The cloud is the de facto transformational platform for leading enterprises. It provides newfound agility, resiliency, and growth opportunities for the hyperconnected fourth industrial revolution. And across all industries, retail is in the top eight for investments and initiatives in the cloud. More than 78% of retailers are either mature cloud users or are advancing cloud investments. In fact, with the current pace of spending, the global retail cloud market will grow to $39.63 billion by 2026.
What is behind this rapid investment? It is a change in consumer behavior. The new consumer leverages social media for product reviews, is comfortable purchasing online and expects better and more personalized experiences across channels. But enterprises find it challenging to address all these expectations with existing, non-scalable legacy system architecture, which isn’t well integrated. As such, many retailers are prioritizing a digital-first retail strategy and adopting a cloud/hybrid ecosystem to leverage cloud-managed services. But identifying and migrating knowledge assets will need to be a central focus in the cloud migration to meet the changing customer and market demands.
Knowledge Management – An Obstacle in Cloud Migration
One critical aspect of cloud adoption is migrating a company’s knowledge assets. The legacy to cloud migration journey requires knowledge sharing across teams. But knowledge assets are typically distributed across many people and sources. This distribution of information with no records or documentation makes migrating the existing asset inventory challenging. And most retail enterprises struggle to share knowledge, find answers to technical/functional queries, etc.
Another hurdle to overcome is the data that drives loyalty program management. This program allows companies to provide a better customer experience but is frequently challenging to manage effectively due to siloed multichannel sales and customer data at the store level. Consequently, contact support teams do not have a 360-degree customer view. AI-based Knowledge Assist can help answer most of the above challenges and equip teams with information, at the right time, from multiple sources and types of data.
How Does AI-based Knowledge Assist Work?
AI-based Knowledge Assist is an effective Natural Language-based assist (query/response) platform. It helps users find various types of knowledge from several sources, like documents and web pages, through a query that uses natural, simple English language. Knowledge Assist prioritizes responses based on the relevance to the user query. The whole process and knowledge search occur quickly, and the user gets the correct information.
Knowledge Assist analyzes a query, searches for relevant documents and returns the summary and links to the user. For asset inventory discovery and rationalization, Knowledge Assist uses the relationship graphs created by the scanning agents to help find the requested assets. These graphs efficiently retrieve asset information and aid in accurate decision-making to rehost/retire.
Knowledge Assist with cognitive search capabilities provides relevant information efficiently and interactively. Designed to work on multiple data repositories, Knowledge Assist can answer different personas at the same time. For the support agent/customer persona, it could help with a product catalog search, customer information, purchase history, etc. For an IT team persona, it could aid application migration triage, specific migration plan, server information, etc.
Benefits of Utilizing AI-based Knowledge Assist
Knowledge Assist helps retailers reimagine intelligent, data-driven retail. It boosts retail support agents’ productivity as they get relevant, near real-time information from a query with minimal effort and can proceed with the next action. Knowledge Assist is an AI-based support agent that is available 24-7. The assistant expands its knowledge with each new query in the migration journey and learns from the historical interactions, thereby continually improving itself and becoming more efficient and valuable.
But the benefits of Knowledge Assist extend beyond operations – it improves the asset migration process during a cloud migration journey. AI-based cognitive search reduces the hidden and indirect costs incurred while discovering the inter-dependency bottlenecks across various knowledge sources or assets. AI-based Knowledge Assist plays a role in several stages in the cloud migration journey and for different personas to ensure all relevant information is available to the team. For IT teams, it can assist in the cloud migration discovery and assessment phase, where teams usually spend a lot of time trying to understand the technical landscape, various legacy systems, and relevant documents. In this area, it accelerates asset assessments and prepares retailers for an efficient cloud migration and adoption journey.
Bhajandeep Singh
AWS AI/ML Practice Manager, Wipro Limited
Bhajandeep led multiple Data Analytics and AI solutions projects. Currently, he leads the AWS AI/ML practice in Wipro’s AI/ML Solutions group. Bhajandeep is AWS AI/ML specialty certified and writes technical blogs on AI/ML services/solutions.
Manish Okhade
Head - Cloud AI, Wipro Limited
Manish has more than two decades of industry experience in Engineering, Digital and Artificial Intelligence. He is presently leading a Cloud AI Practice in Wipro’s AI/ML Solutions group. Manish is currently focusing on building accelerators and forging partnerships with niche start-ups in various domains.
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