.png)
.svg)
.jpg)
25/01/2026
Artificial intelligence is transforming all sectors of activity, from business strategy to daily uses. To effectively manage innovation and remain competitive, it is crucial to rely on reliable and current indicators. This guide summarizes the most recent and relevant AI statistics, offering a clear vision of the 2025-2026 trends, expected performances, and challenges ahead. Discover key figures, sector KPIs and actionable analyses to successfully transition to a data-driven organization.
📊 AI statistics: key figures in 2025-2026
💡 What this data reveals
- ✓ The growth of the artificial intelligence market and global investments confirm the central role of AI in the economy by 2030.
- ✓ The adoption of AI is progressing in businesses, leading to significant productivity gains and a measurable ROI.
- ✓ Web traffic generated by bots and AI exceeds half of the global total, illustrating the increasing automation of digital uses.
- ✓ Value creation through AI requires strategic structuring, targeted investments and adapted governance to maximize impact.
Market and investments
💡 What this data reveals
- ✓ Massive investment is accelerating the industrialization of AI, with major players like Amazon, Meta, and OpenAI investing hundreds of billions.
- ✓ France is experiencing a strong growth dynamic in the AI sector, especially in SMEs.
- ✓ The creation of real value remains limited: companies must move from a logic of experimentation to a measurable ROI strategy.
Adoption in business
💡 What this data reveals
- ✓ Business adoption is growing rapidly, driven by internal demand and the industrialization of uses.
- ✓ French SMEs are accelerating their transformation, but efforts remain to be made to reach the global level.
- ✓ Employee training and involvement are key to maximizing the impact of AI on performance.
Utilization rate by sector
💡 What this data reveals
- ✓ The marketing, finance and customer service sectors are the most advanced, driven by the search for personalization and efficiency.
- ✓ The automotive industry and HR are experiencing rapid growth in adoption, paving the way for new automations.
- ✓ Sectoral productivity gains vary, justifying a strategy adapted to the sector.
Deployed technologies
💡 What this data reveals
- ✓ Generative AI, chatbots and NLP are the flagship technologies, driven by daily and business uses.
- ✓ Multimodal AI is essential in training, customer service and auditing thanks to its ability to cross several types of data.
- ✓ Robotic automation accelerates the transformation of back office and administrative processes.
Impact on productivity and work
💡 What this data reveals
- ✓ Gains in productivity and creativity are now measured and tangible in all professions.
- ✓ The leverage effect of AI on performance depends on continuous training and ownership by teams.
- ✓ Companies that industrialize AI see their competitiveness increase rapidly.
Time savings and automation
💡 What this data reveals
- ✓ Automation extends to all functions, freeing up time for innovation and human added value.
- ✓ AI is accelerating the refocus of HR on creativity and talent management.
- ✓ Automating customer relationships is becoming the norm and bringing customer satisfaction.
Transformation of professions
💡 What this data reveals
- ✓ The change in jobs requires new skills and the rise of hybrid profiles.
- ✓ Functions with high emotional or strategic intelligence are the least exposed to automation.
- ✓ Training and retraining are essential to maintain employability and growth.
User perception and expectations
💡 What this data reveals
- ✓ Knowledge and use of AI are progressing, but trust has yet to be built, especially among seniors.
- ✓ The expectation of regulation and ethics is strong, constituting a challenge for social acceptance.
- ✓ The generational divide must be bridged by more pedagogy and support.
Consumers and the general public
💡 What this data reveals
- ✓ Younger generations are driving adoption and influencing expectations for digital services.
- ✓ The use of ChatGPT and generative AIs is rapidly becoming widespread among the French general public.
Professionals and employees
💡 What this data reveals
- ✓ Professionals see AI as a tool for career development and for improving the quality of work.
- ✓ The integration of AI encourages the refocusing on missions with higher added value.
Sectoral applications
Human resources and recruitment
💡 What this data reveals
- ✓ HR automation accelerates the recruitment and management of talent in France.
- ✓ AI makes it possible to better target skills and to anticipate mobility or training needs.
Marketing and content creation
💡 What this data reveals
- ✓ AI is now essential in digital marketing for the creation, optimization and personalization of content.
- ✓ AI tools make it possible to generate qualified leads and significantly increase commercial performance.
Customer service and support
💡 What this data reveals
- ✓ Support automation allows predictive and personalized management of customer journeys.
