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Machine learning: Unlocking the future for Hong Kong enterprises

Machine learning: Unlocking the future for Hong Kong enterprises We now stand at the edge of a new era in automation; one that is set to boost economic growth and prosperity, and underpin transformative shifts to the next industrial revolution.

Across every sector, advanced technologies such as robotics, artificial intelligence (AI) and machine learning are reducing errors, improving quality and achieving outcomes that were impossible for humans to reach alone. Automation is promising to alleviate the effects of lacklustre growth and aging population in countries around the world, and the McKinsey Global Institute estimates that machine intelligence alone will contribute as much as 1.4% productivity growth per annum in the next 50 years.

Many businesses in Hong Kong and neighbouring Asia Pacific hubs are well on their way to uncovering better productivity through the application of machine intelligence. The future is here. It’s not a sentient robot holding conversations with human colleagues, but rather narrow AI that’s been programmed to perform a single task extremely well.

Narrow AI isn’t conscious and it can’t perform intellectual tasks like a human–but it can sift through data, answer a defined set of questions, and automate routine manual processes.

Narrow AI, and machine learning in particular, are already the topic of conversations we’re having with customers across every sector in Hong Kong. By delivering consistency, accuracy and speed to a range of enterprise tasks, machine learning systems can help all kinds of businesses improve their bottom line and gain an edge over the competition.

In retail and hospitality, chatbots are proving invaluable as businesses work to meet the rising demands of digital-first customers. Instead of simply popping up to answer consumer questions online, chatbots are now expanding their roles and responsibilities–from guiding customers through every step of the ecommerce experience and processing their final payment; to acting as a personal concierge and tour guide for hotel guests; to giving in-store shoppers directions to the dressing rooms and information on what’s in stock.

The logistics industry, meanwhile, is looking to machine learning to solve the complex problems that can stop supply chains from running smoothly. Uncertain consumer behaviour, surprise weather events and poor visibility across the supply chain can all result in delays, too much or too little inventory, and lost profits. Machine learning, able to derive insight from large, intricate sets of data, is an obvious solution. By learning to identify the most important data across item-level inventory, GPS, environmental conditions and social media, intelligent algorithms can offer real-time visibility and highly accurate predictions in order to reduce inefficiencies in supply chain performance.

Financial service providers are likewise turning to machine learning to enhance their forecasting accuracy. Banks that replace traditional statistical-modelling tools with AI techniques can analyse enormous quantities of data to recommend the best financial strategies and products, targeted to individual clients’ needs.

At the moment, we’re helping a Hong Kong bank explore how AI can help to streamline service, verify identification and improve the customer experience. By pairing data analytic tools with machine learning, financial institutions can spot trends and anomalies quicker in order to identify and mitigate threats immediately – whether they’re coming from outside the business, or from within.



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