APAC Companies Go All-In for the “AI Pivot”

Forget cautious tiptoeing around AI. Asia-Pacific businesses are diving headfirst into the GenAI revolution and playing for keeps.

A bombshell report from IDC reveals that regional leaders are demanding an 80% success rate on their generative AI initiatives by 2027. No more pilot purgatory or lukewarm ROI. APAC companies are done with dabbling, according to the report; they want to see AI driving real business value fast.

This insight, dropped at the recent IDC FutureScape event in Singapore, signals a seismic shift in the AI landscape. The “innovate or die” era has morphed into “innovate with AI or be left in the dust.” IDC’s group vice president and general manager Sandra Ng calls 2025 the year of the “AI Pivot,” a do-or-die moment where enterprises must transition from AI experimentation to full-throttle execution.

“It’s no longer a question of whether to embrace AI,” warns Ng. “It’s about how quickly and effectively you can weaponize it to outmaneuver the competition. Companies clinging to outdated business models will be steamrolled by those who can harness the power of AI.”

But achieving that 80% success rate won’t be a cakewalk. IDC has identified seven critical pillars that APJ enterprises must conquer to become true AI powerhouses:

1. Strategy: Forget siloed thinking. Successful AI demands IT and business teams to become buddies, laser-focused on enterprise-wide use cases that deliver tangible results. Companies in pilot mode are essentially throwing money down the drain. IDC predicting over a third of companies will still be stuck in AI experimentation by 2026.

2. Governance: Responsible AI isn’t just a PR stunt; it’s a matter of survival. Companies must embed ethical considerations, brand protection, and data privacy into their AI’s DNA. By 2025, IDC predicts that 70% of companies will have formalized policies to mitigate AI risks. Those who don’t are playing with fire.

3. People: AI isn’t about replacing humans but creating superhuman employees. Upskilling and alignment between executives and the workforce are critical. IDC predicts that by 2027, over half of A2000 enterprises will rely on GenAI-enabled platforms for training and development. Lagging behind? Prepare to be outgunned by the competition.

4. Applications: GenAI is set to unleash a tidal wave of intelligent applications redefining the enterprise’s decision-making. Imagine AI-powered assistants, advisors, and agents that provide real-time insights and recommendations, supercharging productivity and efficiency. By late 2026, IDC estimates that 50% of APJ companies will have harnessed this power. Those who haven’t will be left scrambling to catch up.

5. AI Platforms: The days of fragmented AI tools are over. Unified platforms are essential for orchestrating AI efforts at scale. By 2028, 75% of enterprises with a cohesive AI platform strategy will be reaping the rewards of their investment. Those who fail to consolidate will be left with a mess of incompatible systems.

6. Data: Data is the fuel that powers the AI engine. But many companies are drowning in a sea of “dark data,” unable to extract its hidden value. IDC predicts a surge in multicloud data logistic platforms and data-as-a-product architectures to tackle this challenge. Ignore your data, and your AI ambitions will wither on the vine.

7. Infrastructure: Scaling AI requires industrial-strength computing power. Current infrastructure solutions are fine for playing around, but moving to production demands a robust and scalable foundation. IDC expects a shift towards hybrid, fit-for-purpose infrastructure to optimize performance and cost. By 2028, IDC estimates that 75% of enterprise AI workloads will be deployed on hybrid fit-for-purpose infrastructure to turbocharge time to value while optimizing performance, cost, and compliance. Fail to invest in your infrastructure, and your AI initiatives will stall before they even begin.

Bottom line

The AI revolution is a high-stakes game, and Asia-Pacific businesses are going all-in. For data leaders, this means a relentless focus on data quality, a strategic approach to AI platform adoption, and an unwavering commitment to responsible AI governance. Those who can master these pillars will emerge as victors in the AI arms race, while those who falter will be left behind.

Image credit: iStockphoto/fongleon356