- The report reveals that the adoption of AI is explosive, but most companies jump for the hard work of preparation
- Management teams fail to align themselves with AI priorities, leaving fractured and confused strategies
- AI is as good as data behind it, and most data strategies are lacking
The thrust of the adoption of artificial intelligence has triggered comparisons with the cloud of the last decade, but although use increases quickly, understanding remains superficial, said new research.
A Hostinger report has revealed that almost 80% of companies now use or plan to use AI, but a separate Adecco group report says that only 10% of leaders in the C Suite C think that their organizations are fully ready for the disruption that AI provides.
Among the 359 million companies estimated worldwide, around 280 million AI integration into at least one function.
The adoption of AI accelerates, but the strategy and the structure are lagging behind behind
An increasing number of small businesses turn to the best AI tools to manage tasks such as e-mail writing, data analysis or content generation.
Large companies can constitute complete teams for implementation, but small businesses discreetly transform operations by using lean approaches, sometimes improvised.
However, preparation does not follow adoption, and there is a disturbing gap in the strategy, because if 60% of managers expect workers updating their skills, 34% of companies have no official AI policy.
Adecco noted that more than half of CEOs admit that their teams have trouble aligning themselves with priorities, and only a third of companies invest in a data infrastructure that would help fill these shortcomings.
However, a small group of “ready for future” companies builds more reactive strategies by supporting continuous learning and based on business levels to shape their IA management.
The CEO of Adecco, Denis Machuel, says it clearly: “The transformation led by AI must be centered on man”.
Many companies rush into the adoption of AI without understanding what differentiates them, resulting in dispersed or redundant projects.
“Without an overview of the company’s scale, AI efforts become partitioned and poorly aligned. Corporate architecture can help concentrate AI initiatives on what really distinguishes a business, ”explains Stender.
By mapping their unique forces and workflows, organizations can guide AI deployments that strengthen strategic priorities rather than dilute them.
AI depends not only on investment, but on introspection, and it is not a magic solution – and if companies do not understand what they need, they will not know how to use it, and the result will be catastrophic.
