AI spreads faster than cloud tech, but most companies don’t know what they are doing with it
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- Report thinks the company AI acceptance explodes, but most companies skip the hard work of the preparation
- Leadership teams fail to coordinate AI priorities, so that strategies are broken and confused are left behind
- AI is only as good as the data behind it, and most data strategies are missing
The increase in the adoption of artificial intelligence has fueled the comparisons of the cloud tree of the past decade, but although the use is growing rapidly, the concept of shallow remains, new research has claimed.
A Host finger The report found almost 80% of the companies used or plan to use AI, but a separate Adecco Group Report claims only 10% of C-suite leaders believe that their organizations are completely ready for the disruption that AI entails.
Among the estimated 359 million companies worldwide, around 280 million now integrates AI into at least one function.
AI acceptance accelerates, but strategy and structure are lagging behind
A growing number of small companies turn to the Best ai -tools To handle tasks such as writing e -mails, analyzing data or generating content.
Larger companies can build full teams for implementation, but smaller companies quietly transform the activities with the help of slim, sometimes improvised, approaches.
Yet readyness does not follow the acceptance, and there is a worrying gap in strategy, because although 60% of the leaders expect employees to update their skills, 34% of companies do not have a formal AI policy.
Adecco has established that more than half of the CEOs allow their teams to adapt to priorities, and only invests one third of the companies in data infrastructure that would help close these gaps.
A small group of ‘future’ companies, however, builds up more responsive strategies by continuously supporting and trusting business-wide insight to shape their AI direction.
The CEO of Adecco, Denis Machuel, it clearly states: “AI-driven transformation must be people-oriented.”
Many companies hurry in AI acceptance without understanding what distinguishes them, resulting in spread or superfluous projects.
“Without business-wide insight, AI efforts are to stand to a standstill and incorrectly aligned. Enterprise architecture can help concentrate AI initiatives on what a company really distinguishes,” explains Stendera.
By mapping their unique strengths and workflows, organizations can guide AI implementations that strengthen strategic priorities instead of diluting them.
AI not only depends on investments, but on introspection, and it is not a magical solution – and if companies do not understand what they need from AI, they will not know how to use it, and the result will be catastrophic.
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