According to IDC, 40% of all the digital transformation capabilities will be fueled by cognitive and AI initiatives by 2019. IDC also expects that 20% of the workers will be using automated technologies by the end of the year. Gartner has predicted that about 20% of the content for business, including legal documents, press releases, and shareholder reports will be taken over by machines in 2020.
Both machine learning and AI have a huge potential for application in business and can change the way in which companies operate. These two technologies are already paving the way for a new digital wave that is taking over the industry. Machine learning will allow companies to have a new perspective on things, which they otherwise would have failed to observe due to the bias that exists in the human beings and the data that is accumulated by them. AI and machine learning can help in improving innovation and customer experience.
Let’s look at how both these revolutionary technologies can act as driving forces for digital transformation.
Applications of AI and Machine Learning
Machine learning can transcend human capabilities when it comes to managing huge amounts of data by searching for patterns and high order interactions among the data and tackling with challenging business issues. Nowadays, many digital businesses are seen embracing machine learning methodologies, due to increasing bandwidth, sinking storage costs, and access to sensor data.
Here are a few examples of their applications across different types of industries:
Risk and Fraud Management
Machine learning can mainly be used for fraud detection for mapping transactions to assess the probabilities of fraudulent activities in the process. Similarly, in credit risk, it can be used to map the details of the loan applicant to calculate the possibilities of the applicant defaulting on loan repayment.
One of the most remarkable breakthroughs due to machine learning and deep learning has been that of computer vision, which has led to healthcare companies using it for image analysis and diagnostic purposes. Medical data collection, new drug discovery along with robotic surgeries are other areas where machine learning has a key role to play to improve the existing processes.
Supply Chain Processes
The role of machine learning is to use algorithms to enable businesses to transform large volumes of passive data into useful information for the business. Companies using machine learning can assess the seasonal trends, actions taken by consumers, demand for new products to sell their services more effectively to the customers. This also enables them to manage their inventory better and achieve maximum growth for their business.
Core Benefits of AI and Machine Learning in Digital Transformation
Generating Business Insights
The process of generating insights involves extracting the key and meaningful information from huge volumes of raw data. With the amount of data doubling up every year, the complexity of the data also has been increasing which has created obstacles in the path of digital transformation. The tools of AI can read, review and analyze huge amounts of data to provide insight on the customer’s perception of a particular brand and the reasons behind it.
Effective Customer Engagement
AI is creating a revolution by improving personalization of information through virtual assistants and chatbots to boost customer engagement. Companies such as Facebook and Nuance are offering solutions in this space and offering services in diverse areas such as media content distribution, customer service support to personalized marketing campaigns.
Companies are using AI for speeding up on their knowledge-based activities that can boost their efficiency and core business performance. For example – Hospitals looking for patients for drug trials and banks focusing on creating strategies for investment for their customers. With automation of most of the internal processes, they are able to provide superior customer service and accelerate their business growth.
GE – An Example Worth Mentioning
GE, one of the most renowned names in industrial, financial and consumer products, has managed to leverage AI and machine learning powered by big data to achieve digital transformation for its company. Bill Ruh-CEO of GE Digital and Chief Digital Officer has emphasized on the growing importance of data and analytics in this process. The organization has also been actively employing machine learning as an approach for assisting them to leverage the power of IoT and Big Data.
GE has successfully leveraged the concept of Digital Twin which is actually a digital replica of an industrial machine (over 750,000 of them have already been deployed by GE!). In the beginning, GE didn’t have the required expertise in machine learning and AI so it went on to acquire start-ups who possessed the required knowledge in this area. The SmartSignal company was acquired in 2011 to assist them with supervised learning models to be used for remote diagnostics. Again in 2016, GE acquired Wise.io for seeking assistance on unsupervised deep learning and employed data scientists who were experts in this field. This has been immensely useful in identifying anomalies in data and assessing trends in industrial sensor data, without the necessity of creating a huge volume of labeled data. GE has also been making the best use from its third acquisition of Stew to combine data from multiple sensor sources for industrial equipment.
This solution has helped them in assembling and organizing data coming through different types of machines in the plant. At the same time, GE has collaborated with Cambridge-based data curation company, TAMR, for using machine learning for combining its business data. As a result, GE has been able to integrate its supplier data using TAMR’s machine learning software and saved $80 million in the last few years and has become one of the world’s leading vendors and users of machine learning for industrial data.
Companies around the world are slowly discovering the huge potential of machine learning and AI which can bring about a digital transformation by making their business tasks more smooth and productive for higher growth prospects.