisher solutions, often in SaaS mode, to avoid IT constraints.
This also applies to larger companies, even if they sometimes have the financial and human resources to adapt their tools to their needs.
Economic consequences
Significant Spending
Within the EU, IT spending amounts to approximately $1,300 billion, or €1,100 billion, representing 6.1% of the Union’s GDP. Software alone accounts for €250 billion, or 1.4%.
AI Impact: Doubling Publishers’ Revenue
One way or another, publishers will capture their share of this newly created value.
If we accept Philippe Aghion’s forecast, and if the +0.7%/year is shared equally between ICT providers and their business clients, and if the current proportions between software and IT services remain the same, we can estimate:
- Applications will contribute to an annual GDP increase of 290/(290+490) = 37% * 0.7% = +0.26%/year, or €47 billion/year for the EU.
- The revenue of application publishers will increase by €47/2 = €23.5 billion/year, or +8.1%/year. This means a 2.2x increase over 10 years, solely due to the added value of AI services integrated into applications.
Of course, there will be winners and losers. The former will fall behind, while the latter will significantly outperform.
- Losers: Those who do not seize the opportunity in time or limit themselves to decorative features.
- Winners: Those who exploit their monopolies (especially the GAFAM) and publishers who start early and build for the long term.
An opportunity to seize
Major players will attempt to establish and maintain their monopolies and find revenue sources to absorb their (unreasonably?) massive investments in data centers.
In fact, we are already seeing this in Microsoft’s price increases. It won’t be long before OpenAI and others follow suit. If not directly (token prices), it will be indirectly (inflation in the number of tokens required to perform tasks that are ultimately not so complex).
Fortunately, there are other solutions—just as effective, more economical, less energy-intensive, sovereign, and high-performing.
In conclusion: There are always good reasons to watch the trains go by—or to resolutely board them. This was true for the Internet and the cloud, and it will be true for AI. Everyone must find their own path.
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