The business case for multimodal AI and automation

Media Thumbnail
00:00
00:00
1x
  • 0.5
  • 1
  • 1.25
  • 1.5
  • 1.75
  • 2
This is a podcast episode titled, The business case for multimodal AI and automation. The summary for this episode is: <p>In this episode of <em>Transformers</em>, Ann Funai sits down with Mark Polyak, Chief Product &amp; Technology Officer at MINT.ai, to explore how multimodal AI and intelligent automation are reshaping the future of work, marketing and human innovation.&nbsp;</p><p><br></p><p>Drawing from his background in counterterrorism and real-time data systems, Mark shares how data integrity, transparency and human oversight are essential to successful AI implementation. The conversation explores the shift to prescriptive analytics, the rise of agentic AI and how multimodal systems are driving workflow automation, a creative production boom, and business ROI.&nbsp;</p><p><br></p><p><em>Chapters</em>&nbsp;</p><p>&nbsp;</p><p>00:00 –&nbsp;From conflict zones to campaigns: Using data to get closer to truth&nbsp;</p><p>04:52 – Why data integrity matters: Guardrails, transparency and trust in AI systems &nbsp;</p><p>06:35 – Beyond descriptive: Unlocking prescriptive analytics for smarter business decisions&nbsp;</p><p>12:34 – Adapt or stagnate: The rise of multimodal AI and intelligent automation &nbsp;</p><p>15:33 – AI and the workforce: How technology is reshaping labor trends &nbsp;</p><p>21:20 – 3 ways AI is changing marketing: Automation, creativity and ROI&nbsp;</p><p>25:00 – Most AI solutions are failing: The role of trusted partners in driving real results&nbsp;</p><p>28:55 – The ‘glue’ role: Why business translators are essential to success with AI&nbsp;</p><p>31:44 – Responsible innovation in action: Building multiagentic AI with guardrails&nbsp;</p><p>36:20 – Spotting AI hype: How to tell real value from empty promises &nbsp;</p><p>39:55 – <em>Team of Teams: </em>Leadership lessons from high-security environments&nbsp;</p><p><br></p><p>&nbsp;</p><p><em>The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity.</em>&nbsp;</p>

DESCRIPTION

In this episode of Transformers, Ann Funai sits down with Mark Polyak, Chief Product & Technology Officer at MINT.ai, to explore how multimodal AI and intelligent automation are reshaping the future of work, marketing and human innovation. 


Drawing from his background in counterterrorism and real-time data systems, Mark shares how data integrity, transparency and human oversight are essential to successful AI implementation. The conversation explores the shift to prescriptive analytics, the rise of agentic AI and how multimodal systems are driving workflow automation, a creative production boom, and business ROI. 


Chapters 

 

00:00 – From conflict zones to campaigns: Using data to get closer to truth 

04:52 – Why data integrity matters: Guardrails, transparency and trust in AI systems  

06:35 – Beyond descriptive: Unlocking prescriptive analytics for smarter business decisions 

12:34 – Adapt or stagnate: The rise of multimodal AI and intelligent automation  

15:33 – AI and the workforce: How technology is reshaping labor trends  

21:20 – 3 ways AI is changing marketing: Automation, creativity and ROI 

25:00 – Most AI solutions are failing: The role of trusted partners in driving real results 

28:55 – The ‘glue’ role: Why business translators are essential to success with AI 

31:44 – Responsible innovation in action: Building multiagentic AI with guardrails 

36:20 – Spotting AI hype: How to tell real value from empty promises  

39:55 – Team of Teams: Leadership lessons from high-security environments 


 

The opinions expressed in this podcast are solely those of the participants and do not necessarily reflect the views of IBM or any other organization or entity. 

Today's Host

Guest Thumbnail

Ann Funai

|CIO & VP of Business Platform Transformation, IBM

Today's Guests

Guest Thumbnail

Mark Polyak

|Chief Product Technology Officer, MINT.ai