Exabytes, a Malaysian digital solutions company, launched GROW AI at its summit in Kuala Lumpur this month, marking a strategic shift from helping businesses go digital to enabling them to adopt artificial intelligence at scale. The initiative extends the company’s 25-year GROW Digital mission into a new phase focused on moving organizations beyond fragmented AI pilots toward integrated, enterprise-wide AI applications that improve productivity and operational performance.
The company has set an ambitious goal: support one million businesses in adopting AI by 2030. Exabytes expects approximately 300,000 of those businesses to come from Malaysia, with the remainder from other Southeast Asian markets and potentially beyond. The initiative arrives as Malaysia advances its AI Nation 2030 ambition and as businesses face mounting pressure to translate growing interest in AI into practical, measurable outcomes.
The timing reflects a real adoption gap. A 2025 Ecosystm study conducted in partnership with Red Hat and supported by Malaysia’s National AI Office found that only 21% of 133 Malaysian SMEs surveyed had progressed beyond AI pilot projects. Around 60% of those businesses cited a lack of in-house technical expertise as a major barrier to adoption. Many organizations understand that AI will affect their competitive position but remain uncertain about where to begin or how to implement it securely.
A Framework Built on Four Principles
GROW AI is built around the RASA framework, which stands for Reliable, Accessible, Scalable, and AI-driven. The strategy integrates Exabytes’ capabilities across cloud infrastructure, cybersecurity, business applications, e-commerce, workplace productivity, automation, and managed AI services. Rather than helping businesses deploy standalone AI tools, the framework aims to connect AI with organizational knowledge, workflows, employees, and operational systems.
Chan Kee Siak, founder and CEO of Exabytes Group, said the initiative represents the company’s next chapter after helping businesses establish digital foundations. “Businesses understand that AI will affect how they compete, but many are still uncertain about where to begin and how to implement it securely. Our role is to reduce that complexity by bringing together the technology, infrastructure, expertise and partners they need to turn AI into measurable business outcomes,” Chan said.
Exabytes itself demonstrates the framework in practice. The company deployed Eve, an AI agent and avatar, two years ago. Eve now handles more than 80% of Exabytes’ Level 1 workload, including sales support, product inquiries, and customer service tasks. This internal success serves as both validation of the strategy and a testing ground for solutions Exabytes plans to package for clients.
Two Critical Barriers to Enterprise AI Adoption
Chan identified data readiness as a significant obstacle for organizations moving beyond AI experimentation. Many companies possess the budget to deploy AI but struggle to organize and prepare data held across different systems. “Many organizations want to implement AI and may even have the budget to do so, but one of their biggest challenges is that their data is not ready,” Chan said.
The second barrier is expertise. A workforce lacking AI skills and understanding makes it difficult for organizations to move from isolated pilots to enterprise-wide deployment. This skills gap drives Exabytes’ internal approach: the company has directed more than half of its overall budget and resource allocation toward AI-related initiatives. That spending extends across infrastructure, employee training, and solution development.
Exabytes is also changing its recruitment strategy. The company first assesses whether AI can perform certain tasks before deciding to hire for or replace a vacant position. However, Chan emphasized that this shift does not mean employees are being made redundant. Instead, existing and new employees are given access to AI tools and training to help them work more effectively alongside the technology.
A Regional Partnership to Scale Enterprise Solutions
At the summit, Exabytes signed a three-year memorandum of understanding with Aurora Mobile, a NASDAQ-listed company. The partnership centers on Aurora Mobile’s enterprise AI platform, GPTBots.ai, and aims to co-develop AI solutions for Southeast Asian markets.
Chris Lo, founder and CEO of Aurora Mobile, said the collaboration addresses a core challenge. “Enterprise AI transformation requires more than deploying a standalone chatbot. Organisations need to connect AI with their knowledge, workflows, employees and operational systems. By combining GPTBots.ai with Exabytes’ infrastructure and regional reach, we aim to help organisations progress from isolated pilots to enterprise-wide AI adoption,” Lo said.
The MoU covers multiple use cases. For SMEs, Exabytes and Aurora Mobile will develop AI-powered sales, marketing, customer service, and internal knowledge assistants. For larger enterprises and public sector organizations, the partnership will focus on private AI deployments, hybrid AI infrastructure, intelligent service desks, and workflow automation agents. Exabytes will deploy GPTBots.ai internally to test workflows before packaging them as repeatable frameworks for business clients.
Implementation at Organizational Scale
Exabytes is addressing a common pitfall: businesses attempting to overhaul every department simultaneously. The company recommends a phased approach, starting with specific high-impact use cases rather than organization-wide transformation. This strategy helps organizations avoid the complexity and cost of simultaneous deployment across all functions.
The GROW AI Summit brought together more than 500 business leaders, technology executives, and public-sector representatives. Sessions focused on practical AI implementation, technical requirements for scaling deployments, cloud infrastructure, cybersecurity, workplace applications, commerce, workforce development, customer engagement, and data protection. Participants included representatives from Amazon Web Services, Lark, Sangfor, EasyParcel, and other solution providers.
Exabytes currently supports more than 160,000 businesses across the region. Reaching one million businesses by 2030 would represent a more than sixfold increase. The company’s willingness to allocate more than half of its budget to AI initiatives signals serious commitment to that target, though success will depend on whether organizations can overcome the adoption barriers the research has identified: technical expertise, data readiness, and the ability to move beyond isolated pilots into integrated enterprise deployments.
The broader question facing the region remains unresolved: whether the infrastructure, partnerships, and training that initiatives like GROW AI provide will be sufficient to close the adoption gap identified in the Ecosystm research, or whether SMEs and enterprises will continue to struggle with the practical implementation that separates pilot projects from measurable business outcomes.