Nasscom：2026 AI工程深度技能培养：赋能职场进阶与学术人才培养的行业定制方案研究报告（82页）.pdf

1、 A structured way to think about developing AI capabilities in relation to real engineering responsibility Industry Perspectives convened by nasscom For Industry leaders,Academic Institutions,faculty,and students How to Use This Document This document is written for multiple stakeholders involved in

2、 workforce upskilling and academic skilling in AI engineering.It is intended to be read selectively,based on role and context,rather than from start to finish.The guidance below outlines how different audiences typically engage with the content,what it is most useful for,and the boundaries within wh

3、ich it should be interpreted.Intended Use(Applies to All Readers)This document is designed to support clear thinking about AI capability development in relation to system responsibility across the lifecycle.It is not intended for:Individual performance assessment Job grading,promotion,or compensatio

4、n decisions Tool or vendor certification mapping Academic ranking or accreditation comparisons Using it in these ways distracts from its core intent.Read Paths by Audience A.Boards,CEOs,CFOs,and Enterprise Leadership How this can be useful Gaining clarity on where AI capability matters most in compl

5、ex systems Understanding how responsibility evolves as systems learn over time Identifying areas where intelligent behaviour may be insufficiently owned Start with Executive Summary Sections 13 Section 11(high-level view)What this typically helps clarify Why broad,tool-centric training often fails t

6、o address system responsibility Where intelligent-system behavior introduces new organizational exposure How attention needs to extend beyond release quality to full lifecycle behavior You may skip Sections 47 Annexures AB(unless deeper detail is required)B.Industry Engineering Leaders,Engineering M