APAC Takes a Different Route to AI Leadership

When it comes to AI, the Asia Pacific region is not a follower.

That much was clear when Cognizant released a thought leadership ebook that examined the results of a global survey conducted together with ESI Thoughtlab.

Based on the conclusions, Jeff Olson, associate vice president for projects, artificial intelligence & analytics practice, digital business & technology at Cognizant, believes Asia Pacific is now at a “tipping point” for AI.

In turn, this is creating a wellspring of AI optimism across the Asia Pacific and having a positive knock-on effect on AI maturity. The ebook, titled “Getting Ahead With AI: How APAC Companies Replicate Success by Remaining Focused,” which Olson co-authored, highlighted that around 45% of Asia Pacific respondents now view themselves as leaders.

In some ways, the region may already be leading the AI charge with their substantial investment appetites. “The difference between the Asia Pacific and the rest of the world is in terms of AI investment. [Asia Pacific companies] expect to spend more money on AI over the next three years. In this regard, the region is the undisputed leader on setting money aside for investment in AI technologies to transform their business,” observes Olson.

Why APAC AI journey is different

Asia Pacific companies are not just spending more on AI; they are also looking at different AI categories.

The Cognizant ebook noted that regional companies are more interested in machine learning, while their North American counterparts focus more on digital assistants and robotic process automation (RPA).

One reason could be the low labor costs. Another reason is the laser focus that regional governments have as they outcompete each other for AI talent and investment. Following the continuous trail of news articles from China to Singapore and India shows how much public money is being spent on ambitious AI initiatives that tout deep-pocketed perks. 

Regulations (or the lack of ones) are also shaping the regional AI landscape. For example, China, which has the second greatest number of AI leaders behind Japan, has lax privacy regulations, allowing Chinese businesses to access large data pools to train their AI algorithms.

However, when you dive into numbers at the corporate level, adoption is still at an early stage, with 55% considering themselves as beginners or implementers. Still, 71% of surveyed companies view AI as “an essential ingredient for good business,” says Olson.

The size of AI projects and how Asia Pacific companies are driving them are also different. Olson observes that regional AI projects tend to be smaller ones focused on customer intelligence or customer experience.

In comparison, AI projects in North America and other parts of the world are “more encompassing,” adds Olson. The larger size makes it a complex exercise, and companies may not immediately see the business value.

The smaller size allows the companies to drive these faster and learn from them quickly while highlighting its value to its stakeholders and FOMO among their competitors. It is why Olson thinks that “the region is right on the edge of a genuine AI explosion.”

WATCH Jeff Olson on how APAC AI leaders are different.

Deconstructing the Asia Pacific AI leader

This is overall good news for the region and may even allow Asian-led themes to dominate global AI development. But Asia Pacific AI adoption is not homogenous with AI leaders and laggards. Unlike other regions, the chasm that separates AI leaders from laggards is enormous.

The reasons are pretty simple. Olson explains that many AI leaders in the Asia Pacific “have developed a broad-based business view of the value of the technology.” In other words, these companies are looking to use AI to change their business; not just run their business faster or better.

Another reason is that AI leaders are not afraid to tackle the complex strategic questions right up front, creating policies around data management, ethics, and governance. It offers them a framework “within which AI and machine learning can be applied to the business that allows them to change,” says Olson.

AI laggards, meanwhile, see AI as a tech project and only develop the frameworks later. It hampers them in adoption and when scaling these PoCs into companywide initiatives.

For example, an AI leader would have tackled data privacy right at the beginning using the framework they built. Data privacy could stall the AI projects or require them to recalibrate and restart for AI laggards who often lack such frameworks.

One area where AI leaders stand apart is their focus on monetization. “The non-leaders tend to be more focused on cost control and operational improvements,” explains Olsen.

WATCH Jeff Olson explain what sets AI leaders apart.

A bumpy road ahead

While the ebook shows that Asia Pacific AI adopters are becoming world leaders, it will not be a smooth ride.

Firstly, countries now see AI as a nationalistic pride. It can create new barriers to adoption, like what we see with the deployment of 5G equipment. New regulations and export controls of such technologies will make the picture murkier in the Asia Pacific. It will be interesting to see how major economic blocs in the region will address these issues.

Data privacy laws and data sovereignty will provide significant roadblocks. The simple truth is that AI algorithms need to ingest copious amounts of data to become worthwhile models. Having a slice of the regional data can only restrict the use case and even introduce bias.

While low labor costs may have allowed Asia Pacific companies to focus on revenue optimization, it will not last. It is because of the second frontline where the AI war is being waged: talent.

It is also an area where many companies get it wrong, says Olson. Many companies tend to see AI talent crunch as one where technical talent is scarce. But the real shortage lies in the business application of AI.

“A large part of the focus on talent for AI today has been getting the people who are strong in mathematics, AI, and technologies that support AI. But where you make your money out of AI projects is when you apply them to your business. And that requires a deep business understanding,” Olson argues. 

This is an issue that AI leaders tend to catch on quickly, ensuring that their technical talent works closely with their business domain experts. “But for many, that's where I think the crunch is coming,” adds Olson.

WATCH Jeff Olson highlight the reasons AI in APAC is promising.

The hard truth about AI

In the ebook, Cognizant offers four approaches to address these challenges. They include starting small and leaving nothing untouched, balancing humans and machines, exploring new value models, and looking at data modernization as a continuous loop.

Olson also suggests companies set up centers of excellence (CoEs). These can provide expertise to the different business units or project teams looking at AI, offer oversight, and build stronger partnerships with businesses.

It does not mean that every AI leader needs a CoE, nor having one means you are assured of success. But it does offer necessary guardrails and drives business collaboration that AI projects need. It is also an area that Cognizant works closely with its customers.

Whatever the approach, it is clear that Asia Pacific companies have no time to bask in the glory of their AI leadership. The AI wars are being fought on many fronts, with governments working together to shape the outcomes. Sitting idle is no longer an option.

It is also clear that companies need to be prepared for the hidden truth about AI: “AI's ability to look at large quantities of data in very small detail is really paying off big for Asia Pacific companies. But it can also fundamentally change the business and the way people work,” says Olson.

It is a truth that today’s AI leaders across the globe understand very well.

Winston Thomas is the editor-in-chief of CDOTrends and HR&DigitalTrends. He is always curious about all things digital, including new digital business models, the widening impact of AI/ML, unproven singularity theories, proven data science success stories, lurking cybersecurity dangers, and reimagining the digital experience. You can reach him at [email protected].

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