India's largest platform and marketplace for GCC & AI leaders and professionals

Sign in

India's largest platform and marketplace for GCC & AI leaders and professionals

3AI Digital Library

AI@scale: How to go about it

3AI January 13, 2020

AI is invoking shifts in the business value chains of enterprises. And it is redefining what it takes for enterprises to achieve competitive advantage. Yet, even as several enterprises have begun applying AI engagements with impressive results, few have developed full-scale AI capabilities that are systemic and enterprise wide.

The power of AI is changing business as we know it. AIQRATE AI@scale advisory services allow you to transform your operating model, so you can move beyond isolated AI use cases toward an enterprise wide program and realize the full value potential.

We have realized that that unleashing the true power of AI requires scaling it across the entire business functions and value chain and its calls for “transforming the business “.

An AI@scale transformation should occur through a series of top-down and bottom-up actions to create alignment, buy-in, and follow-through. This ensures the successful industrialization of AI across enterprises and their value chains.

The following strategic interventions are to be initiated to build AI@scale transformation program:

  • AI Maturity Assessment: This strategic top-down establishes the overall context of the transformation and helps prevent the enterprises from pursuing isolated AI pilots. The maturity assessment is typically based on a blend of AI masterclass, surveys and assessments
  • Strategic AI Initiatives and business value chains: This bottom-up step provides a baseline of current AI initiatives. It should include goals, business cases, accountabilities, work streams, and milestones in addition to an analysis of data management, algorithms, performance metrics. A review of the current business value chain and proposed transformational structure should also be conducted at this stage.
  • Strategic mapping & gap Analysis: The next top-down step prioritizes AI initiatives, focusing on easy wins and low hanging fruits. This step also identifies the required changes to the operating business model.
  • AI@scale transformation program: This critical strategic step consists of both the transformation roadmap, including the order of initiatives to be rolled out, and the creation of a planned program management approach to oversee the transformation.
  • AI@scale implementation: This covers implementation, detailing the work streams, responsibilities, targets, milestones, talent and partner mapping.

By systematically moving through these steps, the implementation of AI@scale will proceed with much greater speed and certainty. Enterprises must be aware that AI@scale requires deep transformative changes and need strategic and operational buy ins from management for long term business gains and impact .

AIQRATE works closely with global & Indian enterprises , GCC’s , VC/PE firms to provide end-to-end AI@scale advisory services

Related Posts

AIQRATIONS

    3AI Trending Articles

  • Emerging role of Generative AI for Businesses

    Featured Article: Author: Rajan Gupta, VP & Head of Research & Analytics, Analyttica Datalab Artificial intelligence (AI) has revolutionized the way businesses operate, and Generative AI (GAI) is quickly becoming a hot topic in this field. Generative AI is the technology behind applications that can produce new content, such as images, sounds, and even text. […]

  • Facebook is testing an AI-powered tool to Summarize News

    Facebook has been trying to get a foothold in the news space for many years. Last year, the company launched a dedicated section on its site called Facebook News for users in the US. It also wants to expand this program to other countries such as Brazil, Germany, and India. According to a report from […]

  • Towards a Responsible Future – Decoding the Importance of Ethics in AI

    Featured Article by Anusha Thakur The conjunction of the obtainability of vast amounts of stretch, speed, and big data for the development of machine learning algorithms and cloud computing platforms has led to a varied range of innovations in Artificial Intelligence (AI). In an era defined by state-of-the-art technologies, the role of AI systems, and […]

  • Automated Quality Excellence Framework for Data Science Modelling

    Featured Article: Author: Abhishek Sengupta, Walmart Global Tech India Introduction:  A necessary but often tedious task data scientists must perform as part of any project is quality assurance (QA) of their modules so as to prevent any unforeseen incidents during deployment. While Quality Assurance and Excellence is quite prevalent in Data Engineering, QE in Data […]