Generative AI: An Ally for Business Productivity

The challenge for 2025 is no longer whether generative AI will transform professions, but how companies will successfully integrate it in a responsible and strategic way, without losing their culture or agility.’

In communication and marketing, generative AI enables the rapid production of text tailored to different audiences. Tools like Jasper or Copy.ai can draft newsletters, social media posts, or product descriptions in minutes, while adjusting style and tone according to the target audience.¹

‘AI does not replace human creativity; it catalyzes it. Companies that use it as a creative co-pilot will get the most out of these tools.’

Generative conversational assistants also enhance customer support by providing consistent answers to common questions, while supplying scripts and recommendations to human agents to improve the overall experience.²

In software development, generative AI is revolutionizing code production. Solutions like GitHub Copilot assist developers by suggesting complete functions or automatically correcting certain errors³, while companies like Atlassian use it to generate unit tests or deployment pipelines⁴.

These tools reduce human errors and accelerate project delivery while maintaining code quality.

Generative AI also opens new possibilities in design and creativity. Platforms such as Canva or Figma use generative models to quickly produce images, logos, and layouts, allowing marketing teams to test multiple concepts in record time.⁵

In the video game and immersive experience industry, AI facilitates the creation of textures, environments, and scenarios, enabling rapid, cost-effective prototype generation.⁶

Although generative AI is a powerful tool, it is not suitable for every use case. Misapplication can lead to suboptimal results and diminish AI’s value for a business. Before implementing GenAI, it is essential to assess the project’s value and feasibility. This involves evaluating whether generative AI is truly appropriate for the task: it excels at content generation, conversational interfaces, and knowledge discovery but is less effective for prediction, forecasting, or decision-making.

It is also important to consider alternatives. In some cases, other AI techniques—such as non-generative machine learning or optimization methods—may provide more reliable, cost-effective, and simpler-to-implement results.

Finally, combining different AI techniques can improve performance and accuracy while reducing data requirements and associated costs.

Emmanuel Vivier emphasizes the importance of experimenting thoughtfully: “It is not enough to adopt ChatGPT or Midjourney; companies must rethink how they train, evaluate, and govern innovation.”

Generative AI is therefore a major lever for increasing productivity and driving innovation. However, its effectiveness depends on careful implementation that balances automation with human oversight. By selecting the right use cases and intelligently combining AI techniques, companies can transform workflows, enhance output quality, and innovate faster while maintaining reliability and relevance.

To learn more about GenAI from Emmanuel Vivier: https://youtu.be/sFRutgq1HUo

Proximus NXT supports organizations in deploying AI, regardless of their maturity level—covering strategic vision through adoption. Boost your productivity and discover how to integrate AI securely and compliantly to meet your company’s specific needs.

Contact our experts to guide you at every step with secure, sector-adapted solutions: https://www.proximusnxt.lu/fr/faconnez-lavenir-de-votre-entreprise-avec-lintelligence-artificielle  

References

1.    Jasper AI, https://www.jasper.ai/ 
2.    Copy.ai, https://www.copy.ai/ 
3.    GitHub Copilot, https://github.com/features/copilot 
4.    Atlassian, utilisation de l’IA pour tests et pipelines, https://www.atlassian.com/ 
5.    Canva, Figma et design génératif, https://www.canva.com/ , https://www.figma.com/ 
6.    Applications IA générative dans le jeu et l’UX, https://venturebeat.com/ai-in-gaming 
7.    Gartner, Leinar Ramos, “When NOT to use Generative AI”, https://www.gartner.com/