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In an ever-changing economic world, the training of students in finance and management is facing a major challenge: meeting the needs of a constantly changing labour market, particularly under the impetus of technological advances and artificial intelligence (AI). This mismatch between the skills acquired during studies and those sought by employers raises crucial questions about the effectiveness of current training curricula and the preparation of future professionals for the realities of the field.
The root causes of discordance
Gaps in academic programs
Academic programmes in finance and management are often criticized for their lack of alignment with the real needs of the market. A study found that the skills taught do not always correspond to employers' expectations, particularly with regard to digital tools and modern methodologies. This disconnection can be attributed to institutional inertia and slow integration of educational innovations.
Difference between theory and practice
Another major obstacle is the predominance of theoretical education at the expense of practice. Students are often trained in abstract concepts without concrete application, which limits their ability to adapt quickly to professional requirements. This approach can lead to frustration among both graduates and recruiters, who see a lack of preparation for the realities of the field.
Impact of new technologies on the skills required
The emergence of disruptive technologies, such as AI, big data and blockchain, is radically transforming the financial and management professions. Technical skills, such as mastering data analysis tools and understanding algorithms, are becoming essential. However, these skills are still insufficiently integrated into traditional curricula, creating a gap between academic training and market expectations.
The impact of artificial intelligence on the financial professions
Automation of repetitive tasks
The AI has the ability to handle repetitive and time-consuming tasks such as data entry, reporting generation or preliminary risk analysis. This automation allows professionals to focus on activities with higher added value, but it also requires an adaptation of skills to supervise and interpret the results produced by the machines.
Redefinition of professional roles
With the integration of AI, traditional roles evolve. For example, financial analysts now need to have programming and data science skills to effectively exploit AI tools. This transformation of occupations requires a review of the profiles sought by enterprises and, consequently, of the training provided in higher education establishments.
Risk of job losses
Increasing automation raises the question of the sustainability of certain positions, particularly those focused on routine tasks. Some estimates suggest that a significant proportion of entry-level jobs in finance could be threatened by AI. This perspective highlights the urgent need to rethink training to prepare students for more strategic and less automated functions.
Reform proposals to align training with market needs
Integration of digital and technological skills
It is imperative to incorporate modules dedicated to new technologies into finance and management programmes. This includes learning programming languages, mastering data analysis tools, and an in-depth understanding of the AI systems. Such integration would allow students to develop technical skills in line with current market requirements.
Strengthening partnerships between training centres and enterprises
Fostering collaboration between academia and the private sector can help reduce the gap between training and employment. Internships, in-company projects and professional interventions in the curriculum allow students to become familiar with the realities of the field and acquire directly applicable practical skills.
Implementation of continuing and adaptive training
In a context of rapid change, training can no longer be limited to the academic period. It is essential to promote continuing training programmes that enable professionals to update their skills regularly. Such training should be flexible, accessible and focused on technological developments and emerging market needs.
Development of cross-cutting competences
In addition to technical skills, soft skills such as critical thinking, creativity, communication and adaptability are increasingly valued. Educational programmes must therefore incorporate modules designed to develop these skills, which are essential for navigating in a complex and constantly changing professional environment.
Some skills often required by companies
| Areas | Expected competencies |
| Financial accounting increased | Master accounting bases with automated tools (ERP, OCR) |
| Artificial intelligence | Mastering key concepts: machine learning, deep learning, NLP |
| Python for finance | Programming in Python: financial calculations, pandas, numpy |
| Agile project management | Mastery of Scrum methodology, hybrid management and digital tools (Jira, Trello) |
| Soft skills : communication & leadership | Being comfortable with expression techniques, active listening, emotional intelligence |
| Financial analysis with IA | Know how to use predictive models for performance analysis |
| Data visualisation & storytelling | Know how to design dashboards with Power BI, Dash, data narrative |
| Introduction to Automation (RPA) | Know how to automate repetitive tasks via Power Automation |
| Ethics and governance of AI | Mastering algorithmic biases, automated decisions and regulation |
| Fintech and financial innovation | Mastering dematerialised payments, blockchain, decentralised finance |
| Advanced Learning Machine for Finance | Mastering the forecasts for scoring, fraud detection |
| Economic Intelligence & IA Strategy | Strategic watch, decision automation, IA generative |
| Negotiation & Influence | Advanced Persuasion Techniques, AI in HR |
The mismatch between finance and management training and labour market needs is a major challenge in the AI era and technological transformations. To respond to this, a recast of academic curricula is needed, incorporating technical skills, practical experience and a development of soft skills. Only a holistic and proactive approach will effectively prepare students for the demands of a constantly changing labour market.