- ✓ AI improves responsiveness and customer satisfaction, while reducing operational costs.
Health and medicine
💡 What this data reveals
- ✓ The health sector benefits greatly from AI, both for the analysis of medical data and for the management of equipment and diagnostics.
- ✓ AI improves prevention and the quality of medical services through advanced predictive analyses.
Finance and banking
💡 What this data reveals
- ✓ AI tools are transforming financial management, from anomaly detection to strategic forecasting.
- ✓ Finance and tech are the sectors where automation offers the greatest leverage effect on performance.
Commerce and retail
💡 What this data reveals
- ✓ AI allows advanced personalization and automated management of flows in commerce and retail.
- ✓ Recommendation systems and predictive analytics optimize customer experiences and profitability.
Generative AI and content creation
Adoption of generative tools
💡 What this data reveals
- ✓ Google and OpenAI AI models dominate, but competition is intensifying on text and image generation, and web development.
- ✓ The massive adoption of generative tools is transforming editorial and creative practices in business.
Impact on content creation
💡 What this data reveals
- ✓ The share of content generated by AI is increasing sharply, upsetting the challenges of verification and originality.
- ✓ AI makes it possible to increase editorial productivity and improve the relevance of the content offered to audiences.
Web traffic and cybersecurity
💡 What this data reveals
- ✓ AI now generates more than half of web traffic, impacting cybersecurity and access management.
- ✓ French companies are investing in specialized AI tools to anticipate and counter cyber threats.
- ✓ New AI threats (deepfakes, automated attacks) require greater vigilance and governance arrangements.
ROI and financial performance
💡 What this data reveals
- ✓ The ROI of generative AI is becoming a central argument in the strategic decisions of senior management.
- ✓ The financial gains are particularly marked in support and IT functions.
- ✓ Businesses need to structure their AI governance to maximize customer value creation.
Challenges and future perspectives
Ethical and environmental concerns
💡 What this data reveals
- ✓ The challenges of energy efficiency and digital frugality are becoming critical with the rise of AI.
- ✓ Diversity and transparency are at the heart of the debates for responsible and socially accepted AI.
- ✓ Businesses must anticipate regulatory constraints and adopt ethical governance.
Adoption challenges and barriers
💡 What this data reveals
- ✓ Access to AI skills and measuring ROI are the two biggest obstacles to industrialization.
- ✓ European regulatory constraints are becoming an asset for customer credibility and trust.
Trends 2026 and beyond
💡 What this data reveals
- ✓ The acceleration of AI uses and investments will transform all jobs and sectors by 2030.
- ✓ Automated content creation is growing rapidly, requiring new tools for verification and analysis.
🎯 Conclusion and recommendations
The 2025-2026 data confirm the exponential rise of artificial intelligence in the global economy, with major impacts on productivity, value creation, business transformation and the governance of organizations. AI is an essential driver of performance, provided that ethical, environmental and regulatory issues are mastered. The increasing adoption of generative tools, the structuring of data, and the investment in training are the keys to a successful transition to smart and responsible business.
🚀 Priority actions for 2026
- Deploy a continuous training plan on AI for all employees, adapted to jobs and levels of digital maturity.
- Structuring a governance dedicated to AI to drive innovation, ensure compliance and anticipate risks related to safety, ethics and environmental impact.
- Identify and automate processes with low added value (back office, customer service, content creation) as a priority to maximize ROI.
- Develop a robust data management and valorization strategy to feed AI algorithms and strengthen the quality of analyses.
- Adopt an ecodesign and frugal AI approach in order to limit the carbon footprint, water and energy consumption, and to assess the environmental impact at each stage of the AI life cycle.
🚀 FAQ
📊 Key figures at a glance
Global Market Growth: 37% per year (2024-2030)
Economic contribution by 2030: $15.7 trillion
Businesses with positive ROI: 74%
Average productivity gain: +40%
📈 AI market and growth
What is the growth of the global AI market?
The global artificial intelligence market is showing a annual growth of 37% between 2024 and 2030. It goes from 184 billion dollars in 2024 to a screening of 826.7 billion dollars in 2030. This exponential expansion confirms that AI is no longer a simple technological trend but a major structural transformation of the global economy.
What economic impact will AI have by 2030?
Artificial intelligence should contribute in the amount of 15.7 trillion dollars to the global economy by 2030, or approximately 26% of global GDP. This massive economic impact will affect all sectors, from health to finance, trade and industry. Businesses that adopt AI now will have a decisive competitive advantage.
