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ASEAN organizations still struggling to build right data and AI foundation

Efficient data usage has enabled artificial intelligence (AI) to have a greater impact on organizations. For example, generative AI has received hype among big tech companies thanks to its enhanced capabilities that are made possible by the data it has access to. Gartner predicts that emerging technologies like generative AI are still three to eight years away from reaching widespread adoption.

For enterprises, the use of AI for better efficiency and productivity at work has always been the end goal. However, most organizations are facing barriers to making full use of their data and AI.

A recent report by Kyndryl showed that AI adoption among organizations is still low. In fact, findings from the Five Insights to Help Organizations Build Scalable AI report showed that only 7% of organizations in Southeast Asia are focused on building the right data and AI foundation for their business.

The report, in collaboration with technology research and advisory firm Ecosystm, uses feedback from five hundred C-suite leaders across ASEAN. It aims to address data and AI challenges faced by organizations in ASEAN and provide recommendations for them to build scalable strategies that deliver business impact.

According to the study, in ASEAN, there are four main challenges to implementing successful data and AI. This includes the integration of an AI solution within existing systems, which affects 48% of organizations while another 38% struggle with collecting data from multiple sources. 34% also have problems with the quality of data and another 31% struggle with identifying the right data for AI models.

The challenges aren’t surprising given that some organizations jumped onto the AI bandwagon without thinking about how exactly they should use the technology. This problem not only applies to businesses in Southeast Asia but globally as well. Hence, businesses need to have a proper plan in place as they look into building scalable AI.

Making sense of data for scalable AI

As access to data remains a key stumbling block, organizations need to get true insights that can only be derived from a consistent and complete dataset that has no data gaps. Building that dataset requires key conditions such as a focus on clean and trusted data, a data interoperability strategy, and synthetic data generation to bridge data gaps.

Businesses also need data creativity. A true data-first organization derives value from its data and AI investments across the entire organization, and organizations in ASEAN recognize that. Over the next two years from 2023 through 2024, 77% of participants will increase the use of AI and Data solutions for customer experience, 75% for human resources and 72% for marketing.

The returns on investment will be measured in financial terms internally such as an increase in profit margins, cost optimization, reduction of operating costs, and so on – across all lines of business, including IT. This will help identify and prioritize business cases for data.

The report also highlighted that a lack of an internal policy and a limited understanding of the risks (36%) are the two biggest challenges to effective data governance policy in ASEAN. Data governance policies formulated by data-first organizations should include accountability and ownership guidelines, standardized regulations, a dedicated data stewardship team and a regular process for re-evaluation of the policies set up.

As such, organizations must have observability, intelligence, and automation built into the entire data lifecycle. Building a data infrastructure that is ready for current needs but may not be able to support future business requirements as data continues to proliferate, represents a myopic view.

An enterprise data fabric, on the other hand, futureproofs organizations as it speeds up and simplifies access to data assets across the entire business. The metadata generated by the data fabric will include business, technical, and operational data, which can generate insights for the entire business if managed intelligently.

Findings from the report also show that the true value of data and AI solutions will be fully realized when the people who benefit from the solutions are the actual users managing the solutions and running the queries. However, only 10% of organizations in ASEAN have business teams managing or maintaining AI solutions. Building scalable AI will require organizations to empower citizen data scientists through training, and access to user-friendly tools that help them gather the right information for the right insights and make data-driven decisions a norm for the business.

For Ullrich Loeffler, CEO of Ecosystm, executives across the ASEAN region understand that data is the foundation of their innovation and transformation journey. However, building and implementing a holistic data strategy is not easy and we see common challenges around data integration, quality and governance.

“Trust in the data and subsequent AI models is critical to truly embrace a data-driven DNA across the organization and this trust in the data layer is missing in the majority of organizations today,” added Loeffler.

In Malaysia, Joey Mak, Managing Director of   Kyndryl Malaysia explained that data and AI initiatives across organizations in Malaysia are surging as they seek to drive growth, transformation and sustainability agendas. Mak added that IT and business leaders see potential in leveraging Data and AI to unlock real-time insights and deliver the agility that is required to succeed in today’s competitive and volatile market.