Day #3 Leveraging Artificial Intelligence For Business Success
Let us stay a bit longer with the second chapter "Understanding Big Picture" (of the book "Leveraging Artificial Intelligence For Business Success") which does a comprehensive job of outlining the entire AI landscape. We are already allowing AI to drive our day-to-day life when we use apps like voice assistant, camera, face recognition, google translation and google maps on our phones. Most businesses are sitting on huge amounts of data that could be AI-leveraged. Data could be scattered across different business functions like accounting, CRM, Sales, HR and the entire supply chain.
Organizations could use AI to better understand their customers (say by using support calls data), penetrate new customer segments and markets (using CRM data), reduce costs across the entire supply chain and launch new products. As per a recent Gartner survey, "one-third of organizations are applying AI across several business units, creating a stronger competitive differentiator by supporting decisions across business processes."
Mckinsey's "The state of AI in 2021" global survey indicated that "AI adoption continues to grow and that the benefits remain significant— though in the COVID-19 pandemic’s first year, they were felt more strongly on the cost-savings front than the top line."
Yet, several hurdles remain in AI adoption. Ben Dickson, the founder of TechTalks, identifies "lack of tooling and infrastructure" as a barrier to deploying good-quality ML algorithms. The good news is that there is rapid progress on these fronts with the rise "no-code ML platforms, easy-to-use ML programming libraries, API-based ML services (MLaaS), and special hardware for training and running ML models."
To be contd.
References:
1) https://www.gartner.com/en/newsroom/press-releases/2022-08-22-gartner-survey-reveals-80-percent-of-executives-think-automation-can-be-applied-to-any-business-decision
2) https://www.mckinsey.com/business-functions/quantumblack/our-insights/global-survey-the-state-of-ai-in-2021
3) https://bdtechtalks.com/2022/08/29/mckinsey-applied-ai-mlops/