Many APAC organisations still face barriers when scaling AI adoption, often being stuck in pilot mode and encountering difficulties getting enterprise-wide impact, including their digital/ERP modernisation/transformation.
How can they really unlock real business value from AI, which functions should they start with, and how can they integrate AI in their ERP to increase efficiency and gain a competitive advantage?
iTNews Asia uncovers these questions in a chat with Victor Ng, Vice President and Managing Director for Southeast and North Asia, Infor.
iTNews Asia: How do you see the role of ERP and industry-specific systems in enabling AI adoption amongst organisations in APAC?
One of the biggest shifts we are seeing is that organisations are now asking how to embed AI into the way their business operates. As they scale AI, enterprise systems become increasingly important because they provide the operational context across business processes, industry knowledge and real-time information, which enables AI to generate recommendations that are relevant and actionable. Whether it’s improving demand forecasting, optimising production or streamlining supply chains, AI delivers the greatest value when it understands how the business actually works.
Ultimately, organisations won’t differentiate themselves by simply deploying more AI. They’ll differentiate themselves by embedding AI into the operational processes that drive business performance.
iTNews Asia: What’s driving their AI adoption?
What's changed over the past year is that AI conversations have become much more outcome-focused. Previously, organisations were exploring what AI could do. Now, they are identifying where AI can solve meaningful business problems and how success should be measured.
From the conversations we're having with customers, organisations are operating in an increasingly complex environment shaped by supply chain volatility, geopolitical uncertainty and growing pressure to improve productivity. AI is increasingly viewed as a practical way to help organisations respond faster, improve decision-making and build greater operational resilience.
This shift is also changing investment priorities. Rather than pursuing broad AI programmes, organisations are focusing on high-impact operational use cases where they can demonstrate measurable improvements before expanding adoption across the business.
iTNews Asia: Are most organisations here still in the early stages of AI development? How smooth or difficult has their AI journey been?
Most organisations have already demonstrated that AI can deliver value through pilots. The challenge now is moving beyond these individual successes to scale AI capabilities consistently across the enterprise.
Scaling AI requires clear governance, modern business applications, employees who are confident working alongside AI, and the ability to integrate AI into day-to-day operations. Those foundations are still developing across many organisations in APAC, particularly as digital maturity varies significantly across industries and markets.
The challenge is no longer identifying opportunities to apply AI, but determining where it can deliver meaningful, lasting business impact.
iTNews Asia: What typically are the challenges your customers face in their AI and digital/ERP modernisation/transformation?
We typically see three common challenges.
Firstly, many organisations still operate with fragmented enterprise systems and inconsistent data, making it difficult for AI to generate reliable insights and scale beyond individual use cases.
Secondly, workforce readiness remains a challenge. Demand for AI skills continues to outpace supply in many Asian markets, making workforce readiness, upskilling and change management just as important as technology investment.
Finally, many organisations struggle to identify where AI can deliver the greatest business value. Rather than pursuing broad transformation programmes, organisations seeing the strongest outcomes begin with clearly defined business priorities, then modernise the underlying processes needed to support long-term AI adoption.
iTNews Asia: While AI adoption is fast growing in the region, a lot of the discussion this year has been on the difficulty of organisations to scale. What are the barriers preventing them from launching complex AI initiatives, even among companies with strong ambition to scale?
The challenge today is less about AI capability and more about readiness and execution. Many organisations have demonstrated value through pilots, but scaling AI introduces new requirements around data, governance, integration and connected operational workflows that often only become apparent once organisations move beyond experimentation.
iTNews Asia: How then can organisations move from pilots to obtain enterprise-wide impact?
For enterprises to scale, AI needs to operate across multiple business functions, comply with governance requirements and coordinate actions across teams. Organisations with fragmented ERP systems, disconnected operational workflows and inconsistent data often find that AI becomes difficult and costly to scale.
This is particularly important in APAC, where organisations often operate across multiple markets with different regulatory, operational and business requirements. Building a scalable AI foundation means organisations need more than high-quality data. They also need connected systems, strong governance and a unified enterprise environment that allows AI to scale consistently across functions and regulatory environments.
The most successful organisations are those that focus first on strengthening the foundations that allow AI to be deployed more consistently, then expanding into new use cases as confidence grows. Scaling AI is ultimately a business transformation journey, and not a technology rollout.
-Victor Ng, Vice President and Managing Director for Southeast and North Asia, Infor
iTNews Asia: Infor has said often that agentic AI cannot just be a feature bolted on. How should organisations approach AI agents?
Agentic AI should be viewed as an extension of an organisation's operational systems, not as a standalone AI tool. Its role should be to augment existing business processes rather than introduce new complexity. AI agents need access to trusted enterprise information, industry-specific knowledge and clearly defined business rules to make decisions that are relevant and actionable.
That's why we say agentic AI cannot simply be "bolted on". A generic AI agent may be able to answer questions, but organisations will realise greater value from AI agents that understand the workflows, terminology and operating requirements of their industry.
Rather than focusing on deploying as many AI agents as possible, organisations should identify business processes where industry-aware AI can remove operational friction, automate routine work and help employees make faster, better-informed decisions.
iTNews Asia: What practical advice for CIOs and IT leaders can you give on their agentic AI implementation? How critical is the ability for AI to perform tasks autonomously as a priority for enterprise success?
While autonomy is an important goal, my advice would be to begin with the business outcome they’re trying to achieve. When CIOs start with a specific operational challenge, establish clear measures of success and establish governance from the outset, they are more likely to see measurable results.
As confidence grows, AI can gradually take on more complex activities, while employees continue to provide oversight for higher-impact decisions.
It is equally important to prepare employees for this transition. AI adoption is as much about organisational change as technology implementation. Organisations that invest in skills, governance and business alignment alongside AI will be far better positioned to scale adoption than those focused solely on deploying new capabilities.
iTNews Asia: How can this success be measured?
Success should be defined by the measurable value AI delivers rather than the number of AI tools or AI agents deployed. Organisations should look at improvements in operational performance, such as better forecasting accuracy, faster decision-making, higher productivity, improved process consistency and stronger operational resilience. These indicators show whether AI is becoming embedded in day-to-day operations rather than remaining confined to isolated pilots.
iTNews Asia: Finally, how can APAC organisations maximise their business ROI from AI?
To maximise return on investment, organisations should prioritise solving specific operational challenges, validate the impact, then build on those successes over time. Sustainable ROI comes from solving business problems at scale, not deploying AI for its own sake.
