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DESCRIPTION:This meeting was recorded. You can find the recording at https:
 //youtu.be/S1e8WbYj7Vw\n\nArtificial intelligence can only create real val
 ue when the underlying data\, architecture\, and governance are ready for 
 it. In this talk\, as a system architect I will share practical lessons fr
 om experience of designing and leading large-scale insurance platforms at 
 three startup insurance companies\, including quoting engines\, carrier in
 tegrations\, and cloud-native lead acquisition systems. Drawing on two dec
 ades of experience in insurance technology\, I will outline four key prere
 quisites for successful AI adoption in regulated industries: solid data fo
 undations\, modular and API-driven architectures\, strong security and com
 pliance practices\, and cross-functional teams and processes. The session 
 is aimed at students\, engineers\, AI practitioners\, and business leaders
  who want a clear\, real-world view of how to prepare complex systems for 
 AI at scale.\n\nSpeaker(s): Malar Kondappan\n\nVirtual: https://events.vto
 ols.ieee.org/m/522134
LOCATION:Virtual: https://events.vtools.ieee.org/m/522134
ORGANIZER:allen.jones@ieee.org
SEQUENCE:43
SUMMARY:What Needs to Be in Place Before AI: Lessons from Large-Scale Insur
 ance Platforms
URL;VALUE=URI:https://events.vtools.ieee.org/m/522134
X-ALT-DESC:Description: <br /><p><span style="font-size: 12.0pt\; font-fami
 ly: 'Aptos'\,sans-serif\; mso-fareast-font-family: Aptos\; mso-fareast-the
 me-font: minor-latin\; mso-bidi-font-family: Aptos\; mso-font-kerning: 0pt
 \; mso-ligatures: none\; mso-ansi-language: EN-US\; mso-fareast-language: 
 EN-US\; mso-bidi-language: AR-SA\;"><strong>This meeting was recorded. You
  can find the recording at</strong> </span><a href="https://youtu.be/S1e8W
 bYj7Vw"><span style="font-size: 12.0pt\; font-family: 'Aptos'\,sans-serif\
 ; mso-fareast-font-family: Aptos\; mso-fareast-theme-font: minor-latin\; m
 so-bidi-font-family: Aptos\; mso-font-kerning: 0pt\; mso-ligatures: none\;
  mso-ansi-language: EN-US\; mso-fareast-language: EN-US\; mso-bidi-languag
 e: AR-SA\;">https://youtu.be/S1e8WbYj7Vw</span></a></p>\n<p><span style="f
 ont-size: 12.0pt\; font-family: 'Aptos'\,sans-serif\; mso-fareast-font-fam
 ily: Aptos\; mso-fareast-theme-font: minor-latin\; mso-bidi-font-family: A
 ptos\; mso-font-kerning: 0pt\; mso-ligatures: none\; mso-ansi-language: EN
 -US\; mso-fareast-language: EN-US\; mso-bidi-language: AR-SA\;">Artificial
  intelligence can only create real value when the underlying data\, archit
 ecture\, and governance are ready for it. In this talk\, as a system archi
 tect I will share practical lessons from experience of designing and leadi
 ng large-scale insurance platforms at three startup insurance companies\, 
 including quoting engines\, carrier integrations\, and cloud-native lead a
 cquisition systems. Drawing on two decades of experience in insurance tech
 nology\, I will outline four key prerequisites for successful AI adoption 
 in regulated industries: solid data foundations\, modular and API-driven a
 rchitectures\, strong security and compliance practices\, and cross-functi
 onal teams and processes. The session is aimed at students\, engineers\, A
 I practitioners\, and business leaders who want a clear\, real-world view 
 of how to prepare complex systems for AI at scale.</span></p>
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