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During a keynote panel discussion at the IBM Hong Kong Technology Forum 2025, a distinguished group of experts delved into the future of AI-powered automation, underscoring the critical need for responsible AI adoption and governance.

The discussion covered various aspects of AI adoption, including use cases, ROI, governance, risk management, and education. The panelists highlighted the importance of starting now, being purpose-driven, and considering risk management, while also emphasizing the need for governance frameworks, education, and training to ensure responsible AI deployment.

Moderated by Karen Ko, Managing Director, APAC Financial Services Transformation Lead, Protiviti HK, the panel featured Alfian Michael Sharifuddin, Managing Director & Head of Technology and Operations, Hong Kong & Mainland China, DBS Bank (Hong Kong) Limited,  David Chan, General Manager of Global Innovation at MTR Corporation, Kenny Au, General Manager & Head of Operations Division at The Bank of East Asia Limited, and Jerry Zhu, Director, Client Success Leader of IBM Asia Pacific.

The Imperative of Responsible AI Adoption

As AI continues to revolutionize industries, organizations must proactively embark on their AI journey, navigating the associated risks and challenges.  They also need to consider the ethical implications of AI adoption, selecting the right technology platforms and the right partners to build the fair, transparent, and unbiased AI Systems. This includes implementing robust risk management and governance frameworks to mitigate potential risks, such as data breaches, job displacement, and reputational damage, while also align the  AI systems with business goals and societal values.

"We must accelerate our AI journey today, but it's equally crucial to start small, identify the right partner, and rapidly scale with quantifiable ROI," emphasized Jerry Zhu, Director, Client Success Leader of IBM Asia Pacific.

Real-World Examples of AI Adoption

The panelists shared several examples of AI adoption in their respective organizations and their tips to the business leaders.

Kenny Au, General Manager & Head of Operations Division at The Bank of East Asia Limited, emphasized the importance of building AI solutions that serve a purpose, citing examples from his bank's experiences with generative AI, such as using AI-powered document summarization to reduce production time for credit memos and corporate events preparation from five to six hours to just 30 minutes.

“Besides generative AI that’s causing a lot of attractions, we should also think about the traditional AI that we already have in the banks. The key is to identify the right applications for AI and find solutions that are embedded in our business processes, making the end-to-end journey more successful,” reminded Kenny.

Alfian Michael Sharifuddin, Managing Director & Head of Technology and Operations, Hong Kong & Mainland China, DBS Bank (Hong Kong) Limited, highlighted the bank's innovative use of AI in sales agent training, where AI agents listen in on sales calls and provide coaching and advice to relationship managers on improving their performance.  He also noted that the bank has implemented over 200 AI use cases, with a focus on areas such as Know Your Customer (KYC), Anti-Money Laundering (AML), and code simplification.   

“To ensure a smooth AI adoption, we need to educate everyone, from employees to stakeholders, about the benefits and limitations of AI, and make them comfortable with the idea of working alongside AI agents.  We’ve established a robust risk management framework, with dedicated teams across our organization, to carefully assess the risks associated with each AI model, ” shared Alfian.

David Chan, General Manager of Global Innovation at MTR Corporation, shared examples of MTR's AI-powered initiatives, leveraging the operational technology that combines AI with IoT for smart maintenanceⁱ, smart mobility, and using computer vision to have AI monitor and control the passenger flow at major interchange stations in Hong Kong, ensuring a smoother and more efficient travel experience.  

“While we’re excited to deploy AI, we mustn’t overlook the risks associated with it; we need to strike a balance between adoption and risk mitigation. We need to educate our team to understand what it means to them in their data operation, because they will face different challenges and they are not going to use the same type of AI in their daily life,” highlighted David.

Jerry Zhu also cited the success story of Nextel Brazil, which implemented IBM's AI-powered solution to improve network incident response time from 30 minutes to just 5 minutes, achieving an 83% reduction in response time. ⁱⁱ

“Rather than trying to tackle everything at once, we should start with small, manageable projects, focus on quick wins, and build from there to overcome internal resistance and scale AI adoption, ” reiterated Jerry.

The Importance of Governance and Risk Management

The panelists all stressed that organizations must carefully consider the governance and risk management implications of AI adoption, and drive transparent, explainable, and fair AI systems.

Karen Ko, Moderator, Managing Director, APAC Financial Services Transformation Lead, Protiviti Hong Kong, summarized the key takeaways, "This expert discussion reinforces the imperative of responsible AI adoption, emphasizing the importance of governance, risk management, education, and strategic implementation. By adopting AI in a thoughtful and intentional manner, organizations can unlock its full potential and drive sustained business success."

The key takeaways:

1. Start now: Don't wait, begin AI adoption today to stay ahead.
2. Be purpose-driven: Identify specific problems to solve and ensure AI solutions align with business goals.
3. Consider risk management: Balance AI adoption with risk mitigation to avoid negative consequences.
4. Establish governance frameworks: Develop robust risk management and governance structures to ensure responsible AI use.
5. Education and training are crucial: Educate employees on AI, its benefits, and its limitations to facilitate successful adoption.
6. Start small: Begin with low-hanging fruits and build on early successes to overcome internal challenges and resistance.

About the IBM Hong Kong Technology Forum

The IBM Hong Kong Technology Forum provides a unique platform for industry leaders to share insights, expertise, and best practices in AI-driven transformation, fostering a deeper understanding of how enterprises can harness AI to stay competitive in today's rapidly evolving digital landscape.  The IBM Hong Kong Technology Forum 2025 brought together over 360 industry leaders and technology pioneers from more than 150 organizations to explore the transformative power of AI on March 13, 2025.

ⁱ Reference case: Advancing Asset Lifecycle Management with IBM Maximo at MTR Corporation
March 28, 2025
ⁱⁱ Source: Nextel Case Study https://www.ibm.com/think/topics/network-operations-center