Today, retraining is an essential part of the career paths of executives and managers, who are faced with accelerating economic, technological and societal change. In 2025, the context is radically different from that of the past decade: the rise of artificial intelligence, the ecological transition and the ongoing transformation of organisations are redefining the contours of the professions and the skills expected.
In this article, I propose an analysis of the challenges specific to 2025, by comparing the dynamics of professional retraining and future developments. So that you can plan your project without ignoring the structural changes in the world of work.
Contents
2015 - 2025: the changing dynamics of career transition
Retraining in 2025 is nothing like a transition in 2015. Ten years ago, career paths were more likely to be linear, and reconversions involved longer training periods and gradual repositioning.
In 2015, the importance of stability and vertical mobility
At the time, a typical career for executives and managers was based on principles that still exist, but are less dominant today:
- A sequential career model: study → stable employment → internal progression → career in the same sector.
- A majority of managers favoured loyalty to the company to secure their career progression. Success was measured by climbing the hierarchy rather than diversifying skills or sectors.
- Executives who changed jobs on average every 4.7 years (DARES, 2015).
Changing career had a high opportunity cost, as it meant 'erasing' part of one's career history. So it was seen more as taking a big risk, rarely as a deliberate career development strategy.
Longer and more cautious career changes in 2015
This was an era of thwarted aspirations. 33 % of employees wanted to change jobs, but only 9.5 % actually succeeded (CEREQ, 2015).
At the time, people overestimated the stability of the sector and the lifespan of acquired skills, and underestimated the dynamics of rapid obsolescence. It was thought that retraining would be sufficient for 10 to 20 years. In reality, skills were already beginning to wear out more quickly under the discrete effect of the first waves of digitalisation (automation, cloud, big data). Another illusion was that many people were betting on "safe haven sectors" (banking, real estate, insurance), which were themselves very quickly disrupted by digital technology and the new entrants in fintech.
Back then, the process of retraining was just as challenging as it is today, but also more difficult:
- Resuming traditional studies after initial training: MBAs, specialised masters, long professional qualifications over 12 to 24 months for the majority of executives undergoing retraining
- Piecemeal funding: use of Individual Training Leave (CIF) and personal funding.
- Targeting a similar job level in a related sector or function, with few radical breaks. According to an OpinionWay survey for Afpa (2015), 78 % of working people undergoing retraining wanted to "stay close to their previous professional experience". To give you a few typical examples of the time: an engineer became a project manager after a master's degree in management, or a marketing manager switched to digital after an MBA in digital marketing.
- And all this without any support, because coaching was rare and public services more limited.
Strong institutional validation (a diploma recognised by employers), vertical specialisation (deepening your expertise), and networking (mobilising your historical internal or sectoral network) were crucial then and remain important today, but other levers have gradually been added to make your career change project a success.
Today, a combination of mobility and learning
The rate of retraining of working people has risen to 30% in 2025 (compared with 9.5 % in 2015), with 75 % of French people trained via the CPF or hybrid courses. The non-linear career model is expanding, with a combination of mobility, continuous learning and adaptability. In line with the notion of "boundaryless career" developed by Arthur & Rousseau (1996), you no longer define your current situation by the organisation to which you belong, but by your ability to navigate from one career project to another.
However, even today, certain aspects of the executive retraining as well as the psychological impact of the pace of adaptation that is now necessary. Spending all your time "learning to learn" is mentally exhausting. Learning burn-out ("learning fatigue") is a phenomenon that is beginning to be documented.
Retraining in 2025 - 2030: the challenge of anticipation
Immediately after the pandemic, many companies made defensive adjustments to their existing teams. Today, faced with far-reaching changes, Human Resources now places a premium on adaptability, the ability to learn quickly and the ability to manage change. Professional longevity depends less and less on acquired expertise, and more and more on the ability to integrate new skills on an ongoing basis.
