Cognizant keeps a holistic view of AI, covering everything from enablers such as platforms, data governance, master data, to the human aspect where we view AI as a means to augment people’s decisions.
We’d like to share some of the ongoing projects from our clients that have set out for an AI-fueled business:
- Digitalization at shipping giant. Wallenius Wilhelmsen is a 150-year-old Norwegian shipping company. WWL is currently in the midst of a fundamental digital transformation, where connectivity, IoT, AI and big data will increase efficiency, help meet regulations and cut carbon emissions. To make it all happen, a modern data platform is essential – it will help consolidate, manage and make data available across the enterprise to support digital transformation. As an example, 55 vessels are now streaming performance data to the onshore big data platform, where engine performance is tracked to improve efficiency and save fuel.
- Mowi automates farming. As Mowi made a conscious decision to improve its traditional operations through technology, it meant steering away from a labor-intense business to a more knowledge intense and connected one. The mission is driven by hard facts: aquatic food plays an important role in feeding the growing number of people (47.5 million additional tons will be required), but 90% of the world fisheries are already fully or overfished. To scale up volumes, digitalization and transformation of the value chain are key, and Mowi has set up a vision to become the world’s most automated farm. The heart is an operations center where the entire value chain is integrated, farms remotely controlled in real-time, and decisions infused by AI. All data is to be stored in machine learning platforms to analyze, spot trends, and learn from.
- Becoming a digital insurer. Cognizant has been involved in several data modernization projects, as part of the preparation for realizing AI and machine learning initiatives. This very company’s overall ambition is to become a customer-driven digital insurer, with the ability to predict and address the customer need before it is expressed, regardless of channel. It also wants to move away from a siloed country-level perspective into a more Nordic and proactive one. A new data lake will give the company an engine for capturing any type of data, generating insights via advanced algorithms and integrating these insights in real-time with the core processes. Firstly, the insurance company has decided to execute a minimal viable product (MVP) and to build a churn prediction model for its large portfolio of commercial customers. Now, they are looking to expand the program and include more areas.
- New data foundation for digitized banking. To this Nordic-Baltic banking group, a scalable, future-proof data lake is a prerequisite for capturing diverse types of data, encouraging experimentation with data, generating comprehensive insights, and integrating data with decision-making. This, in turn, makes it possible to get to know the customers and to create engaging digital channels that drive profitability and sustainability. The data lake is also a cost-effective way to store and manage large volumes of data from internal and external data sources to enable AI, to provide enterprise-wide access to data to several strategic business initiatives across the bank, and to provide the ability to ingest and process near real-time events. So far, the bank company experiences several new capabilities and advantages. Among other things, the bank has a better understanding of the customer’s purchasing behavior and can tap into their transactional data to provide relevant and timely “next best action”.
- Preparing for AI at Orkla. Consumer goods company Orkla offers strong local brands in the Nordics but is also a global player. It has implemented a business-driven, step-by-step approach for accelerating digital initiatives across its 108 factories. From a supply chain point of view, Orkla has been challenged by many local systems. More than 50 different ERP systems are now being consolidated into two systems. Acknowledging the value of data, preferable high-quality master data, as the most fundamental piece has been essential. It is now treated as an important asset across the value chain. Reliable data is also the foundation for AI and new insights. So far, Orkla runs a few IoT pilots and has “demystified machine learning and artificial intelligence” using embedded solutions from the ERP vendors.
If you’re curious to explore Cognizant’s global AI projects, please read more in this whitepaper containing 33 cross-industry case studies and also check out our AI offerings.