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How businesses can stay on top of the AI wave
As artificial intelligence becomes increasingly widespread, companies will need to keep up with the latest trends and put their own spin on it to stand out from the competition.
At a recent “AI for Business – Reimagining Tomorrow” webinar, we have invited speakers from HSBC Global Research, Google, Grab and Brandix to share their thoughts on how AI can be applied in various sectors.
Key takeaways from the webinar:
- Businesses in almost every industry will be able to use AI to streamline processes, serve customers better, innovate and grow.
- In addition to saving time and money in myriad ways, AI enables the personalisation that customers increasingly expect.
- The dawn of generative AI allows people to interact with AI platforms in plain language, paving the way for mass adoption by employees and customers.
- AI will augment the workforce rather than replacing it. Companies need to roll out AI tools strategically and upskill their staff to use AI effectively.
Watch the replay to understand the potential applications of AI and its impacts in our latest webinar.
The share prices of large technology companies have surged over the past two years in large part because of the excitement around artificial intelligence (AI.) But the biggest beneficiaries of the current competition among tech giants to develop and deploy AI solutions could well be the end-users, who will be able to access the technology more affordably. These include businesses across virtually every industry who will be able to use AI to streamline processes, serve customers better, innovate and grow.
As AI adoption continues to expand across regions and sectors, those who are not up to speed on its potential applications and impacts risk being left behind. It is crucial that businesses not only understand the latest AI developments, but also take a forward-looking view of how it will reshape their industry.
“We need to think how we can use the technology to make ourselves an efficiency leader or cost leader,” said Michael Yung, Strategic Advisor at Google Cloud, speaking at HSBC’s latest AI for Business webinar on the theme of Reimagining Tomorrow. Yung offered several practical examples of how leading businesses are using AI to save time and money, design new products and services to differentiate themselves in a crowded market, and provide better, more focused customer service.
Of course, AI is not exactly new. As Yung pointed out, it has been widely used for at least a decade to help process the ever-growing volumes of data available to companies to generate insights and make predictions. “We often call it traditional AI now,” he said. “You can use it to analyse lot of data. It can tell you about what happened in the past and why it happened. And then, of course, there is predictive AI – you give it some data and ask it questions, and it can predict what will happen in the near future.”
Such “traditional” AI drives the recommendation engines of e-commerce sites and helps retailers optimise inventory, Yung added. It allows banks and other companies to detect fraud more quickly, efficiently and on a much larger scale. And it can improve the ability of all types of businesses to provide answers to customers’ call centre enquires – and handle documents and paperwork by making complex data more accessible.
The dawn of the GenAI age
What has really changed since the advent of Generative AI tools like ChatGPT two years ago is the ability for non-specialists to interact with AI platforms, enabling businesses to empower their employees with productivity-boosting workplace co-pilots, and to serve customers with intelligent, automated support agents offering personalised attention.
Personalising the customer experience with AI is a major focus of digital platforms. Tim Ackarapolpanich, Commercial Director at Grab Thailand, said that “consumers these days expect personalisation.” This is feasible for Grab, which provides everything from taxi bookings and food deliveries to financial services and holiday packages – giving it access to vast troves of first-party customer data.
“At Grab, we leverage first-party data to understand where people go, what food they order, and which groceries they buy,” explained Ackarapolpanich. “These first-party data are what our AI models consume, allowing us to personalise offerings to meet consumer needs.”
Ackarapolpanich also highlighted the vital role AI plays in preventing fraud within Grab’s ecosystem, ensuring the trust needed for growth. “We have so many parties and stakeholders, including merchant partners, customers and drivers. We leverage AI to run simulations and modelling to ensure that the transactions between these people are good and not fraudulent,” he said. “We run this model and predict what would be a fraudulent transaction and prevent it before it happens. That's one of the things that we have done to ensure the ethical use of our platform.”
AI is also transforming more traditional industries. Hasitha Premaratne, Managing Director of Sri Lankan apparel manufacturer Brandix Group, described how his company piloted “smart factories” that use AI to carry out predictive maintenance, which can lead to significant efficiency improvements and cost savings.
By gathering and analysing real-time data on “how many times a machine has failed and why it may be running at a lower productivity level at times,” AI helps the company make “more proactive and timely decisions,” explained Premaratne. On the product sales and market side of Brandix’s business, AI can play a vital role in helping to analyse and predict fast-changing fashion trends and consumer preferences, he added.
Moreover, in support of the core manufacturing and sales functions, Premaratne said that Brandix is also applying AI to optimise its Human Resources and finance processes. And considering recent regulations requiring apparel manufacturers to track and verify the origin of raw materials like cotton through the supply chain, the company is applying AI to improve traceability.
Getting buy-in
“I think AI can help in any industry,” said Ackarapolpanich. “The best thing we’ve done at Grab is to give AI tools for everybody in the organisation to try. Any type of company can do this – it’s about adopting an AI-first mindset.”
Premaratne at Brandix said that how firms engage with data and AI has to start at the top of an organisation and cascade down from there. He suggested that rather than providing AI tools to all employees, companies wishing to encourage employees to adopt them would be better off initially giving access to a small group of users, which would create a “buzz” ahead of a larger-scale rollout. “That will lead to more people pushing for access and take things to the next level.”
As AI continues to spread, fears of widespread job losses are unlikely to be realised, said Mark McDonald, Head of Data Science and Analytics at HSBC Global Research. “Although there is lots of concern about AI leading to large-scale job losses, we think these risks are overblown. AI tools learn to automate tasks, so unless someone’s role is very narrow the more likely outcome is that AI can help automate specific tasks, which then allows the employee to focus on the tasks which AI cannot currently help with. Fortunately, for many people these are likely to be higher value tasks which can have more of an impact on a company’s performance,” he said.
HSBC believes the winning formula for business is leveraging AI and human judgement to boost each other. “We’ve been using AI for many years to enhance operational efficiency, improve customer experience and strengthen risk management,” said Stuart Rogers, Regional Head of International Markets, Asia Pacific, HSBC Commercial Banking, in his opening remarks. “We invest heavily to remain at the forefront of using AI to improve areas such as fraud detection, transaction monitoring, customer service and risk assessment.”
As AI becomes increasingly ubiquitous, what will set businesses apart is their ability to put their own spin on it. “AI itself is not a differentiator – if every one of us has AI, including our competitor, it is only an equalizer,” said Yung. “You therefore need to create differentiation though your own data, your own expertise in products, processes and workflows.”
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