What are the planned investments in AI for 2025?
Global investments in artificial intelligence will reach 200 billion dollars in 2025. Tech giants are investing massively:
- Amazon: $125 billion in AI
- Meta: $600 billion in AI infrastructures
- OpenAI: Valuation of 500 billion dollars
These colossal investments demonstrate the conviction of technology leaders that AI represents the future of economic competitiveness.
How is the French AI market evolving?
The French AI market is experiencing dynamic growth of 28.9% per year and should reach 20 billion euros in 2030. However, there is still a delay: only 10% of French businesses use AI actively, against 35% globally. This difference represents both a challenge and an opportunity for French companies that are rapidly adopting these technologies.
What are the sectors that dominate the AI market?
Three sectors represent the dominant share of the global AI market: health, finance, and manufacturing. These industries particularly benefit from the capabilities of AI in predictive analytics, process automation, and operations optimization. Healthcare uses AI for diagnosis and medical research, finance for fraud detection and risk analysis, and manufacturing for production optimization and predictive maintenance.
🏢 Adopting AI in business
How many businesses are using AI in 2024?
35% of global businesses are actively using AI in 2024. In France, the adoption rate remains lower with 10% of businesses, but 26% of SMEs have already taken the plunge. This disparity shows that French small and medium-sized businesses are often more agile in adopting new technologies.
What is the adoption rate in French SMEs?
26% of French SMEs and ETIs have integrated AI into their operations. Even more encouraging, nearly one out of two SMEs plans for an expanded deployment of AI in Next 24 months. This trend shows that SMEs now recognize AI as an essential driver of competitiveness, and no longer as a technology reserved for large companies.
What AI technologies are being deployed the most in business?
Here are the most adopted AI technologies:
- Generative AI - Increasing and widespread adoption for creating content, code, images
- Chatbots and predictive analytics: 42% - For customer service and forecasts
- RPA (robotic automation): 39% - To automate repetitive tasks
- NLP (natural language processing): 33% - For text analysis and communication
- Computer vision: 26% - For the analysis of images and videos
Generative AI clearly dominates, supported by tools that have democratized access to these technologies.
What sectors are adopting AI the most?
The adoption of AI varies considerably across sectors:
- Marketing: 88% - The most advanced sector, using AI for personalization and content creation
- Customer service: 72% - Automation of support and responses
- Finance and tech: Productivity multiplied by 5 - Major impact on operational efficiency
- HR in France: 28% - Increasing adoption for recruiting and talent management
Marketing dominates because AI allows personalization on a large scale, a critical need in an environment where consumer attention is increasingly difficult to capture.
How many employees are trained in AI?
66% of employees are trained in AI tools in France, and 75% of employees are already using AI in their daily work. A particularly interesting figure: 40% of employees are the drivers of the adoption of AI in their business, often ahead of their management's official initiatives. This “bottom-up” adoption shows that AI meets real operational needs.
💼 Impact on work and productivity
What productivity gains does AI bring?
AI generates spectacular productivity gains:
- +15 to 40% increase in productivity by sector
- 45% of businesses doubled their productivity with generative AI
- 90% of users believe that AI saves them time
- Productivity multiplied by 5 in finance and tech
These gains are not theoretical but measured and documented. Businesses that industrialize AI are seeing their competitiveness increase rapidly, creating a growing gap with those that are slow to adopt these technologies.
What tasks are automated by AI?
Automation via AI affects many processes:
- 47% of IT processes are automated
- 30% of repetitive tasks should be automated soon
- 95% of customer interactions will be managed by AI in 2025
This automation frees up time for higher-value tasks, allowing teams to focus on innovation, strategy, and complex human relationships that AI can't replace.
Is AI a threat to jobs?
The answer is nuanced. 75% of employees fear losing their jobs due to AI, but this fear needs to be put into perspective. AI transforms more than it destroys: jobs are evolving towards skills requiring creativity, emotional intelligence and strategic thinking. The evolution of jobs towards tasks with higher added value should contribute to +26% of GDP. Training and retraining are essential to support this transition.
Which jobs are the least threatened by AI?
Functions that require a strong emotional intelligence, creativity, or strategic abilities are the least exposed to automation. This includes: managers and leaders, creatives and artists, therapists and counsellors, business strategists, and complex negotiation professionals. These jobs require solely human skills that AI cannot replicate.
