印孚瑟斯：2022人工智能数据雷达-从数据科学到实际业务让人工智能成为现实（英文版）（36页）.pdf

1、01 11001110 01 11 00 1100 001 11 00 10 11 00 11 01 01 11001110 01 11 00 1100 001 11 00 10 11 00 11 01 1100 11 01 11001110 01 11 00 1100 001 11 00 10 11 00 11 01 DATA+AI RADAR 2022MAKING AI REAL:FROM DATA SCIENCE TO PRACTICAL BUSINESS2|DATA+AI RADAR 2022External Document 2022 Infosys LimitedAIContent

2、sDATA+AI RADAR 2022|3 External Document 2022 Infosys LimitedExecutive summary 5Companies are new to AI and it shows 6Most AI is basic,and not autonomous 7Humans limit the speed of AI 9Sparse satisfaction,but financial services a bright spot 10A conversation about AI with AI 12Data is not the new oil

3、 it needs a new metaphor 13Ever-evolving methods of data management 14Data sharing delivers a dual benefit 15Effective AI requires data to be fresh and clean 16Poor processes invite bias 18Advanced AI requires trust across all dimensions 19Trust is a blind spot 20The where,what,and who of AI 21Deep

4、learning helps achieve AI at scale 22Whats at stake:Data+AI must prove its nothing to fear 23Recommendations:Precision,trust,business value 241.Get your data right,and share it 252.Build trust in advanced AI 273.Compose an AI team biased to business value 28Appendix:Research approach 294|DATA+AI RAD

5、AR 2022External Document 2022 Infosys LimitedGenerating real value from data and AI requires companies to share data,build trust in the results delivered by advanced systems,and keep business goals at the fore.01 11001110 01 11 00 1100 001 11 00 10 11 00 11 01 1100 11 00 11 0001 11001110 01 11 00 11

6、00 001 11 00 10 11 00 11 01 1100 11 00 11 00 00101 11001110 01 11 00 1100 001 11 00 10 11 00 11 01 1100 11 00 11 0DATA+AI RADAR 2022|5 External Document 2022 Infosys LimitedMaking AI Real:From data science to practical businessExecutive summaryCompanies need to think differently about data and artif