- Published on January 31, 2023
- In AI Features
Crunching Time to Market with Agile AI Solutions
The advent of pre-built AI solutions makes it possible for businesses to work with agile models and reduce the time to show business impact by 60% compared to the traditional way of approaching AI/ML solutions.
Image by Crunching time to market with agile AI solutions
- By Prashanth Kaddi
AI is now a dominant driver for many industry-wide use cases. However, despite its ubiquitousness, AI implementations face quite a few stubborn challenges, such as time-to-market and scaling. These challenges can be addressed by shortening the overall development cycle of an AI solution through the various stages, such as identifying the problem area, acquiring data, preparing the model, running it, testing it and finally developing it on the scale, taking up to 4-5 months to show business impact. In a progressively competitive and fast-evolving data-driven world, it is becoming more and more necessary to be agile in adopting AI-driven solutions.
Organizations are trying to get around this problem by reusing highly customized in-house developed solutions across problem areas. But buildi
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Prashanth Kaddi
Prashanth Kaddi is a Partner with Deloitte India, in the Consulting business working on analytics and cognitive. He has 20 plus years of experience in technology, analytics, product management and strategic marketing. He has worked with Fortune500 companies across Asia Pacific, India, Europe, US and Latin America solutioning and delivering data-to-information solutions. As a result, enterprises have transformed business models, increased top line and bottom line, deepened customer engagement, and enabled better risk management through AI/ML solutions. Prashanth is also a part of the global leadership team of the Deloitte AI Institute, driving AI as a strategic growth engine.
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