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RPA the gateway to AI adoption in Asian businesses

It seems like every business these days is talking about artificial intelligence (AI), but how many of them are actually adopting AI solutions and technology?


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Published by Questex Asia
on 13 May 2019

RPA the gateway to AI adoption in Asian businesses

It seems like every business these days is talking about artificial intelligence (AI), but how many of them are actually adopting AI solutions and technology?

Where AI is being used in Asia, it’s being done to good effect.

For example, in financial services, it’s helping with real-time fraud detection across trillions of dollars’ worth of transactions.

In healthcare, AI is saving lives by helping doctors review patient records and medical tests more accurately and efficiently for specific symptoms, such as lung cancer in radiology scans.

But for many businesses in the region, AI is generally seen as a rather sophisticated and complex undertaking.

How could they get started to leverage the power of AI in this age of digital transformation? To find out, Enterprise Innovation spoke to Malina Platon, Managing Director, ASEAN, UiPath.

 

What are the key obstacles to AI adoption among businesses in Asia?

Platon: If you look at recent data, the numbers of businesses adopting AI are disappointingly low, with some surveys pointing to as little as 41% of businesses in Asia Pacific having adopted the technology. This is surprising, considering the well-known benefits of AI, from increased innovation to higher employee productivity.

The main reason we’ve identified is that business owners and key decision makers simply don’t know where to start with AI. That’s why we see robotic process automation (RPA) as a big opportunity to get some low-level automation running in companies – it’s simple and doesn’t require big investment in terms of time and dollars. It provides the building blocks for an eventual AI strategy that is more substantial, and helps the business get familiar with the basic ideas and what it can look like in practice.

This often starts by automating repetitive tasks that humans don’t really add any value to. The RPA software can run in the background 24/7, following if-this-then-that rules-based algorithms that help to automate back-end processes. It frees human workers to engage in higher-value tasks where they are more needed, especially in client-facing roles where admin can distract from servicing clients.

So, I would say the key obstacle is a lack of knowledge and general bewilderment about how to take baby steps to get the ball rolling on their AI journeys, often as part of a larger digital transformation initiative. Many business owners and decision makers don’t even realize RPA and AI are connected, and why it makes sense to start with one to get to the other. There are, of course, other obstacles to AI adoption among business in Asia.

Other notable obstacles include lack of skilled people at the company who can implement AI-related technology and work alongside it, data and other computer resource-related challenges, a company culture that does not recognize a need for AI, and unclear business use cases (usually because the decision makers do not understand the applications of RPA and AI).

How does RPA make sense as an entry-level strategy for organizations in Asia to embark on AI, and as part of their larger digital transformation initiatives?

Platon: RPA is the right way for most businesses in Asia to embark on an entry-level strategy for AI adoption. McKinsey predicts that AI can create a global annual profit in the range of $3.5 trillion to $5.8 trillion across the nine business functions and 19 industries studied in their research.

Despite the tremendous potential of AI, the study also notes that only a few pioneering firms have adopted AI at scale. The last few years have seen a surge in RPA due to its ability to rapidly drive the automation of business processes without disrupting existing enterprise applications. Deeper levels of AI adoption, however, have not been so widespread.

One of the challenges is that most AI applications today are focused on narrowly defined tasks, such as predicting machine failure rates, text analytics for sentiment detection, or facial image recognition. We haven’t yet reached an Artificial General Intelligence (AGI) that can do lots of different tasks as well as humans.

RPA automates basic back-end tasks well, and while we are waiting for AI technology to catch up and become more widespread and affordable, RPA still represents the best place for most businesses to start when it comes to automated back-end processes and low-value tasks. As part of a wider digital transformation initiative, RPA is now effective enough to take the front and center stage.

How could this be done, starting from automation of back-end systems and processes, and what are some best practices to make it a low-risk approach for c-suites looking to lay the foundations of their organizations' AI journeys?

Platon: It starts with educating business owners and the C-suite on the opportunities, but also the challenges, of implementing RPA and low-level automation into their overall operations. As they say, knowing is half the battle. So, let’s first look at how it can be done and some examples of areas it can be applied to.

·         First, in compliance: RPA removes data gaps between disparate sources and logs all actions completed by the software robots throughout automation. This allows employees to proactively recognize and manage any compliance issues and consistently run internal reviews.
 

·         Second is the need to highlight the non-invasive nature of RPA: companies do not need to make changes to existing legacy systems when implementing RPA. This is beneficial because it allows organizations to implement RPA in a non-interruptive way, which makes RPA unique among other types of automation. I also find this is sometimes the most misunderstood aspect of RPA: business owners and the c-suite think they need to throw out all their existing legacy systems when they don’t.
 

·         Third, through its automation capabilities, RPA allows organizations to deliver higher quality services to their customers in a timely manner with increased levels of human interaction.

When it comes to best practices for implementing any RPA strategy, there are some key considerations to keep in mind.

·         First, it’s important to reduce employee resistance in the onboarding phase. Frequent communication from company leaders and executive sponsors to ensure employees are fully informed about what is expected of them throughout the implementation process is essential to successful adoption.
 

·         Second, it’s important to identify the right processes to be automated, which means understanding which ones require human judgement and which ones can be safely left to software robots. RPA are ideal for tasks that are repetitive, rules-based, and high volume. This can include activities such as data migration and copy-paste tasks. RPA implementation is especially difficult though with business processes that are non-standardized and require frequent human intervention in order to execute. Typically, these more complex tasks include interacting with customers and developing human relationships.
 

·         Third, RPA shouldn’t be seen as a silver bullet to all your organization’s challenges – so set realistic expectations around its implementation strategy and expected results. Yes, RPA can achieve a lot and deliver substantial cost savings and efficiency gains for a business, but only if implemented well and with all the above in mind. The RPA approach of each business should be tailored to its specific needs.

Please share some scenarios and/or use cases from specific industry applications, and the benefits yielded so far.

Platon: We have had great success in Asia, whether that’s our partnership with KPMG Thailand or our work with some of the region’s largest corporates. Let me give you one example that I think really illustrates the benefits, in terms of cost-savings and efficiency gains, that can be achieved when RPA is implemented at scale.

In 2017, one of Japan’s leading financial institutions, Sumitomo Mitsui Financial Group (SMFG) and Sumitomo Mitsui Banking Corporation (SMBC) launched an important initiative aimed at increasing the productivity and efficiency of their operations. Looking at the newest technologies that could help deliver on these goals, they selected UiPath’s RPA technology as a critical transformation lever.

Having every intention to turn automation into an important part of the organization’s future, the group established a Productivity Management Department to take on this ambitious plan which currently projects cost reductions of $450 million by 2020 and nearly $1 billion in the medium-term. As you can see, the benefits of RPA far exceed the investment, which is often made back in a matter of months (it can be in as little as the first three months).

 

This article was first published on Questex Asia Ltd, on 30 April 2019. Information is correct at the time of publication.

Last Modified Date: 11 Jun 2019