As far as retraining is concerned, between 2015 and 2025 we saw a shift from individual retraining, which was probably more risky, to a better-financed and better-supported process. Today, retraining means embarking on a structured, financed process, supported by coaches and public schemes (CPF, France Travail, etc.). It also means easier access to short, hybrid, immersive vocational training courses, often online. And it's the chance to test out a promising sector, iterate, pivot: towards great prospects, yes, but you "build your parachute" along the way.
Winning career transition strategies in 2025
Retraining today involves not only changing jobs, but also continuously developing adaptive skills, which increases the psychological and financial pressure on future retrainees. The key success factors for retraining are based more on your ability to learn quickly (learning agility), your personal visibility online ("personal branding" on LinkedIn, "thought leadership") and the development of hybrid skills (techno + human).
This is due to structural differences compared to 2015, including various technological levers. On the one hand, personalised artificial intelligence analyses transferable skills, suggests emerging professions and effectively optimises CVs.
On the other hand, professional development is often achieved through micro-certifications, bootcamps, or intensive 3 to 6 month certification courses, rather than long diplomas, particularly in high-volume or fast-growing fields (data, ESG, cybersecurity, green tech, AI ethics, health tech, etc.). In 2025, many managers embarking on a rapid retraining programme will be opting for short, modular professional courses. A typical example is a marketing product manager who becomes an "AI Product Owner" after a good short course in machine learning. This is why platforms such as LinkedIn are seeing their use grow considerably every year. Changing jobs in 2025 means moving from a world of diplomas to a world of evidence.
Today, 60% of working people in career transition choose a coach or adviser to maximise their chances of success, compared with 15 % in 2015. This stage requires :
- Acquire cross-disciplinary skills (data culture, management of AI tools, management of technological change);
- Adopt a professional attitude that draws on the interaction between human and machine;
- Capitalise on skills that are more difficult to automate: interpersonal skills, leadership, complex judgement, managerial innovation.
- Dare to be cross-disciplinary: combine several professions, mix salaried employment and entrepreneurship, explore unexpected sectors.
- Develop a strong professional brand: clearly position our value proposition with decision-makers.
Accelerated democratisation of professional retraining
In the coming years, we can expect to see a growing emphasis on the hybridisation of technical and 'soft' skills, micro-certifications thanks to AI, and much more agile career paths combining salaried employment and entrepreneurship with hybrid models (freelance, freelance administration, skills cooperatives).
And we can imagine a move towards a more proactive model, where AI better anticipates market needs, encouraging public policies to make retraining a continuous and integrated part of the career path. Retraining will then be less and less a one-off act, and more and more a continuous process of adaptation. Everyone will have to nurture their own employability in real time. Moreover, will we continue to talk about retraining as a "one-off"? career plan a break with a before and after? Will it become a career management skill?
In conclusion
By 2025, career change will no longer be confined to individual repositioning: it will increasingly be part of a systemic dynamic, driven by technological innovation, changing market needs and the emergence of new support systems. It requires thinking in terms of adaptability, hybrid skills and carefully considered mobility in the face of ever shorter innovation cycles. While strategies based on accumulating diplomas or developing sector-specific expertise still work, the coming years will require us to take on board the speed of technological change brought about by artificial intelligence. So the challenge is no longer simply to acquire new skills in promising fields, but to develop your professional 'value proposition'.
A successful career transition in the face of the rise of artificial intelligence
AI is already a challenge for every career transition today, with predictive analysis of job requirements, optimised CVs and algorithmically personalised certification training courses, Applicant Tracking Systems (ATS), etc. I won't go into the ethical risks here (algorithmic bias in career guidance, increased surveillance via AI in recruitment processes). I won't go into the ethical risks here (algorithmic bias in career guidance, increased surveillance via AI in recruitment processes, etc.), but will concentrate on what could be of practical help to you.
