AI & Data Science Talent in APAC: Executive Hiring Trends

The APAC Race for AI & Data Science Talent

The Core Challenge: Demand Is Outpacing Supply

Artificial Intelligence and Data Science roles continue to dominate global hiring momentum. This is reflected clearly in LinkedIn’s Jobs on the Rise 2026 list, where AI, Machine Learning, and advanced analytics feature prominently across regions and industries.

AI literacy is no longer niche. It is rapidly becoming embedded in everyday work and decision-making. While interest from candidates transitioning into data and AI roles is growing, conversations with senior leaders consistently point to a more acute challenge: the scarcity of deep, technically credible AI and Machine Learning talent. This represents a far smaller, highly competitive pool.

The global backdrop reinforces this imbalance.

According to the World Economic Forum, Data Analysts and Data Scientists are projected to see 85% net employment growth, compared with a global benchmark of 41%. Structural churn for these roles also sits at 85%, indicating intense job creation alongside rapid skill displacement.

Key findings from The Future of Jobs Report 2025 include:

93% of employers plan to hire talent to design AI tools
71% plan to hire talent to work alongside AI or re-orient roles around AI
Skills gaps remain the primary barrier to transformation (65%)
Difficulty attracting talent remains a significant constraint (44%)

Across APAC, this translates into persistent demand–supply gaps, rising compensation at senior levels, and increasing competition for leaders with real-world GenAI and production-scale deployment experience.

Against this backdrop, organisations must think carefully about where and how they build AI capability.

Market Snapshots Across APAC

India

We would like to share Boyd & Moore’s latest research and observations across four key APAC markets.

India has an estimated 416,000 AI/ML and big data professionals, ranking second globally after the US. However, demand continues to outpace supply, commonly estimated at a 40–50%+ demand–supply gap. AI and data hiring is growing at 40–60% annually.

Talent is concentrated in:

Bengaluru hosts major AI and data science operations for global firms such as Google, Microsoft, IBM, Goldman Sachs, and Target.

Hyderabad is rapidly emerging as a GCC powerhouse, with large-scale centres from Eli Lilly, PepsiCo, McDonald’s, Qualcomm, and HSBC.

India offers the strongest cost efficiency for data science hiring, making it well suited to scalable GCC and delivery models, with a salary range of US$15k–155k.

Singapore

Singapore’s tech workforce stands at approximately 214,000, with an estimated 12–18% working in AI, data analytics, and cybersecurity which is one of the fastest-growing segments.

Key structural constraints include:

In 2025, Singapore continued to attract high-value AI investments, including:

Singapore remains a preferred APAC headquarters location for senior AI leadership, governance, and regional analytics teams rather than large-scale delivery centres, with a typical salary range of US$70k–235k and upward.

China

China possesses a large and rapidly expanding AI talent base, but advanced-level capability remains constrained. Estimates suggest China may require up to 6 million AI professionals by 2030, while domestic supply may meet only one-third of that demand.

Talent is concentrated in Shanghai, Beijing, and Shenzhen.

China produces the largest STEM graduate pipeline globally, with approximately 12.2 million university graduates annually and 77,000 STEM PhDs. However, senior-level and deep GenAI capability remains scarce.

Hiring data reflects this imbalance. While AI job postings grew modestly in 2025, applicant volumes surged significantly, intensifying competition for high-end talent. Multinationals typically operate R&D and innovation hubs rather than traditional offshore GCCs, particularly in Shanghai and Beijing.

China is not a low-cost market but remains strategically critical due to its depth in advanced AI, particularly in computer vision, recommendation systems, GenAI, and large-scale production deployments. The typical salary range is around US$85k–280k.

Australia

Australia’s tech workforce has surpassed 1 million professionals, but projections indicate a requirement of 1.3 million by 2030, leaving a projected shortfall of nearly 300,000 roles.

Data science talent is heavily concentrated in:

Major employers include global tech firms, international banks, and the big four Australian banks, all of which continue to expand in-house analytics and AI capability.

With a salary range of US$95k–170k, Australia is a high-cost but relatively predictable market, attractive for stable, long-term senior hires, though less suited to cost-arbitrage strategies.

What This Means for Organisations

Across APAC, the competition for AI and data science talent is no longer purely about cost.

At senior and lead levels, China, Singapore, and Australia increasingly converge toward US compensation benchmarks, while India remains materially lower despite strong technical capability.

Organisations that succeed are those that align location strategy, role design, and compensation with the specific value each market delivers — balancing cost, capability depth, and speed to impact.

How Can We Help?

Across APAC, the competition for AI and data science talent is no longer purely about cost. Capability depth, speed to impact, and time-to-outcome are becoming equally decisive. Organisations that succeed are those that align location strategy, role design, and compensation with the specific value each market delivers.

Boyd & Moore Executive Search continues to work closely with clients across APAC to attract and secure scarce AI and data science leaders during this critical phase of market evolution. We would be pleased to discuss how these insights apply to your organisation’s hiring strategy.

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