💰 ROI and financial performance
What ROI do you get with generative AI?
74% of businesses who have adopted generative AI are seeing a positive return on investment. The sectors back office and IT have the fastest ROI because automating standardized processes quickly generates measurable savings. This ROI is explained by the reduction of operational costs, the acceleration of processes and the improvement of quality.
What part of the tech budget is devoted to AI?
Businesses are now devoting up to 20% of their technology budget to artificial intelligence. In addition, 58% of businesses plan to increase their investments in AI in 2025. This growing budget allocation reflects the belief that AI has become an indispensable strategic investment, just like traditional IT infrastructures.
Why are so few businesses creating customer value with AI?
Only 7% of EMEA businesses really create customer value via AI, despite the fact that 74% observe a positive ROI. This apparent paradox can be explained: many companies generate internal gains (productivity, cost reduction) without truly transforming the customer experience. Successful businesses are those that put customer experience at the heart of their AI strategy rather than just focusing on internal optimization.
🎨 Generative AI and content creation
What is the adoption of generative AI in business?
The adoption of generative AI is growing significantly. 75% of marketers are already using generative AI in their daily work, and this trend is spreading across industries. The dominant patterns in 2026 include Gemini 3 Pro (Google), Grok 4.1 (xAI), and GPT-5.1 (OpenAI), all of which are in the top 10 best performing models.
How many weekly users does ChatGPT have?
ChatGPT reaches 900 million weekly users in 2026 a figure that illustrates the massive adoption of generative AI tools by the general public. This rapid adoption, starting from scratch in November 2022, represents one of the fastest growths in technological history. In France, between 25 and 30% of the population regularly uses ChatGPT.
How much web content is generated by AI?
In 2026, The share of web content generated by AI is growing significantly. This revolution is changing the challenges of verification, originality and quality of online content. 63% of marketers are already using AI to create content, and 75% of marketers are using generative AI in their daily work.
What is the impact on the productivity of content creators?
Editorial teams are seeing their productivity increase by +40% thanks to AI. AI is widely used to find ideas and content topics, for drafting drafts, for SEO optimization, and for translating and adapting content. However, human expertise is still essential for strategy, revision, and adding the creative touch that makes a difference.
🎯 Sectoral applications of AI
How is AI transforming human resources?
In French HR, 28% are already using AI, mainly for:
- 30% of HR Sort resumes with AI
- 25% of HR employees automate administrative tasks
AI makes it possible to better target skills, to anticipate mobility or training needs, and to considerably accelerate the recruitment process. This allows HR to focus on people: integration, talent development and corporate culture.
What benefits does AI bring to digital marketing?
AI is revolutionizing marketing with measurable results:
- 63% of marketers create content with AI
- 55% of marketers save time thanks to AI
- +50% of qualified prospects generated thanks to marketing AI
AI enables large-scale personalization, continuous campaign optimization, and a deep understanding of consumer behavior. Marketing is becoming both more effective and more efficient.
How does AI improve customer service?
72% of businesses use AI to sort customer tickets, and 95% of customer interactions will be managed by AI in 2025. This automation allows 24/7 availability, of instant answers, a personalization based on customer history, and the automatic resolution of common problems. Human agents focus on complex cases that require empathy and creativity.
What is the impact of AI in health?
La Health is a dominant part of the global AI market. Applications include AI-assisted diagnosis (especially in medical imaging), the discovery of new drugs, personalized medicine, the early detection of diseases, and the optimization of the maintenance of medical equipment. AI improves prevention and the quality of medical services through advanced predictive analyses.
How is AI transforming finance?
In finance and tech, AI Multiply productivity by 5. Predictive AI models are widely used for cash flow forecasting, fraud and anomaly detection, risk analysis, algorithmic trading, and financial reporting automation. Finance is one of the sectors where automation offers the greatest leverage on performance.
What is the impact of AI in commerce and retail?
AI allows a advanced customization And a automated flow management. Applications include personalized product recommendations, optimized inventory management, demand forecasting, dynamic pricing, and buying behavior analysis. Recommendation systems and predictive analytics simultaneously optimize customer experience and profitability.
🌐 Web Traffic and Cybersecurity
What part of web traffic is generated by AI?
