How GlobalLogic is bringing the next business revolution with AI and Predictive Analytics

With the rapid advancements in digital technologies, Artificial Intelligence (AI) has taken the center stage to propel the digital businesses of today. Using predictive analytics to derive business insights, AI is helping numerous organizations make informed decisions to increase business efficiency and continuity. GlobalLogic, a leader in digital engineering is empowering its customers to become agile, innovative, and transforming their business with AI-powered solutions. Mr. Sanjeev Azad, Vice President – Technology, GlobalLogic in a discussion with CXOToday shares more insights on the same.

• How will AI Evolution bring Business Revolution across industries?

Response: AI has evolved rapidly in the last few years, and many industries have not just transformed their businesses through the potential of AI, but also explored new business opportunities. The evolution of AI technology has fundamentally transformed how the data is collected, processed, and applied to businesses for achieving meaningful automation, gaining efficiencies, and making informed decisions. Though the adoption of AI has mostly been in automating repetitive tasks in various sectors under Industry 4.0, the continuous improvements and recent advancements into algorithms have helped businesses to also engage customers through immersive experiences, providing service excellence and help drive innovation through intuitive models.  Adoption of AI is almost everywhere, whether it is contacting the customer care where intelligent chatbots are serving billions of customers with little human support or by B2B and B2C businesses including e-commerce & logistics to get better insights and predictability to minimize the demand & supply gaps for product recommendations, inventory forecasting, customer churn, etc.

There is no doubt that AI evolution is becoming the backbone for many business revolutions across industries and its adoption will continue to grow in the near future. Contact-center automation, customer segmentation & service analytics, business process automation and services optimization, predictive maintenance and remote assistance, risk modeling and analytics, and fraud detection and analytics are few businesses use cases where adoption of AI is playing a significant role.

• How is democratizing AI driving real-time insights to enable informed business decisions and value?

Response: The potential of AI is vast and a lot of this is yet to be discovered, and it is hard for someone to get expertise into the entire AI technologies ecosystem. That is why, most organizations are facing challenges in their AI adoption journey due to lack of right knowledge and adequate skills – and therefore, have limited AI driven innovations. Since AI is developing continuously, the innovation should not be restricted to just a group of people to experiment and come up with innovative solutions to solve the enterprise-wide use cases.

Democratizing AI will help businesses to drive digital business transformations at a larger scale.  Companies like Microsoft, Google, and Amazon are creating AI building blocks and making it available to their teams to build on top of the stack and solve the larger problems. The idea behind democratizing AI is to make AI accessible to a larger audience including business users, so that the innovative ideas can be developed at root without worrying about the technical complexities. AI, especially ML (machine learning) is all about data and once we have a large volume of data sets, more accurate machine learning models can be built. These models can be made available for the larger group to re-use and develop further innovations.

Collecting and refining data sets is a continuous process and require an enterprise grade storage that allows to process and maintain data to drive meaningful data driven insights. AutoML is a classic example of democratizing AI where the ML models are developed, trained, and deployed as shared models by the data scientist teams. These reusable models are accessible to the end users (businesses) to feed their own data to get the predictability and data driven insights without getting into technical complexities.

GlobalLogic has developed an accelerator named Intelli-Insights^[1] that helps businesses to build and leverage the machine learning models through automated pipelines using open source technologies which can be further extended with additional AI/ML libraries and refined algorithms. Through Democratizing AI, businesses can develop an innovation culture across the organization, virtualize data and enable the businesses to take advantage of AI capabilities to make informed decisions based on data driven insights.

• What is Intelligent Automation and its role in creating agile and scalable businesses?

Response: Intelligent Automation (IA) is about applying the AI capabilities to classic automation techniques such as automating through predefined rule-based scripts or robotic process automation (RPA). In today’s digital era, most business processes are too complex and dynamic in nature that the traditional automation techniques are either complex to maintain or are not sufficient to achieve the full potential of efficiency and productivity.

Therefore, IA is playing a very important role in enabling businesses to handle the agility and evolving business use cases at scale. Many businesses across industries are adopting IA to derive business value in terms of cost saving, reduce human errors, improve speed and accuracy, drive quick business decisions, and provide agility to promote innovation. For industries such as Banking and Insurance, adopting IA is not a choice, but a critical need to bring efficiencies to complex business processes and workflows (For example, automated claims processing and adjustments through AI and machine learning). With advancements in Machine Learning (ML), Optical Character Recognition (OCR) and Natural Language Processing (NLP) technologies, the submitted forms and invoices can be digitized into structured data and improve claims processing and approval automatically without any human intervention. In one of the recent engagements, we helped our customer to reduce the claims processing cost by more than 90%.