Destruction of intermediate professions
According to a McKinsey report (2023), 30 % of professional tasks could be automated by 2030 thanks to generative AI such as ChatGPT, Midjourney, etc. Functions such as simple analysis, administrative management and reporting are the most likely to disappear, making it more difficult to retrain traditional middle-management profiles.
The problem is that this "creative destruction" (Schumpeter) is neither synchronous nor symmetrical: emerging jobs often require different qualifications. This is leading to a polarisation of the labour market: AI is widening the gap between highly-skilled jobs (e.g. AI engineers, energy transition researchers) and low-paid jobs (particularly in logistics, customer service or personal services), threatening the middle classes (see the theory of "Skill-biased Technological Change"). Poorly anticipated reconversions risk trapping more and more workers undergoing reconversion in "grey zones" that are neither stable nor evolving.
Rapid obsolescence of skills and the need for hybrid skills
At the same time, the average lifecycle of a skill has shortened considerably. The report Future of Jobs 2025 of the World Economic Forum indicates that 59 % of employees require retraining or upgrading to remain competitive and 77 % of employers invest in "retraining" programmes. reskilling "focused on AI.
These days, it's no longer enough to have 'deep' expertise; you also need to develop the technological and human versatility to navigate between different disciplines, in line with the T-Skill approach. In fact, the most sought-after skills today combine technological know-how (AI, data literacy) and human skills (critical thinking, leadership, creativity, interpersonal skills). For example: knowing how to write complex prompts AND managing an international team). The barrier to entry for successful retraining could therefore be higher and higher.
Understanding the new AI filters to improve job applications after retraining in 2025
The majority of large French companies - and a growing number of SMEs - use ATS (Applicant Tracking Systems) and AI-powered pre-selection tools to filter applications for available positions. This radically changes the strategies you need to adopt to successfully reposition yourself, because AI software analyses CVs and covering letters, looking for precise matches between your profile and keywords defined by the job offer. Proving your credibility in a new job without direct experience and passing through the artificial intelligence filters that traditionally favour 'already compliant' profiles - that's a tall order!
This is because automatic pre-selection tools (ATS, AI matching) are trained to detect precise job matches between your past and the vacancy in question: the system values continuity, not rupture. Here are a few ideas to help you:
- Think in terms of demonstrable cross-disciplinary skills.
AI scans your CV for technical and behavioural skills. When retraining, it is therefore crucial to spell out the skills that are directly transferable to the new job (e.g. project management, data analysis, team leadership), and that can be validated by recent professional training or pilot projects (certifications, bootcamps, personal projects).
If you were a marketing manager and you become an IT project manager, your CV could include notions of "agile project management", "leading multi-disciplinary teams" or "change management", even without any technical 100 % experience.
- Build a "hybrid" CV: past experience + career projection
Your CV should not simply tell the story of the past: it should demonstrate your alignment with the expectations of the new job. This means restructuring your experience around skill blocks rather than hierarchical titles, and highlighting elements that resonate with the target vacancy, even if they were secondary in your previous position.
- Make strategic use of qualifications and short courses
For AI, a skill exists if it is formalised. Recognised certifications are legible beacons for the algorithms and instantly lend credibility to a retraining profile. Ideally, each key skill in the new profession should be covered by a short training course leading to certification, or an achievement translated into tangible results.
- Anticipate an automated negative bias and broaden your strategy
Many AI tools still have an unconscious bias towards classic profiles (job continuity). Even if you are well prepared, a retraining profile may be less favoured in the first automatic sort. So activate your network to get round the ATS (recommended applications), give preference to recruiters who value the diversity of career paths and build up a strong LinkedIn presence, where AI pre-selection is more "open" to retraining (thanks to published content, interactions, etc.).
Successful career transition in the face of AI is not just a matter of "improving your CV" by adding more and more mastered IT tools. It means reformulating one's identity and professional situation in the language of AI, proving one's worth on bases that can be read by the algorithms, and intelligently anticipating resistance from the system.
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