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Cognizant Report Highlights AI Progress in Asia Pacific, But More Work Needed
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September 3, 2021 News

 

Written by: Martin Dale Bolima, Journalist, AOPG

Companies worldwide, including those in the Asia Pacific region, are making significant progress towards Artificial Intelligence (AI) adoption. This is among the key findings outlined in the report “Getting Ahead With AI: How APAC Companies Replicate Success by Remaining Focused” recently released by leading digital solutions provider Cognizant.  The study, completed in collaboration with ESI ThoughtLab, surveyed 1,200 senior executives globally, including 370 from Asia Pacific, to find out how organisations are deploying AI amidst the uncertainties of today.

The Asia Pacific region, in particular, is seeing both an uptick in AI deployment and growing belief in the technology, with 71% of the respondents highlighting AI as “an essential ingredient in business success,” and 45% claiming to be either leaders or advancers in the use of said technology. Both, according to Cognizant’s report, suggest the high likelihood of AI adoption continuing in the region in the years ahead.

“As a region, APAC is moving in the right direction. AI projects in APAC tend to be smaller and more discrete than those in other regions, enabling organisations to quickly see a return on investment,” said Newton Smith, Vice President of Digital Business and Technology at Cognizant, in an email interview with Disruptive Tech Asean. “This approach has helped APAC businesses gain comfort and competency with maturing AI toolsets and replicate success across the organisation.”

Still Lots of Room for Improvement

The region’s AI utilisation, however, is still far behind in comparison to Western countries, particularly in the Americas, where businesses are using AI for larger-scale engagements. In the Asia Pacific, on the other hand, AI-related projects are relatively small and more discrete but it is a setup that is enabling organisations to both reap the advantages of AI much faster and gain comfort in terms of how to best maximise the technology. Among these advantages are increased productivity, improved customer satisfaction and enhanced employee engagements.

But while that approach has been advantageous, organisations in the region will have to start levelling up their use of AI as soon as possible, especially given the “wide disparity between AI leaders and laggards,” in terms of adopting critical underlying technologies necessary for AI deployment. Two of these are data management, which has been implemented by 95% of AI leaders and only 23% of non-leaders, and machine-learning, which has been deployed by 83% of leaders and just 5% of non-leaders.

“With modest accomplishments under their belts, the time is right for leading organisations to shift gears to [a] higher value, enterprise-wide projects that could potentially change the competitive landscape by delivering new products or services and ways of working,” said Smith. “Naturally, there are challenges. In the aftermath of the COVID-19 pandemic, data modernisation has emerged as one, as businesses come to realise their data & analytics models are highly perishable. APAC businesses are acutely aware of this and plan to diversify their sources of data over the next three years.”

To date, only 17% of businesses in the Asia Pacific region are leaders, or at the highest stage of AI maturity, while 28% are advancers, or are using the technology in key parts of the business and reaping the benefits. On the other hand, 31% are already implementers or are starting to pilot AI use in a few simple applications, while 21% are beginners, or are at the planning stages of AI adoption and building internal support for it. These figures underpin both the progress being made in the region when it comes to AI adoption and the work that still needs to be done to make AI utilisation grow even more in the Asia Pacific.

Critically, organisations lagging behind in terms of AI deployment will need to find the right approach if they are to find the right AI technologies that will yield the most benefits.

“Business leaders need to realise that these tools must be implemented in the right processes to help solve the right challenges. To do so, they can start by implementing a roadmap for automating processes across the enterprise, or in some cases, to integrate isolated processes,” said Smith in explaining what implementers and beginners must do in their respective AI journeys.

Smith added, “Companies ought to kick off with pilots, working closely with business teams to identify use cases and demonstrate their value through pilots. It is important to identify multiple use cases since some AI initiatives will fail. This allows businesses to learn from past mistakes and make them aware of potential challenges that may arise when scaling projects across the organisation.”

Addressing Challenges Related to AI

Organisations will also need to address the talent gap that AI is creating, which is one of the pressing issues hindering the technology’s deployment in the region. Many companies, though, are doing so already using a three-pronged approach of upskilling, partnerships and out-tasking. More progressive countries, on the other hand, like Japan and Singapore, are growing talent internally, working with academic institutions and government policymakers to enhance STEM programmes that would ultimately help organisations bridge said talent gap when it comes to AI.

“On the topic of talent, AI will continue to test [a] businesses’ ability to retrain existing employees while attracting and retaining fresh AI talent in the near future,” said Smith. “AI requires businesses to master a broad set of technologies, and reinventing traditional businesses through AI, requires new skill sets in areas such as machine-learning security and data.”

In addition, concerns about job loss and compromised privacy need to be eased. Smith, though, dismissed both as “overblown”, noting how AI “is expected to create new jobs over the next 10 years even as repetitive tasks are automated.” These jobs, Smith explained, “will be built around data and how it can be deployed to create new experiences,” making it imperative for businesses to “create a new organisational mindset because without one they risk losing their ability to compete.”

Other challenges APAC organisations are facing in terms of AI adoption include project management, managing AI risks and ethics, regulatory constraints, lack of IT infrastructure, uncertain return on investment and embedding AI in daily tasks. These issues are the reason AI adoption is still lagging in the region despite the considerable headway already being made.

Making AI Part of the Business Strategy

While there are still many challenges to overcome, the Cognizant report is nonetheless forecasting a robust future for AI in APAC, especially if organisations in the implementer and beginner stages follow this four-step approach:

  1. Start small but leave nothing untouched.
  2. Strike a happy balance between man and machine.
  3. Explore new value models.
  4. Keep data modernisation in a continuous loop.

Smith also recommends making AI part of the organisation’s overall business strategy for digital transformation. This means, according to Smith, “incorporating key business metrics to ensure that AI helps the organisation maintain an unwavering focus on business outcomes.”

“Businesses should not try to get ahead of themselves when it comes to deploying AI tools,” Smith added. “Achieving AI maturity involves moving along the maturity curve iteratively, adopting the necessary tools and creating new algorithms. The best options will always be defined by where organisations find themselves on the digital maturity curve.”

Lastly, Smith is enjoining organisations to rely on external partnerships “to bring in [the] necessary technology, talent and expertise,” that will ensure the progress of AI deployment. “Many AI efforts get bogged down in lengthy technology procurement processes,” noted Smith. “Businesses need to be sure they have an open cloud environment to experiment with machine data. If possible, they can look at creating a robust set of partnerships that provide access to continuously advancing AI technologies.”

Indeed, much work is still needed to ensure the continued progress of AI in APAC. But the future looks bright and the region seems poised to become a leader in AI deployment in the coming years.

To download the report “Getting Ahead With AI: How APAC Companies Replicate Success by Remaining Focused” by Cognizant and ESI ThoughtLab, click here.

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