- Report finds business AI adoption is exploding, but most companies are skipping the hard work of preparation
- Leadership teams are failing to align on AI priorities, leaving strategies fractured and confused
- AI is only as good as the data behind it, and most data strategies are missing
The surge in artificial intelligence adoption has sparked comparisons to the cloud boom of the past decade, but while usage is growing rapidly, understanding remains shallow, new research has claimed.
A Hostinger report found almost 80% of companies now use or plan to use AI, but a seperate Adecco Group report claims only 10% of C-suite leaders believe their organizations are fully ready for the disruption AI brings.
Among the estimated 359 million companies worldwide, about 280 million now integrate AI into at least one function.
AI adoption accelerates, but strategy and structure lag behind
A growing number of small businesses are turning to the best AI tools to handle tasks like writing emails, analyzing data, or generating content.
Larger companies may build out full teams for implementation, but smaller firms are quietly transforming operations using lean, sometimes improvised, approaches.
Still, readiness doesn’t follow adoption, and there is a worrying gap in strategy, as although 60% of leaders expect workers to update their skills, 34% of companies have no formal AI policy.
Adecco found over half of CEOs admit their teams struggle to align on priorities, and only a third of businesses are investing in data infrastructure that would help close these gaps.
However, a small group of “future-ready” companies is building more responsive strategies by supporting continuous learning and relying on enterprise-wide insight to shape their AI direction.
Adecco’s CEO, Denis Machuel, puts it plainly: “AI-driven transformation must be human-centric.”
Many companies rush into AI adoption without understanding what differentiates them, resulting in scattered or redundant projects.
“Without enterprise-wide insight, AI efforts become siloed and misaligned. Enterprise Architecture can help focus AI initiatives on what truly sets a company apart,” Stendera explains.
By mapping their unique strengths and workflows, organizations can guide AI deployments that reinforce strategic priorities rather than dilute them.
AI depends not just on investment, but on introspection, and it is not a magic fix – and if companies do not understand what they need from AI, they won’t know how to use it, and the result will be catastrophic.
