- The report finds that the adoption of business AI is exploiting, but most companies are omitting the hard preparation work
- Leadership teams are not aligned in AI priorities, leaving fractured and confused strategies
- The AI is as good as the data behind it, and most data strategies are missing
The increase in the adoption of artificial intelligence has caused comparisons with the rise of the cloud of the last decade, but while the use is growing rapidly, understanding remains superficial, has affirmed new research.
A Hostinger report found that almost 80% of companies now use or plan to use AI, but a separate report from the Adecco group states that only 10% of C-Suite leaders believe that their organizations are completely ready for the interruption of AI.
Among the 359 million estimated companies worldwide, around 280 million now integrate AI in at least one function.
The adoption of the accelerates, but the strategy and structure are left behind
A growing number of small businesses is using the best AI tools to handle tasks such as writing emails, analyzing data or generating content.
The larger companies can build complete equipment for implementation, but smaller companies are transforming operations in silence using Lean approaches, sometimes improvised.
Even so, the preparation does not follow adoption, and there is a worrying gap in the strategy, since although 60% of leaders expect workers to update their skills, 34% of companies do not have a formal policy of AI.
Adecco found that more than half of the CEOs admit that their teams fight to align in priorities, and only one third of the companies are investing in data infrastructure that would help close these gaps.
However, a small group of companies “lists for the future” is building more receptive strategies in supporting continuous learning and depending on the vision of the entire company to shape its direction of AI.
Adecco’s CEO, Denis Machuel, expresses it clearly: “The transformation driven by AI must be focused on human.”
Many companies rush the adoption of AI without understanding what differentiates them, resulting in scattered or redundant projects.
“Without a vision of the entire company, Ia’s efforts are rising again and misaligned. Business architecture can help focus AI initiatives on what really distinguishes a company,” Stendra explains.
By mapping their unique strengths and workflows, organizations can guide AI implementations that reinforce strategic priorities instead of diluting them.
AI depends not only on investment, but on introspection, and it is not a magical solution, and if companies do not understand what they need AI, they will not know how to use it, and the result will be catastrophic.
