Key takeaways
Enterprise digital journey:
Organizations are at a unique juncture where most of them are in the process of embarking on digital transformation journeys. While digital transformations entail a gross change in the end user’s interactions with applications, they also involve adopting a paradigm shift in the way engineering needs to be done, compared to the traditional approach.
End users are already experiencing the power of what smart applications can do in their daily lives. Be it real-time traffic congestion alerts, targeted product recommendations or asking a Cortana-powered speaker to order our daily groceries; these experiences are conversational. Also, they feel natural, can figure out our intent, are predictive and are uncannily prescient. We are reaching the tipping point and soon we will see smart applications proliferate into the way end users do business interactions across multiple domains/ industries. Each of these industries/ businesses will need to evolve their current IT applications into entirely different interfaces that facilitate same-newer business processes for end users. The enterprises of yesterday have to embark on this journey to adapt to changing needs of end users.
This change would involve adopting new ‘as-a-service’ models, culture that is agile, design thinking led, full stack led, value stream that isBizDevOps, and powered by ‘cloud native’ platform with ‘intelligence’ infused at every level.
Adding intelligence into applications for democratizing developer experience: While enterprises will look at infusing AI into every application, we will look at how pre-built AI models and tools can help accelerate infusing AI into applications. This helps in democratization of developer experience by ensuring a much easier way of leveraging AI and best practices in applications. The more developer-friendly the models are, the easier they can be adopted by developers and enterprises.
Figure 1: Assembling customized AI applications from pre-built models
This paper looks at three sample components which could potentially be used for infusing AI and accelerating the digitization journeys for customers.
Detailed view:
1. AI-based face recognition: Facial recognition can be used to recognize a face based on contours.
With this technique, applications can leverage data that defines facial details as well as any additional information about the individual and then create new ways of interactions. The global 3D facial recognition system market is expected to grow at the CAGR to over 36% from 2018-2022.
Facial recognition can be effectively leveraged to solve many problems across verticals such as banking, healthcare, residential security, and travelling without hassle etc., and horizontally across domains as well. It has matured quite a lot over the past few years and is fairly accurate.
Figure 2: Use cases for face recognition
Figure 3: Azure face API being used in an ATM center
2. AI-based image classification: With an increasing adoption of autonomous and semi-autonomous vehicles, drones (military and domestic purpose) wearables, and smartphones, the global image recognition market looks all set to account for over $20 billion in the coming years and is expected to double by 2022.
Some of the use cases are illustrated as follows:
Figure 4: Use cases for image classification
Figure 5: Retail use case for image classification
Figure 6: Workflow for auto classifying and training images
3. AI infused virtual CoE as-a-service: As enterprises are embarking on their journeys, having a virtual CoE as a service helps in infusing best practices, templates and a governance mechanism into the adoption process, and can accelerate their innovation journeys.
An AI-based virtual CoE helps in constantly learning and providing the right guidance and reviews. AI can help in self-learning and providing the right guidance to projects ensuring delivery assurance, best practices adoption etc. Learnings and pattern analysis can help recommend based on past execution experiences.
Figure 7: Virtual CoE in action
Use-case realization:
Acknowledgement:
Special thanks to reviewer panel led by Aravind Ajad Yarra, Dr. Abhijit Shrikant Rajnekar, Srinivas Deshpande and core team members Anshika Agarwal, Divyanshu Jain and Sachin Chaudhary for implementaion of the solution.
Rekha Kodali,
Head – Presales and Strategy Microsoft Practice, Wipro Limited.
Rekha’s core competency, honed over 22 years of professional experience, includes enterprise architecture and Microsoft technologies. She has designed state of the art solutions based on a multitude of technologies and acquired various industry-recognized certifications.
Md Tahir,
Senior Consultant, Microsoft Practice, Wipro Limited.
Md Tahir with over 5 years of IT experience, has been integral in building solutions for large integrated deals involving various business application technologies, especially across the health domain.
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