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Asia: Becoming a Powerhouse through AI Adoption

Engati Team
last edited on
October 17, 2023
7-8 mins

Table of contents

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AI adoption in AI

There has been a rapid increase in the adoption and development of artificial intelligence across the globe. Business platforms are depending on AI for better growth, efficiency, and digital transformation. Cutting-edge technologies like 5G will escalate the use cases of AI across industries. According to McKinsey Global Survey 2020, 50% of respondents reported that their companies have adopted AI in at least one business function.

The global leaders in AI adoption, research, and development include Asian countries like China, Singapore, and Japan. A Channel Asia report says, “Certainly, Asia Pacific is expected to emerge as a major market for AI-led initiatives since most countries in the region are establishing committees or task forces for creating national AI strategies, which have either been launched or are on the course of being launched in the next few years.”

The adoption of AI: a trend in Asian Markets

Japan and China leading the Growth

The World Intellectual Property Organization report revealed that Japanese and American companies hold the highest AI patent portfolios, and Chinese research organizations make up 17 of the top 20 academic players in AI patenting and 11 of the top 20 in AI-related scientific publications.

Japanese vision known as Society 5.0 aims to leverage strategic innovations and technology to enhance human life and work towards a smart society. Supportive policies and investment from public and private sectors aid this AI boom in Asian countries like Japan. China and Japan are among the largest suppliers of industrial robots and they are commercializing the research domains for AI. The huge market of China is susceptible to rapid changes and hence can accommodate new innovations in AI without disturbing the economy.

According to a Harvard Business Review report, China has passed a number of policies in recent years to promote the development of AI, including ‘Made in China 2025,’ ‘Action Outline for Promoting the Development of Big Data,’ and ‘Next Generation Artificial Intelligence Development Plan.’ Strong government policies can attract more investors into the technology market since they are regulated and protected.


According to a global study by PwC India, the highest increase in use of artificial intelligence (AI) during COVID-19 times has been witnessed in India. The study also showed that 94 per cent of the over 200 chief executives in India surveyed said they've either adopted or are planning to implement AI in their companies. While the survey for India was conducted between August and September, globally it was conducted among 670 high ranking officials in September-October.

India witnessed the highest increase in AI use compared to major economies like Britain, Japan and the US, with over 70 per cent of Indian organisations having implemented AI in some functional areas in 2020 as compared to around 62 per cent last year. Also, over 90 per cent companies are implementing or planning to invest in AI solutions to address current business concerns, the survey said.

According to the survey, AI adoption in India was led by the travel and hospitality sector with 89 per cent of the surveyed firms doing so, followed by telecom, media & technology firms (86 per cent), financial services (82 per cent), and 73 per cent of healthcare and pharma companies adopting it during the year. AI is deployed across business functions like customer service, finance and tax, HR, IT and cyber security, manufacturing and operations, R&D, risk, legal and compliance, sales and marketing, supply chain and logistics, among others.

The survey also shows that optimism with regard to AI in reducing cost and maximising revenue has gone up significantly from 72 per cent to 92 per cent in India , and 45 per cent of organisations have increased the use of AI since the pandemic hit them. Further, 94 per cent of the respondents have either implemented or are planning to implement AI in their organisations.

AI is now regarded as a key enabler for organisations to emerge from the present crisis, plan for transformation and making fundamental changes to the operating model for lasting competitive advantage, said Sudipta Ghosh, a partner and leader for data and analytics at PwC India. To get the best out of AI, businesses need to start viewing it as a necessity rather than a luxury and weave it into the organisational fabric, he added.

However, companies also find adopting AI difficult and fail to realise the optimum value from their AI investments. For instance, 37 per cent of them find it challenging to identify the right use cases for AI and 28 per cent lack high-quality data for use in AI solutions, the survey said.

Chatbots, eCommerce, ASEAN markets

According to an article by Rene Millman titled, ‘Adoption of AI booming in Southeast Asia,’ the adoption rate of AI in the region grew to 14 percent in 2018. The article, citing an IDC report titled, ‘Asia Pacific Enterprise Cognitive/AI Survey,’ revealed that 37 percent of companies would put AI adoption plans in place in the next five years. Last November, Singapore launched its National Artificial Intelligence Strategy and committed over SGD500 million (US$370 million) to fund activities related to AI under the Research, Innovation and Enterprise 2020 Plan.

Across the region, AI technology is primarily driven by improved business insight, the sheer volume of accessible data, easy availability of computational power and storage, new algorithms and a community mindset ready to embrace AI. The IDC report also found that the most significant barriers to AI adoption in the region are lack of skills and knowledge (23 percent) and the high cost of solutions (23 percent). 

Natural Language 

A chatbot is a domain-specific conversational interface that uses a messaging platform, social network or chat solution for its conversations. Chatbots help online sellers deal with customer requests more efficiently by automating parts of the interaction. Chatbots can come in a simple form, where keywords are scanned from customers’ inquiries to deliver pre-packaged answers, while more sophisticated chatbots are powered by AI and machine learning (ML). 

AI chatbots can use natural language processing to create responses and conversations and actively learn from conversations they have with customers. Kata, an Indonesian start-up, uses natural language processing to power their chatbots that speak and understand the Indonesian language to improve customer engagement.