There is no doubt that IA is playing a very important role in helping businesses to not just automate repetitive tasks but also apply an intelligent layer on top of it to simplify and optimize the end-to-end business processes, resulting businesses to scale and optimize operational costs.

However, many times, we try to oversimplify the problem statement through automation, which may result in higher cost as compared to doing it manually. Hence, it is critical to calculate the overall TCO (Total Cost of Ownership – cost to implement and operate) before implementation itself.

• How are you supporting your customers with AI capabilities for business growth? Please specify some use cases.

GlobalLogic has a rich set of AI/ML capabilities such as machine learning, deep learning, computer vision, natural language processing (NLP), neural networks, pattern recognition, intelligent chatbots frameworks, cognitive and autonomous systems, intelligent content engineering to name a few. With a wide customer portfolio across industries, GlobalLogic is not just helping them build intelligent platforms and solutions using AI technologies, but also partnering with them to co-create and co-innovate to grow and monetize their businesses. Below are a couple of selected use cases:

Adaptive Learning Platform: GlobalLogic enabled a leading player in the education space to consolidate their 30+ media content products availed through mergers and acquisition. The objective was to achieve a unified platform to collect & consolidate all the contents to build an adaptive learning experience for the students. GlobalLogic partnered with the customer and helped in transforming their learning platform with capability to host multiple product models and support learning anytime from anywhere. Our efforts resulted in the development of next generation unified platform which was not just able to consolidate and host the contents from all 30+ products to provide a connected and adaptive learning experience, but also helped to economically scale their business for supporting 15M+ students and 100M+ transactions.

Intelligent Contents Generation Platform: GlobalLogic explored, researched and implemented an intelligent content generation solution using emerging and niche AI tech stack such as OpenAI and advanced computing infrastructure such as GPU/TPU to train highly intensive machine learning models. The customer has a well-established name in digital marketing innovation and is a leader in personalized digital marketing. The client is a strong believer in technology to solve challenges arising in the industries and continue to lead by its standard to bring personalized value proposition to its B2C, B2B and D2C customers. This is a new kind of experiment where this solution helped customers to convert their thoughts into high quality contents at a breathtaking pace.

Since most of our customers are looking for speed and quality for their AI initiatives, GlobalLogic has developed a rich set of accelerators that helps our customers to quickly build and deploy quality solutions with business outcomes.

• What are the key trends in AI and Predictive analytics that can accelerate business transformation?

Predictive analytics enables predictions based on historical data. The better quality of available data, the better will be the resulting predictions. Like how we do learn from our past experience and predict what potentially may happen in future, similarly, machines learn from data collected historically and provide predictions with the help of AI and advanced machine learning algorithms. According to a recent report^[2], the global market size for Predictive analytics will grow from 10.5 billion USD in 2021 to 28.1 billion USD by 2026, at a CAGR of 21.7%.

As the AI technology is maturing due to big data revolution and availability of high-performance compute and storage, predictive analytics results are also getting more accurate and precise. Predictive analytics is helping organizations to optimize operational cost and explore new business opportunities to upsell or cross sell their products and services. Here are few trends in AI and Predictive analytics where most of the businesses are leveraging its power to make informed decisions and accelerate their business transformation:

• Adoption Of AutoML / Making Predictive Analytics Accessible to all: Companies are now democratizing the AI & analytics platforms to perform predictive analytics as well as build intelligent apps for reuse across the organization or in the marketplace. There are several open-source libraries and platforms available such as TPOT, AutoKears, Autos-sklearn, H2O AutoML etc. and most of the leading cloud vendors such as Amazon, Azure and Google are offering platform services for AutoML to democratization of predictive analytics and other AI capabilities directly to business user.
• Adaptive Learning and knowledge management: Most of the enterprises are leveraging AI capabilities to build and adopt adaptive learning techniques for continuous learning and getting the real time insights based on thousands of attributes and data collected under controlled environments.
• Data Driven Insights & Informed Strategic Decisions: With the help of high quality data and precise machine learning models, organizations across industries are leveraging predictive analytics capabilities for use cases such as customer churn prediction, customer segmentation for defining business growth strategies, inventory forecasting, warehouse and storage space management, real time fraud detection, in-store footprints and staff requirements prediction and optimization, loan eligibility and repay capacity prediction based on user’s earning and spend data from various channels.
• Operational Excellence and Process Efficiencies: Businesses are using predictive analytics to understand the potential areas to optimize either process or operations with the right budget and financial planning.
• Adoption of Prescriptive analytics: As predictive analytics is maturing and has wider adoption for many organizations, companies are now going one step ahead, where they are not just using predictive analytics for prediction based on past data, but also applying AI algorithms to understand what actions should be taken to maximize the business potentials.