From proof of concept to execution: discover how to methodically integrate generative AI. Strategy, profitability, and a white paper to ensure your transformation is a success.
Artificial intelligence is no longer a subject of exploration, but of implementation. When properly harnessed, it allows organizations to be more efficient, responsive, and profitable. However, the impact on jobs and people's employability could be massive, particularly with the increasing accessibility of generative AI.
In the corporate world, when it comes to generative AI, technological fascination often overrides reason. It's true that AI (and even more so generative AI) is a key factor in competitiveness. Failing to use it means risking being overtaken by the competition. In this context, AI has become a top management issue: it must be implemented at all costs… even if it means relegating the why and how to the back burner.
This situation leads to numerous failures. According to IDC, 80% of Proofs of Concept (POCs) are not deployed due to poor profitability or difficulties related to governance, data, or inadequate infrastructure. It is essential to abandon wishful thinking and remember that AI is just one tool among many, not a panacea.
Beyond the fad, there are very real benefits…
All of this should not obscure the fact that 20% of POCs lead to the deployment of an AI solution. This rate is expected to increase as organizations gain maturity in this area.
The emerging future is one of companies where a maximum number of intellectual tasks are accelerated, orchestrated, and even automated by intelligent agents, with the ultimate goal of implementing fully autonomous processes. These organizations will be more responsive, more efficient, and also more profitable, since they will be able to reduce their payroll. Will some support functions see their scope diminish?
With the release of new AI models, the possibilities are expanding even further. The latest version of Claude (Anthropic), for example, offers legal advice. Generative AI is a technology where innovations are emerging at a rapid pace, to the point that the scope of what is possible—in the long term—now seems limitless.
…but also major social risks.
Beyond the very real advantages offered by artificial intelligence, one question remains: the impact of this technology on society and on workers. For younger generations, the question will arise as to which career path to pursue: is it still worthwhile to learn to code or to draw? Furthermore, it seems clear that if AI boosts the productivity of a company's employees, this will inevitably reduce the number of new hires. Certainly, new AI-related positions will emerge, but they may not compensate for the jobs eliminated or not created.
For employees, AI doesn't spell the end of expertise, but rather its transformation. An AI-enhanced employee can produce more, faster. Value then no longer rests solely on execution, but on the ability to frame, arbitrate, interpret, and decide. The challenge, therefore, is not to replace skilled professionals, but to redefine what sets them apart.
Furthermore, the promise of automating repetitive tasks can free up time - provided that work is organized to avoid a simple intensification of pace.
Generative AI, an inevitable revolution.
Organizations that are slow to adapt will face a significant gap that is difficult to close. The question is no longer whether AI will become widespread, but how to integrate it methodically into a competitive environment where every productivity gain counts. With this in mind, SMILE is publishing the white paper “ "Upside AI, 10 tips to survive your AI transformation " , to help companies structure their projects and avoid classic pitfalls.
The rapid adoption of generative AI also necessitates a swift adaptation of skills. This presents an opportunity to rethink career paths and accelerate learning, because the goal is not the disappearance of work… but rather its transformation.
