USTGlobal Machine Learning - An Industry Driver for Digital Transformation UST Global Inc, May 2018
Table of Contents Machine Learning - What to Expect 3 Digital Transformation - The Big Change Machine Learning for Digital Transformation How We Leverage Machine Learning Potential 3 4 4 Machine Learning - An Industry Driver for Digital Transformation I MAY 2018 2
Machine Learning What to Expect Machine learning (ML) has been the buzzword in most industries that work towards employing Artificial intelligence. ML is one of the most promising and in-demand applications of AI, so much that it is turning into an industry driver. Machine learning, in its most basic form, is defined as the ability of machines to change the outcome of a behavior/situation based on knowledge or observation of previous outputs or results. Technologists apply machine learning so as to reduce human effort in various work scenarios. ML differs from traditional automation owing to its self-learning abilities; i.e., with no specific instruction set, ML s performance solely depends on experience. Machine learning is being adopted in almost all industries for specific processes. Studies reveal that 98% of organizations that encourage AI-supported activities claim additional revenue being generated while 86% say that AI supported processes have played a key role in their enterprises digital transformation (1). So how exactly does it pave the way for digital transformation? Digital Transformation - The Big Change Digital transformation refers to an insightful transformation of business and organizational activities leveraging the opportunities in emerging digital technologies and accelerating change across the organization. It has huge potential to change business activities, processes and models, and manage the business assets and ecosystem. Machine learning can also be an influencer in partnerships and collaborations as well as customer care models and processes. Digital transformation focuses on three key points - Customer experience Operational Processes Business Models Customer experience is transformed through better understanding of customer needs, and improved processes and service. Operational processes focus on process 101010010 digitization, enabling workforce and managing overall business performance. Transformation is further achieved through enhanced business models, identifying new digital business opportunities and enterprise level digitization. Machine Learning - An Industry Driver for Digital Transformation I MAY 2018 3
There are several factors identified by technologists, which are the causal factors for disruption and transformation newer and improved technology innovations, better insights into customer s behavior and demands, and the industry ecosystem needing a revamp. As digital opportunities lie in all industries without exception, transformation management and its impact are the driving forces behind the profound growth of any business. Machine Learning for Digital Transformation With the rise in popularity of machine learning, more and more enterprises are turning their focus on its applications, either as standalone or in collaboration with other technology platforms. Studies predict that by 2019, 40% of all digital transformation initiatives will be supported by cognitive/ai capabilities and at least 20 percent of all workers will use automated assistant technologies by the following year (2). One such collaboration is that of Internet of Things (IoT) and Machine learning. Machine learning capabilities can be leveraged for training and executing activities locally at the edge devices of an IoT ecosystem, and can also be extended and used to train passed knowledge before taking actions. Machine learning will act as the analytical component in an IoT system. Machine learning is further employed by financial institutions to finely detect fraud and design predictive models for claims processing. Insurance companies employ ML for price optimization and loss prediction. The banking sector is looking into ML as a means to identify and understand customer needs and thereby to achieve their service goals. The healthcare industry is fairly keen on most of the AI applications. Machine learning in particular can be used effectively in the research and development sector for effectively identifying medical conditions, determining drug effects on cells, etc. The retail sector encourages AI-powered shopping applications and instore support systems, where data can be gathered and manipulated by AI and ML components very well used for analytics. Finding patterns in the shopping behaviors of customers can help in a variety of retail functions, from customer experience programs to inventory management. Application of ML in the manufacturing industry will help improve manufacturing yields, reduce wastage, assist humans in product testing, and reduce supply chain forecasting errors and much more. As the core functionality of ML can be applied across areas from analytics to optimization tasks, and from market studies to automation assistance it can be considered as a versatile AI application capable of digitally transforming a multitude of industries. How We Leverage Machine Learning Potential Artificial Intelligence and Machine Learning capabilities is one of the key focus areas at UST Global. We believe that the application of AI and ML needs to be a fine combination of the top-down and Machine Learning - An Industry Driver for Digital Transformation I MAY 2018 4
bottom-up approaches. Our technical teams have identified ML as an AI application, and research on finding business problems needing solutions where it can be effectively applied. They measure the capability and feasibility of the set of solutions they design before moving on to applying it at varying levels. Simultaneously, our business teams identify an industry specific business problem needing modification and make an estimate of the value of an effective solution. They further analyze how much of a difference each possible solution scenario can bring and finally check on the capabilities of an AI application like ML. Such a mixed approach and collaboration between teams can bring out effective and early outputs, thereby making our business, design and development teams work efficiently. So, do we believe that Machine learning is a driving force for digital transformation? Yes, we do! Self-learning smart solutions are certainly the future of global industries. Machine Learning - An Industry Driver for Digital Transformation I MAY 2018 5
ABOUT UST GLOBAL UST Global is a fast-growing digital technology company that provides advanced computing and digital services to large private and public enterprises around the world. Driven by a larger purpose of Transforming Lives and the philosophy of fewer Clients, more Attention, we bring in the entrepreneurial spirit that seeks the fastest path to value in today s digital economy. Our innovative technology services and pioneering social programs make us stand apart. UST Global is headquartered in Aliso Viejo, California and operates in 21 countries. Our clients include Fortune 500 companies in Banking and Financial Services, Healthcare, Insurance, Retail, High Technology, Manufacturing, Shipping, and Telecom. UST Global believes in building long-lasting, strategic business relationships through agile and client-centric global engagement models that combine local experts and resources with cost, scale, and quality advantages of global operations. For more information, please visit: www.ust-global.com USTGlobal Corporate Office: UST Global 5 Polaris Way, Second Floor, Aliso Viejo, CA 92656 Tel: (949) 716-8757 Fax: (949) 716-8396 www.ust-global.com For further information contact: info@ust-global.com /USTGlobal /USTGlobal /ustglobalweb /company/ust-global