Most organisations in Asia Pacific feel that AI has yet to break out of awkward adolescence. Our inaugural Enterprise AI Index has found that only 1 in 10 enterprises consider themselves very mature when it comes to AI adoption.
Yet in India and Australia, a third of enterprises are seeing returns of more than 15% on their AI investments in terms of increased efficiency and productivity, while as many as 30% have grown their revenues by more than 15% through AI adoption. More broadly, Asia Pacific enterprises are more likely to be operationalising AI – making it a part of everyday work – than their peers elsewhere in the world. The region has begun a quiet growth spurt in AI adoption, driven by a core group of “pace-setters” that are successfully embedding AI into the fabric of their businesses to benefit people and profits alike.
How are these pace-setters already achieving so much with AI? And what gaps must leaders plug to start and sustain their own organisational growth spurts?
The answer to both questions starts with who is using AI. Our research found that in most of Asia Pacific’s major markets, the CEO’s Office is more likely to be significantly using AI than in other parts of the world. In other words, C-level leaders in APAC are increasingly applying AI to their own roles and responsibilities – which seems to correlate with faster operationalisation and even ROI organisation-wide.
In other words, leaders who are actively involved in AI’s technology and talent decisions will likely gain maturity with AI much faster than those who just leave it to their lines of business or employees. It also means they must take increasing care to direct their influence in the right direction.
Most leaders will understandably want to start by examining decisions on technology investment. Here, we see two trends: to adopt organisation-wide AI platforms or build and own AI capabilities in-house, recognising the need for consistent and well-integrated solutions that align with real business problems (instead of “AI for its own sake”). Yet this apparent strength may be increasingly compromised by “solution sprawl”: enterprises across the region are more likely to be acquiring AI from a mixture of new and incumbent vendors, than in other parts of the world. The more vendors, the more competing systems and ideologies – and the higher the probability of reinforcing siloed systems and data fragmentation that can scupper AI initiatives before they even launch. It is no coincidence that markets with higher incidence of solution sprawl are also less likely to achieve the highest levels of ROI from their AI investments. Enterprises in such markets are more likely to have too much unstructured data, too many different tools, and not enough time to make sure they work.
Despite high levels of AI adoption in the CEO’s Office, Singapore enterprises are far less likely to say they have achieved substantial returns on investment. And while AI has ignited relatively large and widespread increases to innovation speed in other Asian markets, 13% of Singapore enterprises believe they have experienced a slowdown in innovation because of their investments in AI. Could solution sprawl be the culprit?
Apart from providing a clear enterprise-wide vision for AI, leaders will do well to consider how they assess its impact. That starts with taking a one-platform approach to consolidating data, applications, and systems for higher-quality AI models and more measurable outcomes to customers and their people alike. It is worth noting that in APAC markets with more AI pace-setters, leaders are significantly more likely to consider AI’s impact on employee experience as important. This makes sense: employees will only love their experience with AI if it helps them do their best work easier.
C-level adoption of AI has yet to flow down into how enterprises develop both talent and their skills. HR teams in Asia Pacific are less likely than the rest of the world to be significantly using AI. The adoption of AI for hiring lags any other internal use case we surveyed in almost every part of the region apart from New Zealand (where 40% of enterprises are already doing so). This is creating gaps in enterprise HR capacity which will only grow as AI adds net demand for jobs to most major economies in the region.
Leaders can start to close these gaps by recognising that AI is at its core about people – helping them deliver better results in more productive and creative ways. Practically, this means involving the CHRO in all AI decisions, not just those specifically in HR’s historic remit. This will help enterprises leverage their existing strengths in employee training and support around AI even further; and position them well to close another gap: skills.
Without the right skills in place, Asia Pacific enterprises will eventually hit a growth ceiling with their AI maturity. Every market we surveyed is struggling with access to AI engineers who are critical to the technology’s adoption. In a world where in-demand skills are increasingly scarce, expensive, and subject to change – leaders need to upgrade their tools for upskilling.
Aptly, this is where a platform approach to AI can play a role. ServiceNow’s Now Assist can act as helpers, taking on low-grade and time-consuming tasks so that employees can apply their most valuable skills more often in their roles. Some can act as tutors: using operational data to assess employee performance and offer guidance on where individuals can improve or develop their skills in new directions. And some can act as matchmakers, dynamically aligning employees’ career aspirations with organisational skills gaps as both evolve over time.
All these function as part of a seamless whole that helps scale and amplify the work of existing engineers – supporting development, deployment, and even demos for different personas within the organisation. Even with endemic skills shortages, putting AI to work – and equipping existing talent to do so better – becomes a much less painful process.
As leaders plug business gaps with AI, they will inevitably discover new ones in other areas that require attention. The process of maturing is continuous – but it is not always arduous. In some cases, we have seen Asia Pacific leaders devise comprehensive strategies for improving AI maturity within less than an hour of coming together and level-headedly identifying gaps and using strengths to target them. Such strategies make ample use of centralised capabilities and platforms to ensure continuity across business units, processes, and time.
Leaders wield huge influence over how quickly their enterprises climb the AI maturity curve – perhaps more than even they are aware of. The sooner they recognise their influence and apply it with an organisation-wide perspective, the faster AI will progress from its adolescence into adulthood.