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Leveraging AI to drive post-pandemic business recovery

Nurdianah Md Nur
Nurdianah Md Nur3/3/2022 5:15 PM GMT+08  • 5 min read
Leveraging AI to drive post-pandemic business recovery
How can AI help organisations be more efficient and agile even in the face of uncertainties and talent shortage?
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Becoming an efficient, insights-driven and agile organisation is the goal for most, if not all, businesses as they look to thrive in the post-Covid world. This is why companies in Asia Pacific are increasing their tech investment, with market research firm Forrester predicting that tech spending in the region to grow by 6.2% this year.

One technology that has gained significant interest is artificial intelligence (AI). Many financial services institutions, for instance, are exploring the use of AI to improve their operations.

“AI solutions [have the ability to] transform many aspects of insurance including underwriting, customer service, claims, marketing and fraud detection. However, a recently published Temasek survey reveals that only 13% of businesses in global banking and insurance currently use AI across the bulk of their processes,” says Cassandra Wee, head of insurance at SingSaver, a personal finance comparison site.

She continues: “With significant untapped potential, [financial services institutions] that adopt AI responsibly and rapidly will have the upper hand, especially because there are strong benefits across the entire value chain. This goes a long way in helping reduce costs, increase sales and improve customer service.”

Gaining agility and resilience

See also: Scaling up Asia's infrastructure to drive up sustainability agenda

AI will play a crucial role in managing the post-pandemic workforce for other industries too. “The ability to translate large volumes of data into actionable insights is [no doubt] critical to business success for any organisation,” states Sandeep Sharma, president for Asia at Workday, a provider of enterprise cloud applications for finance, HR, and planning solutions.

“[With AI,] organisations can make smarter, data-driven decisions and build their operational agility and resilience through uncertain times – particularly as plan-execute-analyse cycles become shorter,” he adds.

For business leaders, AI can help enable agile decision-making that connects people, technology and data so that the company can deliver beyond market and customer expectations. “AI allows leaders to experiment in real-time and act confidently when change occurs, instead of relying heavily on static long-term plans,” says Karen Clarke, managing director for Americas at Anaplan, a business planning software firm.

She explains: “[By incorporating AI into scenario planning platforms], organisations can fine-tune forecasts and determine the most urgent business needs, access the economic landscape and decipher how business growth looks three to five years from now. Scenario-based thinking will enable robust recalibration capabilities for companies to declutter old planning processes and remain cost-efficient while doing so.”

See also: Insurance enters a new age

AI-driven automation

As companies accelerate their digital transformation efforts for the post-pandemic, they must also ensure they have the right digital skills to support those efforts. However, Asia Pacific is facing a digital skills shortage. Case in point: Consulting firm Korn Ferry estimates that the region will face a shortage of 47 million tech talent by 2030. A survey by professional services firm PwC also revealed that more than half of Asia Pacific chief executives found it difficult to hire digital talent with the right skills.

Automation technologies, such as robotic process automation (RPA), enriched by AI can help address the growing concerns of skills shortage.

“Automation [should not be] a siloed strategy used primarily to increase efficiency; it can also help address talent woes. We can expect to see RPA increasingly support multiple forms of AI capabilities from software to hardware while working to seamlessly connect human, digital robot and enterprise systems this year,” says Vincent Gao, founder and CEO of Cyclone Robotics, an RPA solutions provider.

Andy Ng, vice president and managing director for Asia South and Pacific region at data management firm Veritas Technologies, shares the same view. He says: “To reduce business complexity and improve productivity, businesses will turn to AI-based process automation to eliminate tedious tasks, enabling workers to focus on higher-value work.

“Done right, automation has the potential to unleash new business and operating models by defining a framework for digital workers to utilise AI-based automation for innovation.”

Designed to enhance productivity, RPA automates repetitive tasks to streamline business procedures. Meanwhile, AI is the simulation of human intellect by machines. Combining the two technologies can empower organisations to automate more sophisticated, end-to-end processes, as well as incorporate predictive modelling and insights into those procedures to help people to work smarter and quicker.

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For instance, RPA solutions leveraging AI can help banks and credit card firms analyse massive volumes of transactional data to identify suspicious behaviour. Those organisations are therefore able to detect fraud cases more accurately and reduce investigation time.

The need for a data-first modernisation strategy

Realising the value of AI calls for organisations to embrace a data-first modernisation strategy, according to Narinder Kapoor, senior vice president and managing director for APAC at Hewlett Packard Enterprise (HPE).

He notes that in many organisations, data remains in disarray and spread across legacy IT systems and multi silos. This data sprawl can prevent AI from using all of the organisation’s data to “learn” and be truly effective.

According to HPE, organisations should adopt these key principles to adopt a data-first modernisation approach:

  • Data is a core asset and a strategic part of business goals, so it should be controlled by the enterprise, not a public cloud vendor.
  • Essential data is everywhere and must be accessible at digital speed from its native location — be it at the edge, in data centres, or in applications that have moved to the cloud.
  • Data has rights and sovereignty, requiring governance policies for security, privacy, and access.
  • The public cloud is not the de facto platform, especially for industries or applications operating under strict regulatory requirements.
  • A unified view of data from the edge to cloud and a single operational model will drive better performance and superior user experience.

With uncertainties and rapid changes abound, businesses in Asia Pacific should use AI to enhance workflows for improved productivity and gain the ability to be insights-driven to remain adaptable. By doing so, they can also help speed up the region’s economic recovery.

Photo: Unsplash

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