In 2024, 51% of global web traffic is already generated by bots and AIs (crawlers, automated agents). This transformation has major implications for cybersecurity, authentication, and access management. Businesses need to rethink their security strategies for this new reality.
How does AI impact cybersecurity?
AI plays a double role in cybersecurity: it is both a offensive weapon (deepfakes, sophisticated automated attacks) and a crucial defense (detection of anomalies in real time, identification of unknown threats). French investments in cybersecurity (AI) are in Strong rise, and the use of AI to detect cyberattacks is now widespread.
👥 Perception and adoption by users
What is the perception of AI by the French?
The French have an ambivalent relationship with AI:
- 88% say they know AI well
- 78% use generative AI on a weekly basis
- 56% don't trust AI
- 80% consider it necessary to regulate AI
This duality reveals that while use is becoming widespread, ethical and security concerns remain strong. The expectation of regulation and ethics is a major challenge for the social acceptance of AI.
Is there a generational divide in the use of AI?
Yes, a major generational divide exists:
- 97% of 18-24 year olds know AI well
- 51% of those aged 75+ know AI well
- 19% of Gen Z uses AI “often”
This 46-point generational gap reveals the importance of pedagogy and support to ensure the inclusive adoption of AI. Businesses need to adapt their training programs across generations.
How do professionals perceive AI?
71% of professionals were thinking of using AI in 2024, and 66% feel that it allows them to focus on the tasks they prefer. Professionals see AI as a career development lever And ofimproving the quality of work, rather than as a threat. This positive perception encourages voluntary and proactive adoption.
🌍 Ethical and environmental issues
What is the environmental impact of AI?
The environmental footprint of AI is considerable and growing:
- 35 to 50% of the electricity consumption of data centers in 2030
- 1.7 gigatons of cumulative CO₂ emissions (2025-2030)
- 1 200 billion liters of water consumed per year
- 21% of the digital ecological footprint in 2030
These figures require urgent consideration of energy sobriety and frugal AI. Businesses need to assess environmental impact at each stage of the AI lifecycle.
What are the ethical concerns around AI?
60% of employees are concerned about data privacy. Other major ethical issues include algorithmic biases, the transparency of automated decisions, and diversity in AI research (only 11% of women in AI research). The establishment of ethical governance is becoming essential to maintain trust.
Why is diversity a critical issue in AI?
Only 11% of AI researchers are women, revealing a serious problem of diversity and equity. This under-representation can lead to biases in algorithms, as homogeneous teams unconsciously replicate their own perspectives. An AI that is truly at the service of all requires the diversity of creators: gender, origin, culture, background.
🚧 Adoption challenges and barriers
What are the main challenges to adopting AI?
There are three major obstacles to the adoption of AI:
- Lack of internal skills - The No. 1 obstacle identified by businesses
- Difficulty measuring profitability - Only 7% of EMEA businesses create customer value
- Regulatory constraints - Perceived as a barrier but becoming a competitive advantage
Success requires a structured approach: training, clear governance, and rigorous ROI measurement.
How do you overcome the lack of AI skills?
To make up for the skills gap, businesses need to:
- Deploy continuing education programs for all employees
- Recruiting hybrid profiles combining business expertise and AI skills
- Create partnerships with universities and research centers
- Use “no-code” or “low-code” AI tools to democratize access
- Encouraging learning by doing with pilot projects
Investing in skills is as important as investing in technology itself.
Are European regulations a hindrance or an asset?
Although initially perceived as a barrier, European regulatory constraints Become a competitive advantage. They force businesses to adopt best practices in ethics, transparency, and data protection. This rigor is becoming a selling point for customers who are sensitive to these issues, particularly in B2B and in regulated sectors.
🔮 Perspectives and trends
What major transformations are expected?
Structuring trends include:
- 95% of customer interactions managed by AI
- Web content: significant growth Of the part generated by AI
- 10% of the car fleet The world will be autonomous by 2030
- 58% of businesses plan to increase their AI investments in 2025
AI will no longer be a specific technology but an invisible and omnipresent component of all our digital and physical interactions.
How will AI transform education and training?
Education will experience a revolution with the personalization of learning paths, real-time support for students, the automation of correction and feedback, and the adaptation of content to the pace of each learner. Multimodal AI will enable immersive learning experiences combining text, audio, video, and interactivity. The role of the teacher will evolve towards mentoring and personalized support.
💡 Questions for decision-makers and strategists
Where do you start with AI in business?
