By Bhavna Prakash
The APAC region is emerging as a global hub for AI innovation, with investments in the region projected to surge five-fold to US$117 billion by 2030.
From GenAI in Malaysia to locally developed large language models in China and India, and high-profile names such as OpenAI descending upon Singapore to establish presence, the region is positioning itself at the forefront of AI transformation.
But realising AI’s full potential will depend on C-suite leaders driving strategies that align AI implementation with core business objectives. Too often, organisations are embracing AI reactively, leading to suboptimal outcomes and missed opportunities.
This misalignment makes achieving returns on investment challenging. Senior executives in APAC have a unique role in ensuring AI becomes a strategic asset rather than a costly experiment.
The true value of AI and enterprise technology
AI has become the third-most significant technology shift, following the internet and mobile revolutions.
In APAC, reports show that companies are making headway in adoption, yet only 35 per cent report significant value from advanced AI. For many enterprises, it remains a top business priority, especially with AI’s potential to reduce costs and optimise workflows.
AI-driven automation enables employees to focus on higher-value activities, enhancing productivity while reducing operational expenses. Apart from efficiency gains, AI is also a catalyst for revenue growth, accelerating product development, achieving faster time-to-market, and transforming customer experiences.
However, while the benefits of AI are widely discussed, many businesses are too quick to jump on the AI bandwagon without a strategic approach to implementation. Reactive approaches often result in suboptimal solutions that don’t generate the expected ROI.
To unlock AI’s potential, organisations must approach adoption with a deliberate data-driven mindset, ensuring alignment with a company’s strategic priorities.
AI for AI’s sake?
For AI to deliver measurable business value, executives must prioritise solutions that address specific organisational challenges.
In APAC, where customer needs and regulatory complexities shape AI adoption, a process-first approach is critical. Leaders should evaluate whether AI is the best solution for any given problem in comparison to traditional methods that could yield similar benefits at a lower cost. A process-first approach allows companies to address immediate business gaps through AI in a manner that offers tangible benefits without unnecessary complexity; AI success is finely balanced between talent, strategic vision and effective execution.
It’s also crucial to ensure that AI solutions are adaptable across departments and functional roles. CIOs and CTOs need to build flexible structures, guardrails, and workflows, enabling an iterative approach to growth. Flexibility and adaptability are essential for scaling AI solutions. With APAC businesses at 22 per cent of machine learning adoption, prioritising scalability and cross-functionality helps avoid the pitfall of “AI for AI’s sake”, ensuring that investments drive meaningful outcomes across departments.
Embracing agility: People, process and technology
To embed AI within an organisation’s culture, the C-suite must focus on three core pillars: people, process and technology. Beyond technology, it requires an agile culture that supports experimentation, creativity, and continuous improvement. In APAC, reports show that only 15 per cent of businesses feel truly AI-ready, likely facing pressure to deploy within short timeframes and to get implementation right.
To address this, an AI centre of excellence (COE) can be a game changer. By bringing together cross-functional teams—from finance and business units to data scientists and AI engineers—a COE ensures that AI initiatives align with the overall business vision and avoid siloed implementations. This centralised approach fosters collaboration, allowing different departments to share best practices and leverage each other’s insights.
COEs also establish a clear workflow for AI adoption, from ideation to deployment. Employees across the organisation can submit AI ideas through a centralised portal, which are then validated by the COE.
This process not only encourages employee engagement but also allows the company to evaluate the potential value of each idea before committing resources. By centralising AI delivery and sharing best practices, a COE empowers businesses to stay ahead of industry trends, adhere to privacy, security and regulatory guidelines, and refine AI applications based on real-world feedback.
Building a culture of continuous learning and improvement
For AI to deliver sustained benefits, companies must foster a culture of continuous learning.
Upskilling employees through training programmes enables teams to maximise AI’s potential and adapt to rapidly evolving technologies.
Creating feedback mechanisms is also vital to the process—allowing employees to provide input on the effectiveness of AI tools, suggest improvements, and share insights gained from hands-on experience.
Why? Continuous improvement is essential for the longevity of AI applications. By monitoring the business case metrics after deployment, companies can evaluate the real-world benefits of their AI solutions. This feedback loop via the COE allows CIOs and CTOs to make informed adjustments to ensure AI initiatives remain relevant and value driven. This cycle of monitoring and learning creates a culture of agility, where AI tools are regularly refined to adapt to changing business needs.
Finally, the technology selected for AI deployment must be scalable, secure, and aligned with regulatory standards. Choosing the right platforms and tools ensures not only that AI applications are robust but also that they evolve alongside industry advancements. Privacy, security, and ethical guidelines are paramount in today’s AI landscape, and the C-suite must prioritise these aspects to build and maintain public trust.
