Indonesia's Long Road to an AI Giant by 2045: Why Are Many Companies Still Stuck in the Pilot Stage?
Indonesia’s ambition to become a leader in artificial intelligence (AI) by 2045 has been solidified by the national road map and the Making Indonesia 4.0 vision. However, reality on the ground reveals a sizable gap between ambition and execution. Many domestic companies are still wrestling with early stages and struggle to move beyond pilots.
The phenomenon of being stuck at the pilot stage has drawn serious attention from Michael L. Pireca, Chief Financial Officer of Rimini Street. He notes that the root problem often lies in a fundamental misunderstanding of the technology itself. Many organisations decide to adopt AI because of hype or by following trends, rather than developing a deep understanding of how the technology can deliver real business value. “Often, companies are stuck at the prototype stage because the demo looks good,” he said. “But it does not deliver the results expected or aligned with the initial demonstration.”
Focusing on needs, not just trends
To overcome this bottleneck, Michael emphasises the importance of business readiness before truly implementing AI. Companies need to evaluate their processes comprehensively, particularly in areas that still rely on manual components. Automation at those touchpoints is believed to deliver significant benefits, even if existing processes are already considered to be functioning well. The recommended approach is business-centric, prioritising business needs before seeking AI tools or innovations. By identifying the biggest pain points in operations, companies can set realistic priorities and ensure every investment yields measurable impact for the organisation.
Funding strategies: “Revenue from savings”
Another major challenge is budgeting. In the face of IT budget constraints, Rimini Street offers a model of ‘revenue from savings’ as an innovative funding solution. Rather than replacing old systems with expensive new software, companies are encouraged to optimise existing Enterprise Resource Planning (ERP) systems. “Companies can fund innovation without increasing IT expenditure by achieving better outcomes from the systems they already have,” Michael said. With more efficient third-party support, organisations can significantly cut IT operating costs. The resulting savings are reinvested to fund AI projects. Notably, Michael stresses that this model is not designed to reduce headcount. “We are replacing vendor software expenses, not people,” he asserted. With more stable and efficient systems, employees are expected to move to more strategic and satisfying roles. Through a combination of solid business readiness and smart funding strategies, Indonesia’s AI scaling challenges are hoped to be addressed without burdening company budgets.
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