CEO & Co-Founder
Artificial Intelligence or AI is the technology behind the fourth industrial revolution that has brought great changes all around the world. It is usually defined as the study of intelligent systems that could execute tasks and activities that would require human level intelligence. Similar to the past three industrial revolutions, AI is leaving an incredible impact on productivity.
The AI revolution has fundamentally changed the ways people collect and process data as well as transformed business operations across different industries. In general, AI systems are supported by three major aspects which are: domain knowledge, data generation, and machine learning. Domain knowledge denotes the understanding and expertise of the real life scenario on why and how we need to engineer a task. The data aspect refers to the process of preparing databases required to feed on to the learning algorithms. Lastly, machine learning detects the patterns from the training data, predicts and performs tasks without being manually or explicitly programmed.
The simulation of human intelligence by machines can infer a fast solution for the problems that are often faced by humanity. AI is backed by advanced data analytics and machine learning, which means AI can learn and gain new insights as it keeps feeding on new data. With proper input, AI could come up with prompt and accurate decisions. In addition to that, the intelligence attribute of AI promotes productivity and reduces dependency on human support which makes AI highly autonomous and a convenient tool to have.
Intentionality is often deemed as the technical and ontological attributes of computer programs that derived from the algorithms and knowledge engineering. This attribute can be interpreted as AI’s capability of delivering insights from the real time information and reacting in the way similar to its creators’ and users’. The responses usually strongly reflect the social context that creator and users are in. Additionally, with development of data ingestion, storage capacity, processing speed and analytic techniques, AI gets more capable of responding to the issues with increasing sophistication. This very much differentiates AI with the fundamental function of machines that merely carry out predetermined routines.
Machine learning facilitates AI to discover the pattern of the data that were previously programmed, which enables AI’s capability of making its own change as circumstances change. The attribute of adaptability profoundly enhances AI’s prediction and decision making. One of the commonly seen examples is Gmail’s Smart Compose feature, which offers the use of personalised suggestions as users typing a sentence. It illustrates how AI adapts to one’s personal writing pattern and delivers appropriate suggestions.
Undoubtedly, the artificial intelligence revolutions had profoundly impacted the way businesses operate. The most common practises are the automation of repetitive tasks that require less human input. However, with the consistent improvement of algorithms, AI technology is no longer only limited to the capability of expanding productivity, but also becomes a necessary tool in engaging customers, providing service excellence, and driving innovation. Here are several industrial scenarios to demonstrate how AI transformed the nature and scope of business activities.
The contact center has evolved significantly over the years and has become more sophisticated thanks to the use of AI Automation. We can see technological advancement of contact centers in the form of Chatbots and Talkbots that enables 24/7 availability and instant response for consumer engagement at scale. Changing the strategies to engage customers with AI based automation vastly boost service capability and reduce service failures that are usually caused by under-performing agents or emotional labour. While human agents require frequent and regular customer service training to maintain the service quality, AI Talkbot learns from every customer interaction and keeps improving to provide excellent service over time. This very much reduces labour cost associated with performance evaluation and contact center training.
Furthermore, AI systems in contact centers such as Talkbot have the capability to be customized to deliver a more personal experience through goal driven dialogues based on the customer data and business metric. In other words, Talkbots can easily do upselling and cross selling if they are given sufficient information about the customers and the business plan. Even without any customer care training, Talkbots can conduct sentiment analysis from the conversation and unlock the hidden customer data in customer voice calls. This, in turn, provides great insights for future planning. Also, compared to the traditional contact center, AI systems show stronger capabilities in collecting information from each call which are used to generate the report in a more intelligent manner and with better insights.
Nowadays the e-commerce market is highly saturated and competitive. Top e- commerce companies heavily rely on AI technology to better understand their customers and to give their customers better service in order to remain competitive and profitable. Intelligent product recommendation is one of the typical applications of AI in the ecommerce industry. This is a real-time application of an AI algorithm that attempts to figure out customers’ preference based on their previous purchases, researches, and consumption habits. The collected insights enable e-commerce companies to personalize product recommendations for different online shoppers. To a certain extent, it enhances the shopping experience and potentially boosts sales. However, if the e-commerces overuses intelligent product recommendation and adopts an aggressive marketing strategy, the reverse effect might happen. Beyond the function of personalization, e-commerce businesses also leverage AI technology to support customer service through chatbots and talkbots to assist them with customer care, inventory management via demand forecasting, or product promotion.
The use of artificial intelligence and machine learning has fundamentally transformed supply chain management and delivered strong optimization of capabilities associated with accurate management, high productivity, low operating cost and quick delivery. For example, with the capability of handling big data, the AI technology could be used to automates the workflow of inventory management. Parcels could be packed and sorted in a seamless process at large scale, which would largely reduce processing time and minimize human error. Also, the AI system can forecast market demand from the market and purchase histories, facilitating the prediction of the future sales and providing information to support resource allocation. Moreover, AI algorithms are also being used to optimize the shipping and delivery route, with some of the most advanced ones even involving the prediction and management of traffic lights.
Overall, in the information and data driven era, the potential of AI is tremendous. Business process automation could reduce stress on internal productivity and decrease reliance on human support while at the same time increase operational cost efficiency. Machine learning enables the company to delve into a more intelligent approach and continually drives the evolution business model. Companies should prepare themselves for the AI revolution wave, so they can leverage on the technology to achieve the optimal operational excellence.