Here is the recommended road map:
- Forming teams to the fundamentals of AI and the tools available
- Identify use cases with a high potential ROI (customer service, marketing, back office)
- Structuring AI governance clear with defined roles and responsibilities
- Deploy pilot projects measurable over 3-6 months
- Evaluate and adjust continuously, then industrialize the successes
The “test and learn” approach with short projects makes it possible to minimize risks while learning quickly.
What KPIs should you follow to measure the success of AI?
Key performance indicators include:
- Productivity gains: Time saved, automated processes, volume processed
- Financial ROI: Reduced costs, increased turnover
- Customer satisfaction: NPS, first contact resolution rate, response time
- Internal adoption: Percentage of active users, frequency of use
- Environmental impact: Energy consumption, carbon footprint
Rigorous measurement is essential to justify investments and guide efforts.
How can responsible and ethical AI be guaranteed?
A responsible AI approach requires:
- Transparency: Explain how AI makes decisions
- Fairness: Regularly audit algorithmic biases
- Confidentiality: Rigorously protect personal data
- Governance: Define clear rules for using AI
- Durability: Measuring and reducing the environmental footprint
Ethics is not a barrier but a factor of differentiation and trust.
What strategy to remain competitive in the face of AI?
To maintain its competitiveness, a company must:
- Continuously invest in training and skills development
- Adopt a culture of experimentation and rapid learning
- Develop strategic partnerships with the AI ecosystem
- Put the customer at the center of your AI strategy (not the technology)
- Rigorously measure ROI and adjust quickly
The winners won't be those with the best technology, but those who best integrate it into their value proposition.
How to prepare your teams to work with AI?
Team preparation involves:
- Technical training: Understand the capabilities and limitations of AI
- Development of soft skills: Creativity, critical thinking, emotional intelligence
- Culture of change: Present AI as an assistant, not a replacement
- Supervised experimentation: Encourage the use of AI with safeguards
- Sharing best practices: Create internal user communities
The success of AI depends as much on corporate culture as it does on technology.
🎯 2026 Action Plan
What to remember from the IA 2026 statistics?
The 2025-2026 data confirms the exponential rise of artificial intelligence in the global economy. AI is no longer an emerging technology but a An essential performance driver. Businesses that adopt it strategically are seeing measurable gains : productivity (+40%), positive ROI (74%), and business transformation. However, only 7% actually create customer value, underlining the importance of a structured and customer-centric approach.
What are the 5 priority actions for 2026?
- Continuing education: Deploy an AI training plan for all employees, adapted to jobs and levels
- AI governance: Structuring dedicated governance to manage innovation and ensure compliance and ethics
- Targeted automation: Identify and automate processes with low added value (back office, customer service, content) as a priority to maximize ROI
- Data strategy: Develop a robust data management and valuation strategy to feed AI algorithms
- Responsible AI: Adopt an ecodesign and frugal AI approach to limit the environmental footprint and assess the impact at each stage
Is AI really accessible to SMEs?
Absolutely. 26% of French SMEs and ETIs have already adopted AI, proving that this technology is no longer reserved for big businesses. “No-code” and “low-code” tools democratize access, SaaS solutions avoid heavy infrastructure investments, and productivity gains can be measured quickly even on a small scale. SMEs can start with targeted projects (customer chatbot, marketing automation) before gradually expanding.
Sources:
https://www.hostinger.com/fr/tutoriels/statistiques-ia
https://tool-advisor.fr/blog/statistiques-intelligence-artificielle-ia/
https://vlad-cerisier.fr/statistiques-intelligence-artificielle-ia/
https://www.focus-ai.fr/blog/ia-en-entreprise-les-statistiques-cl%C3%A9s-et-tendances-pour-2026-(productivit%C3%A9-adoption-roi)
https://independant.io/statistiques-ia-intelligence-artificielle/
https://www.blogdumoderateur.com/top-20-modeles-ia-performants-janvier-2026
https://www.itpro.fr/tendances-2026-lia-devra-prouver-sa-rentabilite
https://bigmedia.bpifrance.fr/nos-dossiers/nouvelles-tendances-ia-ce-qui-va-transformer-2026
https://www.stat4decision.com/fr/2026-annee-formation/
https://independant.io/tendances-marketing-digital/
Concrete example
.jpg)
.svg)
.svg)
.jpeg)
.jpg)
%20-%20blue.jpeg)
.avif)