AI proves its value, but its generalization requires a lasting strategy, targeted choices and a solid infrastructure to transform use cases into large -scale levers.
Many promising ideas emerge to deploy AI, but they still have to be technically and operationally achievable. User cases are multiplying, go into production and prove their effectiveness. If the challenges remain, the question is no longer whether AI creates value, but how to build a strategy that amplifies it.
A recent report, The Radical King of Gen Ai, led to 3,000 companies in nine countries, confirms that efforts in terms of AI are bearing fruit. Among the 1,900 respondents actively using AI, 92 % find a return on investment (king). Those who measure it observe an average gain of 41 %, or 1.41 dollars generated for each dollar invested. However, this king remains limited to part of the potential of AI. Companies therefore intensify their investments to identify more ambitious and high added use cases.
The AI makes the teams faster, effective and profitable. But this success brings its share of new challenges. Businesses must now capitalize on this dynamic. It becomes essential to demonstrate the value generated, and managers must make difficult choices in the prioritization of efforts.
The report reveals that 71 % of the first adopters have more use cases that they cannot finance it, 54 % find it difficult to decide, and 59 % believe that betting on bad use cases could cost them their position. The issues are therefore considerable. But choosing a good use case is not enough: IA projects are complex and involve arbitrations on costs, human resources, technical constraints, etc. An idea must become feasible and sustainable.
On the budget side, 96 % of companies declare that they have encountered at least a cost surpassing. The main positions concerned are: calculation costs (64 %), support software (61 %), and data management (collection, labeling, processing with 58 %). Despite these additional costs, the majority obtained a positive king. The challenge now is to make this success predictable, reproducible and evolving, while reducing budgetary unforeseen events.
Lay the foundations for a corporate AI
AI pioneers have had initial successes. They now seek to perpetuate and generalize them. As projects go into production, the tools must naturally integrate into existing work environments, where users are already evolving.
The approach involves abandoning the evidence of isolated concept in favor of a global strategy, based on data aligned with real uses. This calls unified platforms, capable of supporting all IA initiatives and providing the tools as close as possible to data.
The study also confirms this orientation: 81 % of the first adopters increase their investments in cloud data platforms, with a planned average increase by 24 % by 2026. Three priorities stand out: first, security (criticism or important for 84 %), second, advanced IA features (84 %) and finally,
integrated analytical capacities (84 %).
These priorities reflect a clear vision of the foundations necessary for an effective AI deployment including a unified, without silos, ruled, secure and interrogable database, to provide reliable responses from structured data or not. Then, a methodical implementation, starting with low -risk cases, in order to build robust systems and solid indicators. And finally, an adaptable architecture, capable of evolving quickly while maintaining the standards of security and governance.
These foundations facilitate compliance, management of sensitive data, orchestration of workflows, and prepare the ground for large -scale, confidence.
Towards a perennial leadership
Companies that have already started their IA transformation show strong confidence. They are now interested in the next wave: IA agents.
Although recent, these agents are already aroused the interest of managers, who identify use cases with high potential. Thanks to their extended memory, their advanced reasoning capacities and their ability to act in a targeted manner, they represent a major transformation lever for this year.
The revolution is only just beginning. The tools gain in flexibility, intelligence and autonomy, while costs decrease. The opportunities to transform working and life modes are immense.
But the real leaders will be those who, today, adopt a long -term vision, invest in an infrastructure adapted to data and models, and integrate AI as a structuring pillar of their strategy, and not as a simple experiment.
