By Cally Chan, General Manager of Microsoft Hong Kong and Macau
Hong Kong is at the forefront of fintech innovations, particularly in AI. With Hong Kong’s first official policy statement on the responsible application of AI in the financial sector, the initiative stresses the need to tackle data privacy and cyber threats. Ultimately, the policy aims to prompt institutions to establish a robust AI governance framework.
Hong Kong has chartered into the age of AI. Our data shows that 85% of business leaders believe AI is crucial for sharpening competitiveness. Yet only 34% of them have a plan to scale up AI adoption, mainly due to concerns around data privacy, security, compliance, and return on investment.
So, business leaders know the importance of scaling up AI adoption, but what I heard most from them are: How do we begin our AI journey? How can we prepare our employees for AI? How do we ensure compliance and security? One way to ensure responsible AI practices in your infrastructure, while benefiting from advanced AI capabilities, is to leverage a trustworthy enterprise-grade AI platform, making sure that your AI governance strategy is in place.
AI deployment starts with data control. The frequent sharing of sensitive data could pose significant threats as businesses accelerate AI and cloud adoption. The vast sum of data shared across departments or with external parties could become prime targets for malicious actors, potentially leading to security issues like unauthorized accesses and data breaches. Considering the increase of cyber threats, data safety has risen as the top concern for chief technology executives and board members in our conversations about AI adoption.
Unnecessary sharing of sensitive information such as customer information across departments can lead to potential misuse or accidental exposure. It’s important to keep this data secure by setting up strong access controls, conducting regular audits, and educating employees about the risks.
For financial institutions that are highly-regulated like banks, insurers, and investment firms, it’s crucial to have strict data control measures. Using an enterprise-grade platform with built-in data protection features like encryption, and sensitivity labelling can help safeguard sensitive information.
To tackle that, you need to adopt enterprise-grade solutions to govern, protect, and manage their data across various environments, which are indeed available in the market.
Beef up AI knowledge and security awareness in no time. According to Hong Kong Productivity Council, 30% of surveyed enterprises are currently using AI in various areas of operations and the number is projected to surge by 20% next year.
We’ve observed that the trend of employees bringing their own AI tools to work is becoming prevalent. Imagine your frontline staff using customer personal information with an AI model that uses this data for training; this could cause data leakage and increase security and privacy risks, as some AI tools might not comply with security protocols.
With rising regulatory expectations and customer demands, financial institutions must prioritize AI and security training. Additionally, it is essential to educate employees of all levels on responsible AI use and best practices specific to their roles, guiding them on how to start a conversation with AI with a security by default mindset, as well as best practices tailored to their respective job functions.
Devoted to empower the financial services industry to spearhead innovations in AI in a secured manner, Microsoft encourages organizations to leverage free resources such as online courses and certifications to enhance employee performance through AI tools through its Skills for Jobs Program.
You need to adopt an enterprise–grade AI platform for enterprise use. Based on my conversation with leaders who are eager to scale up AI adoption, many of them are battling to expedite their AI journey that gatekeeps compliance and security while ensuring preparedness of the workforce. To safely set sail into the AI era, they must build an ark leveraging a trustworthy enterprise-grade platform that ensures the responsible AI practices are indigenously embedded in the infrastructure while optimizing the benefits of advanced AI capabilities.
Starting with small steps through a test-and-learn approach will not only secure Hong Kong’s competitive edge as an innovative international financial hub but also secure a promising return on investment under an international standard. With these strategic moves, the future of AI in Hong Kong’s financial sector is not just bright—it’s unstoppable.
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