{"id":7655,"date":"2022-07-11T07:25:29","date_gmt":"2022-07-11T07:25:29","guid":{"rendered":"https:\/\/wordpress-1143641-3979373.cloudwaysapps.com\/?p=7655"},"modified":"2023-10-25T07:37:03","modified_gmt":"2023-10-25T07:37:03","slug":"task-classification-of-ai","status":"publish","type":"post","link":"https:\/\/talentsprint.com\/blog\/task-classification-of-ai\/","title":{"rendered":"Task Classification of AI"},"content":{"rendered":"\n

It takes not just one blow, but many, for a bat to become a Batman. And it all boils down to the tasks they do.<\/em><\/p>\n\n\n\n

In the wise and penetrative words of Alan Perlis, \u201cA year spent in artificial intelligence is enough to make one believe in God.\u201d Let\u2019s raise a toast to Alan and chat more about artificial intelligence (AI) in the same vein. AI looks like a miracle. And it\u2019s a miracle created by humans \u2013 to a large extent. That\u2019s why AI is becoming as powerful and mysterious as a Batman. It has so many shades, and it can fly to unimaginable heights. If we could look at some initial encounters, that should be enough to make us utter a big \u2018Wow\u2019.<\/p>\n\n\n\n

AI- sliced by tasks<\/strong><\/h2>\n\n\n\n

Now, while AI is getting faster and more profound in all kinds of tasks, what\u2019s interesting to note is its swift maturity curve in expert systems. The adoption curve here is quite fascinating and explosive. <\/p>\n\n\n\n

As per the State of AI Report 2021, AI is stepping up in areas as complex as mission-critical infrastructure like national electric grids and automated supermarket warehousing optimization during pandemics. In addition, it is getting its roots deep into faster simulations of humans\u2019 cellular machinery (proteins and RNA).<\/p>\n\n\n\n

The McKinsey State of AI 2021 survey shows that AI adoption continues to grow and that the benefits remain significant\u2014 though, in the COVID-19 pandemic\u2019s first year, they were felt more intensely on the cost-savings front than on the top line. Moreover, as AI\u2019s use in business becomes more common, the tools and best practices to make the most out of AI have also become more sophisticated. Fifty-six percent of all respondents report AI adoption in at least one function, up from 50 percent in 2020. Notably, AI adoption increased most at companies headquartered in emerging economies, including China, the Middle East, and North Africa: 57 percent of respondents signified strong adoption, up from 45 percent in 2020. And across regions, the adoption rate is quite huge at Indian companies, followed closely by those in Asia\u2013Pacific.<\/p>\n\n\n\n

AI adoption is becoming common in areas like service operations, product and service development, and marketing and sales. Popular use cases are service-operations optimization, AI-based enhancement of products, and contact-center automation \u2013 do note that the most significant percentage-point jump has been in the use of AI in marketing-budget allocation and spending effectiveness.<\/p>\n\n\n\n

AI- not so mundane anymore<\/strong><\/h3>\n\n\n\n

AI is being used in service operations optimization (27 percent), contact-center automation (22 percent), AI-based product enhancements (22 percent), and product feature optimization (20 percent). In marketing areas, we see the use of AI in customer service analytics. It is also being used in customer segmentation (16 percent). In supply chain areas, too, AI is expanding its impact on logistics network optimization and sales-demand forecasting (11 percent). Not just that, AI is now being used confidently in risk modeling (16 percent) and fraud and debt analysis (14 percent). In factories, we see AI being deployed for predictive maintenance (12 percent) and for yield\/throughput optimization (11 percent). AI is also becoming handy for top strategic tasks like capital allocation (seven percent) and treasury management (six percent). And all of this translates into bottom-line impact for sure. As much as 27 percent were seen reporting at least 5 percent of earnings before interest and taxes (EBIT) that\u2019s attributable to AI. Many organizations also reported higher levels of cost cuts from AI adoption in the pandemic\u2019s first year, while revenue spikes held steady.<\/p>\n\n\n\n

It is evident that as we gain maturity and clarity on AI, we will see more and more expert tasks getting into the core adoption bucket of AI. This would, of course, need support on facets like skill-sets, human-in-the-loop expertise, and the adequacy of tools for AI.<\/p>\n\n\n\n

Any enterprise that invests well in AI talent, AI models, and AI-ready data \u2013 is bound to unlock many more miracles of AI in the near future. So this superhero is growing brilliantly in various shades of tasks \u2013 as we move ahead.<\/p>\n\n\n\n

AI is getting better and better at expert tasks. From a caveman to a Batman- and now it will need a good Alfred all the more. Let\u2019s start getting those Bat-mobiles out.<\/p>\n","protected":false},"excerpt":{"rendered":"

It takes not just one blow, but many, for a bat to become a Batman. And it all boils down to the tasks they do. In the wise and penetrative words of Alan Perlis, \u201cA year spent in artificial intelligence is enough to make one believe in God.\u201d Let\u2019s raise a toast to Alan and […]<\/p>\n","protected":false},"author":1,"featured_media":7656,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[386],"tags":[],"acf":[],"yoast_head":"\nClassification of AI<\/title>\n<meta name=\"description\" content=\"AI is getting better and better at expert tasks. From a caveman to a Batman- and now it will need a good Alfred all the more. 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