As enterprises in Asia look to harness the power of artificial intelligence (AI), a recent survey by Zapier reveals critical insights into the challenges faced by U.S. organisations—challenges that are likely mirrored in the Asian context.
While 92% of U.S. enterprises prioritise AI, they encounter significant barriers that hinder effective implementation. This disconnect between ambition and reality serves as a cautionary tale for Asian leaders navigating the complex landscape of AI adoption.
According to the survey, 78% of U.S. enterprises struggle to integrate AI tools with existing legacy systems, with 53% describing this process as moderately to extremely difficult. These integration problems resonate with many Asian companies, where outdated infrastructure remains a prevalent issue.
“There’s a huge gap between wanting AI and actually making it work in complex enterprise environments,” notes Emily Mabie, AI automation engineer at Zapier.
The findings also highlight financial concerns, as 45% of U.S. leaders cite high costs associated with AI adoption. For Asia, where competition is fierce and budgets can be tight, this presents a formidable barrier.
Additionally, 35% of leaders in the U.S. point to skills gaps as a significant obstacle. This issue is particularly pressing in Asia, where demand for AI expertise is rising but supply remains limited.
The survey underscores that 81% of U.S. enterprises feel competitive pressure to accelerate AI adoption.
In Asia, where rapid technological advancement is the norm, leaders must not only keep pace but also innovate to stay ahead. The pressure is compounded by the need for effective collaboration among departments; U.S. data shows IT is ten times more likely to lead AI initiatives compared to other departments like sales or HR.
This divide could hinder progress in Asia, where cross-departmental collaboration is essential for successful AI integration.
The Zapier survey paints a complex picture of AI adoption—one that reveals not just fears of job loss but practical barriers such as data quality issues and the difficulty of measuring return on investment (ROI). Companies that report slow AI rollouts often find themselves falling behind competitors, missing productivity gains, and experiencing delayed returns.
To navigate these challenges, organisations in Asia must ensure that their AI tools are interconnected, focus on automating workflows, and democratise AI access across teams while maintaining IT oversight. By addressing these integration challenges, Asian enterprises can bridge the gap between ambition and execution, unlocking the full potential of AI in their operations.
