How Companies Turn AI Pilots Into Powerhouses in 2025

Enterprises across Asia-Pacific are accelerating their use of artificial intelligence. However, most still struggle to move beyond pilot projects into full-scale operationalization. In a conversation with iTNews Asia, Mitch Young, Senior Vice President for APAC at Zendesk, outlined the critical steps organizations must take to transform AI from isolated experiments into a core driver of customer value, revenue, and operational efficiency. 

Young emphasized that successful scaling starts with a strong technological foundation. Thus, this includes reliable data pipelines, integration across legacy systems, and infrastructure that can support continuous AI expansion. Hence, without these basics, early AI use cases stall before delivering long-term impact.

But technology alone is not enough. Young highlighted that human readiness and cross-functional alignment remain some of the biggest barriers to enterprise-scale adoption. Skills gaps, lack of AI literacy, and limited trust in AI systems often prevent teams from using AI effectively, leaving deployments stuck in siloed pilots. 

Common scaling pitfalls include: 

• Firstly, overconfidence in custom-built AI solutions that later become costly to maintain 

• Secondly, poorly integrated workflows that limit the value of automation 

• Thirdly, underdeveloped governance, visibility, and risk controls 

Additionally, Young noted that modern no-code platforms and unified knowledge systems are helping organizations bypass some of these hurdles and accelerate deployment timelines. 

Importantly, the role of AI in the enterprise is shifting from cost reduction to revenue generation. Companies using AI to improve service quality are reporting higher customer satisfaction, increased loyalty, and new cross-sell opportunities. Young recommends that organizations target 80% automation of routine and mid-complexity tasks. This enables human agents to focus on high-value interactions that require empathy or judgment. 

To scale effectively, Young advises APAC organizations to begin with one high-value use case, adopt iterative experimentation, and prioritise governance, compliance, and transparent AI practices from day one. “Start with strong foundations, focus on measurable outcomes, and scale step by step,” he said. “Success will follow.” 

 

Source: 

https://www.itnews.asia/news/from-pilot-to-powerhouse-tips-on-how-organisations-can-scale-ai-621936