SHRPA 2026 Global Executive Insights: Regional View on Scaling AI Transformation

Across APAC and the ME regions, AI transformation is picking up pace. Regional disparities exist, but broader trends suggest that organisations are past experimentation and are moving towards functional adoption. Yet there are very few organisations where enterprise AI transformation is taking place.

41% of organisations are still in the experimentation stage, and 37% of organisations are in the functional adoption stage. However, only 22% of organisations are leading AI transformation across enterprises. 

The Middle East region has the highest number of organisations that are in the functional adoption stage, followed by the SEA region. India has the highest number of organisations which are still in the pilot stages or are yet to start AI transformation.

This suggests that while organisations are able to start their AI transformation journey, most organisations are still finding it difficult to sustain the momentum and move towards scaling this to functional levels and eventually to enterprise levels. 

Where are HR leaders focusing their attention for AI adoption in HR? 

Adoption is highest in hiring and HR operations across the regions. While AI adoption in learning, employee experience and performance is lagging compared to hiring and HR operations. However, India has higher adoption levels in these HR areas as compared to other regions.

In addition to the high levels of AI adoption, HR leaders also anticipate a high impact of AI in hiring and HR operations. This could be a reinforcement of confidence developed due to repeated usage of AI in these HR areas and the availability of strong use cases.

Across APAC and ME, investments are planned to increase in attracting talent and talent development and upskilling. HR leaders in the Middle East are also planning to increase investments in improving productivity through Gen AI and automation. Areas like employee experience, total rewards and career growth are expected to see a drop in investments. 

How is the HR tech market across APAC and ME supporting AI adoption?

The HR tech market landscape across APAC and ME is presently divided between two forces. On one side, consolidation is underway, with established players acquiring AI-native point solutions. On the other side, the market remains fragmented, with multiple AI-native solutions competing for the top spot. 

The consolidation is observed more across the SEA and the ME market, whereas the India market displays a fragmented and diffused market with market share distributed across multiple HR tech platforms. 

HR leaders across APAC and ME highlight the dearth of capabilities for skills intelligence and real-time skills mapping in the present HR tech platforms. With a focus on talent development and upskilling, skills intelligence becomes crucial for HR leaders to equip themselves. 

HR leaders in the ME and SEA region also seek  HR capabilities that can assist with decision-making. Capabilities that enable predictive talent analytics and better HR data infrastructure are essential for better decision-making and are presently underserved in these markets. HR leaders in India however, are underserved in workforce planning and workflow automation capabilities which assist with optimisation of workforce. 

What are the regional differences in building enterprise AI maturity?

The primary challenge for HR leaders across APAC and the ME in any HR transformation is being able to move from pilot to scale. This is reflected in the maturity levels of organisations across the regions as well, with a good fraction of organisations being able to go past isolated experiments but getting stuck before enterprise AI transformation. 

The three non-negotiable foundation pillars, which are necessary to get right for scaling AI transformation, are ownership of transformation, data readiness and workforce AI readiness. These areas are critical for any organisation to attend to avoid stalling their transformation efforts at the beginning of the process. 

Ownership for AI transformation:

Across the regions, HR leadership have emerged as a primary owner of the AI transformation process. The other key stakeholders of the process are the IT function and dedicated change management teams. 

For a regional perspective, there is a high degree of ownership clarity across the ME region, with 64% of organisations selecting HR leadership as the sole stakeholder. The ownership is slightly diffused in the SEA region and highly diffused in the Indian organisations, with no clear ownership structure and mostly driven by co-ownership across different stakeholders in the process.

Source: SHRPA 2026 Business & HR Leaders Survey

Data readiness for AI transformation:

46% of HR leaders across APAC and the ME regions find data challenges as the primary challenges limiting their organisation’s AI adoption. The data challenges cover data privacy and security, as well as infrastructural challenges like fragmented and inaccurate data across systems that are not integrated. 

Within data challenges, SEA and the Middle East regions are grappling with a lack of integration across systems as a primary data challenge. Issues with fragmented and inaccurate data are also more commonly observed in the SEA and the Middle East region as compared to India. 

Workforce AI readiness: 

Skills requirements are changing as organisations are adopting AI in their workflows. With the introduction of AI, HR leaders feel that developing a dual demand for deep expertise and AI fluency will be a key skill that will surface across levels and job roles. 

While the workforce is facing a dual demand for deep expertise and AI fluency, human judgement skills are not getting prioritised for executive leadership roles. HR leaders in the ME and SEA regions are doubling down on the combination of deep expertise and AI fluency skills for their executive leadership roles, but very few HR leaders want reinforcement of human judgement skills for these roles. 

For HR leaders in India, the focus is beyond deep expertise and AI fluency being the only changing skill requirement due to AI for executive roles.

This may result in a loss of context setting by humans in AI workflows, as technology will make more decisions for the workforce without the historical organisational context and human judgement.

What HR leaders must focus on?

With regional differences observed across the three essential pillars of enterprise AI maturity, HR leaders in organisations with a global presence must acknowledge the disparities and localise their transformation strategies based on regional insights. Additionally, leaders can also take learnings from other regions on how they approach AI maturity and what should be prioritised, which can result in scaling AI transformation successfully.

Download the SHRPA 2026 HR Tech and Transformation Global Executive Insights here.