Asia Pacific enterprises are starting to gain significant traction with AI – but will need to plug gaps in strategy and skills if they’re to reach full maturity. ServiceNow’s inaugural Enterprise AI Maturity Index found that in the four major APAC markets surveyed – Australia, India, Japan, and Singapore – enterprises are more likely to have operationalised AI than the global average. In most of those markets, the CEO’s office is more likely to be significantly using AI than elsewhere in the world, suggesting that Asia Pacific leaders wield outsized influence on the pace – and returns – of AI adoption.
What then should these leaders focus on if they want to achieve and sustain greater maturity with AI?
While only 1 in 10 Asia Pacific enterprises consider themselves very mature in AI adoption, a substantial minority have already begun to generate strong ROI from the technology.
When it comes to increased efficiency and productivity, 36% of Indian enterprises have derived more than 15% return on their AI investments, along with 33% of Australian enterprises – significantly higher than the global average of 26%. Those increases appear to be translating into greater revenues too: 30% of Indian enterprises and 27% of Australian enterprises have seen AI increase their revenues by more than 15%.
Not all Asia Pacific markets have achieved such success. In Singapore, for example, only 18% of enterprises have improved efficiency and productivity by more than 15%, while 13% of enterprises have in fact seen their pace of innovation slow down.
Despite promising signs of growth with AI, Asia Pacific enterprises may struggle to maximise their returns in the longer term due to an overabundance of technology solutions and systems. In Singapore, 77% of enterprises are acquiring AI from a mix of new and existing vendors – significantly more than the global average, of 64%. Similarly in both Australia and India, 67% of enterprises in each country take the same approach with AI procurement.
This points to increasing risk of “solution sprawl”: when enterprise systems multiply out of control, leading to endemic issues with unstructured data and organisational silos. The Index’s findings suggest many enterprises are yet to fully recognise the risks of solution sprawl: in Australia, Japan, and Singapore, less than 1 in 2 have made significant progress on connecting data and operational silos to achieve concrete results with AI.
Even APAC’s AI Pacesetters will need disciplined leadership, focused on consolidating platforms and structuring data, to curb the spread of solution sprawl.
Asia Pacific enterprises have adopted AI unequally across their organisations. In Australia, India, and Singapore, for example, more than 55% of enterprises are already using AI significantly in their strategy and corporate finance functions. Yet in all three markets, less than 20% have adopted AI to a similar extent in HR.
That is set to change sooner rather than later. In India – the market with the highest levels of AI maturity and ROI throughout the region – 43% of enterprises plan to deploy AI to assist with hiring, while 52% intend to improve performance management with AI. Indian enterprises are also more likely than their regional peers to consider AI’s impact on employee experience, with 85% considering it to be important compared to 74% globally. It appears that growing maturity with AI usage has rendered Indian enterprise leaders increasingly attentive to the correlation between effective technology and people strategy.
This focus on applying AI to HR operations comes as demand for AI skills reaches fever-pitch in the region. In every Asia Pacific market covered by the Index, we saw most enterprises planning to ramp up hiring across a spread of roles in AI engineering. Some examples:
- In Singapore, 65% of enterprises expect to hire more data scientists.
- In Australia, 49% expect to hire more machine learning engineers.
- In India, 60% expect to hire more AI configurators.
- In Japan, 55% expect to hire more experience developers.
This presages increasingly ferocious competition for scarce talent in Asia Pacific. Many enterprises already plan to address this with greater upskilling efforts, particularly in areas like data science and AI configuration which represent crucial foundations for AI adoption. Enterprise leaders should similarly consider how AI itself can help to scale AI engineering and adoption processes by creating more productive and automated experiences for existing talent.
The Index’s findings suggest Asia Pacific leaders should start by centralising technology and data on a single platform, simultaneously combating solution sprawl and laying strong foundations for productive AI development. They would also do well to extend AI across use cases in multiple business units under a clear and consistent vision, particularly in tackling acute issues faced in HR and talent development.
“The reality is that AI offers organisations a competitive advantage, an attainable way to connect people, processes and technologies across the enterprise –- but it needs to be done in an integrated approach," says Chris Bedi, Chief Customer Officer at ServiceNow. "Enterprises need to lay the groundwork today to be an AI-connected enterprise tomorrow."
Achieving business objectives in such areas will likely take longer than the quick wins experienced with AI to date. Leaders should finally prepare themselves and their stakeholders to exercise patience and constantly check their focus on priorities for the business – not just AI for its own sake.
Find out more about what Asia Pacific leaders can do to accelerate AI maturity in our latest Executive Circle feature.