By 2020, 25 percent of customer service and support operations will integrate chatbot technology, according to Gene Alvarez, managing vice president at Gartner, a research and advisory company. He said that chatbots “should enrich the customer experience, help the customer throughout the interaction and process transactions on behalf of the customer.”


Shopping Experiences

Besides the 24 hours a day, seven days a week availability that chatbots can provide, there are other benefits of using chatbots in e-commerce businesses.

Chatbots can reduce the manual labour cost of a customer service team as they require less personal support while giving efficient customer assistance. 

Chatbots also collect data to understand the needs and preferences of customers, allowing online retailers to personalise product pages and build customer loyalty. Retail giant H&M’s chatbot asks customers some questions about their style and offers products accordingly. With this, customers can easily navigate through the brand’s massive catalogue of products. 

AI chatbots also enable retailers to increase both, the number of customers and the average amount they spend by creating personal and convenient shopping experiences. Unfortunately, customers are impatient, based on research from HubSpot’s ‘Consumer customer support survey’. The report found that a customer’s patience wears out after 10 minutes, with 90 percent of respondents saying that an ‘immediate’ response is essential when they have a customer service question. Deeply integrating AI into chatbots can quickly provide accurate answers to customers.

However, businesses must also know when to refer questions to a human. Although chatbots can hold conversations just as fluently as humans, there will be some questions a chatbot may not have an answer to.

How to adapt to AI?


In our experience, having worked with countless organisations on their AI and digital transformation strategies, there are barriers to successful adoption that we see time and time again. Here are the essential elements businesses must have in order to overcome the obstacles standing in the way of leveraging AI to its full potential.

1. Access to the right data

Make no mistake – good data fuels good AI. Trained on the right data, machine-learning algorithms can do amazing things, such as see (machine vision), read (natural language processing), speak (natural language generation), walk (autonomous robots), act creatively (generative design), and much more. However, while businesses have access to more data than ever before – both internal and external – that data often isn’t ready to feed AI applications.

There are often issues around data integrity and complexity, siloes, metadata, information architecture and so on. To address these challenges, businesses need to approach them strategically and foster a culture where data assets are valued, defined, mapped, classified and well-governed.

So, to lean into AI, good data is a must, just as a map application needs good data to plan the best route. Any path on the map needs to consider all possible routes, travel preferences, waypoints, real-time traffic, roadwork data etc. If any of these factors are missing, out of date or incorrect, the outcome is bound to be less than perfect. Similarly, if the data you put into your AI algorithm is incomplete, inaccurate, inappropriate, or out of date, then AI will never achieve its potential.

2. Identify the Problems You Want AI to Solve

Once you're up to speed on the basics, the next step for any business is to begin exploring different ideas. Think about how you can add AI capabilities to your existing products and services. More importantly, your company should have in mind specific use cases in which AI could solve business problems or provide demonstrable value.

3. The right technology

The uses of AI are diverse – from “ask-me-anything” chatbots to machine learning that predicts propensity of a shopper to buy. This means that AI can and should be delivered in different ways, using the right data, processes and technology. For instance, many AI algorithms have to ingest real-time data from event streams and processes, which requires a modern technology stack. For some projects, you can get an off-the-shelf “as a service” algorithm, while other projects require teams to craft unique machine learning approaches.

Getting the technology right can be a challenge, particularly for established businesses that have invested heavily in platforms a decade ago and are now struggling to bring their legacy system into the AI age. AI often requires an update to the technology used to collect, store and process data. Digitally native companies often have a huge advantage here as they can build nimble and scalable businesses on cloud with modern apps, APIs to collect and stream real-time data and modern ML/AI like Engati’s bots.

4. The right organisational culture

The culture of an organisation – or lack thereof – is one of the most underestimated barriers to successful AI adoption. Progress has to start from the top, with good leadership and open conversation to dispel fears and misunderstandings about the technology. Companies that are serious about AI need an executive sponsor – someone like a Chief Intelligence Officer or a Chief Data Officer to oversee AI strategy.

The next step is bringing people along on the journey. Including AI champions, who can span the world of business and technology and help engage with business users and techies alike, can be extremely useful. Having a better understanding of data science and AI across the business will also help promote data governance and ensure data is treated as the vital business asset it is. If everyone in the business understands the need for good-quality data, then that can be a big step towards better data, and therefore better AI.

5. A strategic approach

Finally, avoid AI for AI’s sake and ensure you approach AI strategically. It is absolutely vital that your AI initiatives align with your business imperatives and your technology strategy. Too many companies experiment with AI instead of first questioning how AI can help them tackle business challenges and uncover opportunities. In an ideal world, your business strategy should guide your data strategy, which in turn, should align with your AI strategy. Understand the purpose of AI for your business, and then develop the approach based on the goal.

These elements are the foundations for businesses attempting to adopt AI successfully. No matter what stage of the journey to AI your business is on, it’s worth frequently checking in and re-evaluating the barriers that are limiting the success of your AI and pivot where necessary. For, when successful, AI has the potential to offer enormous return on investment for businesses today.

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Engati Team

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