Covering Disruptive Technology Powering Business in The Digital Age

Attributed by David Irecki, Chief Technology Officer for APJ, Boomi

David Irecki, Chief Technology Officer for APJ, Boomi

In the realm of technology, a new concept or innovation emerges every few years to capture the world’s attention before inevitably giving way to the “next big thing”. Virtualisation, cloud computing, and even the metaverse can be seen as recent examples of such phenomena.

While virtualisation and cloud computing have undoubtedly solidified their positions as foundational elements of modern IT infrastructure, the metaverse, despite its initial fanfare, has not. Instead, the hype surrounding it was overshadowed by the meteoric rise of artificial intelligence (AI).

Though by no means a novel concept, AI really entered the public consciousness in November 2022 when ChatGPT was born. This revolutionary language model showcased an unprecedented ability to comprehend and generate human-like text. In an instant, the world got a glimpse into a future where machines might finally grasp the intricacies of human language, and creativity may now be possible. As ChatGPT turns two, it is now clear that the toddler has not only learnt how to walk – it is running.

In Malaysia, 41% of CEOs expect generative AI to have substantial impacts on their companies, the workforce and markets in the next three years. As organisations recognise AI is here to stay and accelerate adoption, it is also appropriate to identify the steps we need to take to nurture this technology to maturity.

Building a foundation for future success

Security threats, poor data quality, and privacy concerns over sensitive or proprietary information are among the biggest concerns about AI. Ultimately, addressing these risks will require that businesses start with the basics. This includes the back-end systems and processes their AI draws from.

Because it is responsible for implementing the business logic and managing data, among other things, the back-end is a critical component of AI adoption. The ‘garbage in, garbage out’ is particularly true of AI, where poor quality data delivers unreliable AI outputs that lead to inaccurate or faulty responses. Boomi’s “A Playbook for Crafting AI Strategy” Report found that data quality is a critical stumbling block for AI deployment for half of the study’s participants. To ensure AI systems are supported by high-quality data,  we need to give back-end systems and processes due attention to understand the origins and creation processes of the data.

A context pipeline plays a crucial role here. By providing a connected, clean, accurate, and secure data layer in usable formats, it ensures AI receives relevant information specific to your organisation. For generative AI, this means delivering precise and pertinent answers while minimising the errors seen in systems like ChatGPT. Without high-quality, well-structured data, AI systems can underperform and fail to deliver on their potential.

Organisations will need to put in the work upfront to achieve all this. However, it will pay off in the long run, especially as they eventually entrust AI with bigger and more important decisions.

Harnessing AI’s transformative potential
In the next five to ten years, AI-driven innovation will push the boundaries of what businesses can do.

According to the Malaysia Centre for Fourth Industrial Revolution, Gen AI has the potential to add USD113.4 billion in productive capacity to the Malaysian economy. Put in context, that is equal to one-quarter of GDP in 2022.

Given its current trajectory, it’s safe to say that Gen AI is proving to be more than just a passing trend. It is becoming a transformative force that is already reshaping industries and setting the foundation for the next leap in the development of our societies  – where we will see unprecedented synergy between human and machine intelligence in the Fifth Industrial Revolution.

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