Harnessing Generative AI for Data Modernisation

By Praveen Kumar, Vice President for Asia Pacific at Rocket Software

Artificial intelligence (AI) is quickly becoming a core driver of innovation and competitive advantage. By 2030, AI is expected to generate approximately US$115 billion in productive capacity for Malaysia. This contribution to Malaysia’s national GDP demonstrates AI’s potential across manufacturing, healthcare, finance, and public services.

As a result, AI is now a key driver of growth for the country. The Malaysia AI Roadmap developed by the Ministry of Science, Technology and Innovation (MOSTI) serves as a guideline to develop an AI innovation ecosystem, leveraging AI as a critical driver for productivity. To improve the delivery of public service, the AI at Work 2.0 initiative will equip up to 445,000 public officers with Google’s latest suite of generative AI (GenAI) solutions.

At Rocket Software, we help our clients unlock the full potential of AI to help them solve complex IT challenges across infrastructure, data, and applications. Here are the trends we expect to see in enterprise AI throughout 2025:

Prediction 1 — Extracting more value from unstructured data, faster

GenAI is already reshaping the way businesses approach unstructured data, internal processes, and operational challenges. Currently, unstructured data makes up around 90% of enterprise data. In Malaysia, over 80% of banks have implemented at least one AI-driven initiative, primarily in customer analytics, fraud detection, and electronic Know-Your-Customer (eKYC) processes.

According to IDC, GenAI will help equalise spending on unstructured and structured data processing and analysis software by 2027, doubling unstructured data’s productive use by APAC organisations. As a result, more businesses will deploy GenAI to unlock insights from their unstructured data.

Prediction 2 — Breaking down bottlenecks with AI

As more organisations integrate AI into their operations, the technology will increasingly support cross-departmental data access and streamline operations. The AI at Work 2.0 initiative which aims to automate routine tasks will allow public officers to focus on higher–value work. Additionally, the recent Public Sector AI Adaptation Guidelines launched by Malaysia’s Ministry of Digital aim to assist government agencies in responsibly adopting AI, further underscoring efforts to automate and improve citizen services.

By integrating GenAI into existing workflows, organisations can streamline operations and boost productivity across various departments. Eventually, we could see these new workflows improving efficiency and breaking down departmental silos.

Prediction 3 — A rise in demand for solutions and talent

Despite the potential benefits of AI, many companies still face challenges around data security and talent shortages, especially when it comes to experts that can effectively manage AI models. But this is set to improve. As investments in AI steadily increase, we expect to see a rise in demand for solutions that simplify AI integration and provide stronger security measures to protect sensitive data — as well as talent that can bring out the most value from these AI models.

Prediction 4 — Increased focus on data security and risk management

The continuous evolution of AI models will require constant vigilance when it comes to data security and risk mitigation. In the Asia-Pacific region, countries like Malaysia and Singapore have proactively developed AI governance frameworks to address these challenges. The establishment of Malaysia’s National AI Roadmap and AI Governance Framework outlines ethical AI adoption, emphasising transparency, accountability, and risk mitigation. Singapore’s AI Verify Initiative serves as the world’s first AI governance testing framework, helping companies validate their AI models against internationally recognised principles.

AI is rapidly evolving and transforming industries, but it also introduces significant risks. It’s critical for companies adopting GenAI to prioritise data protection, governance, and model accuracy. We predict that vendors and organisations will work together to prioritise risk management. The goal here is to make AI powerful, trustworthy, and secure.

The future of GenAI is yet to be written

AI is becoming a core element of everyday use across applications and personal devices. Organisations that can adapt quickly and effectively to AI — either by integrating it into existing systems or developing new workflows — will stand to gain a competitive edge, unlock new insights, and set the stage for a more data-driven future.

AI adoption is a journey with no end in sight, but with the right strategies and partners, organisations can capture its full potential.

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