The New Data Economy Transistor (https://transistor.fm) https://feeds.transistor.fm/the-new-data-economy This is The New Data Economy. Every episode, we sit down with the operators, innovators, and executives who are living at the intersection of AI, data, and customer trust. Listen to the people who are making real decisions about how to build with AI responsibly, how to earn and keep customer trust, and what it means to compete in an economy where data is the primary resource and permission is the primary constraint. The New Data Economy is brought to you by Transcend. © 2026 Transcend fa45a3a8-4725-55d4-8e8a-30248627a6ec yes The New Data Economy Trailer! en Wed, 21 Oct 2026 05:00:20 -0400 Wed, 21 Oct 2026 05:05:11 -0400 http://newdataeconomy.com https://img.transistorcdn.com/cH2a4hI_A2bj3VCD0s7dgjmDLMgULelngxSSat5YgoM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS84YzQx/NzBiM2U0ZjAxNmYx/ZTIxYzMwOWNmOTY4/YzY3MC5wbmc.jpg The New Data Economy http://newdataeconomy.com episodic Transcend This is The New Data Economy. Every episode, we sit down with the operators, innovators, and executives who are living at the intersection of AI, data, and customer trust. Listen to the people who are making real decisions about how to build with AI responsibly, how to earn and keep customer trust, and what it means to compete in an economy where data is the primary resource and permission is the primary constraint. The New Data Economy is brought to you by Transcend. This is The New Data Economy. Transcend newdataeconomy@ringmaster.com No No Data Is the New Oil, But Only If It's Clean with Abbey Keck - The New Data Economy 3 3 Data Is the New Oil, But Only If It's Clean with Abbey Keck - The New Data Economy full fb9bd6ef-7ee5-4993-8250-9e8d5094de84 https://share.transistor.fm/s/b286829c Abbey Keck has spent her career sitting at the intersection of product, data, and privacy, building foundational teams and products at companies like Walmart, Google, Facebook, and Oracle. In this episode, she joins Kate Parker to unpack what she calls the shift from collecting as much data as possible to actually knowing how to use it well. Abbey explains why the old data lake mentality is giving way to a cleanup phase, where companies are learning to prioritize clean, proprietary, well understood data over sheer volume.


The conversation covers how consent, transparency, and clear value trade offs build long term trust with customers, why AI works best when it's fed high quality data rather than treated as a shortcut to expertise, and how privacy, product, analytics, and operations teams are increasingly collaborating instead of working in silos. Abbey also shares how her love of escape rooms and scavenger hunts shaped the way she approaches problem solving in her day to day work.


Takeaways:

  • Shift your data strategy from collecting everything to use intentionally. The real value now comes from proprietary, well understood data rather than sheer volume.
  • Treat data cleanup as an ongoing parallel workstream, not a pause button. Run cleanup alongside innovation and A/B testing rather than choosing one over the other.
  • Use consent and transparency as trust building tools. Clearly communicating the value trade off of data collection makes customers more comfortable and more forgiving.
  • Let your analytics and data science teams tell the full story, including the bad news. Surfacing messy or low quality data early prevents flawed business decisions down the line.
  • Use AI to extend expertise, not replace it. AI works best when it helps existing experts test ideas and bridge gaps between disciplines rather than standing in for real knowledge.
  • Break down silos between privacy, product, analytics, and operations. Cross functional collaboration leads to faster, more informed decisions and stronger products.
  • When presenting data strategy to leadership, connect it directly to revenue and long term customer relationships, not just protection and compliance.

Quote of the Show:

  • "It's the ability to actually have a relationship with your customer and allow you to collect more, but of the right thing. That's maybe the most valuable now, because it's unique to you." - Abbey Keck


Links:


Ways to Tune In:

]]> Abbey Keck has spent her career sitting at the intersection of product, data, and privacy, building foundational teams and products at companies like Walmart, Google, Facebook, and Oracle. In this episode, she joins Kate Parker to unpack what she calls the shift from collecting as much data as possible to actually knowing how to use it well. Abbey explains why the old data lake mentality is giving way to a cleanup phase, where companies are learning to prioritize clean, proprietary, well understood data over sheer volume.


The conversation covers how consent, transparency, and clear value trade offs build long term trust with customers, why AI works best when it's fed high quality data rather than treated as a shortcut to expertise, and how privacy, product, analytics, and operations teams are increasingly collaborating instead of working in silos. Abbey also shares how her love of escape rooms and scavenger hunts shaped the way she approaches problem solving in her day to day work.


Takeaways:

  • Shift your data strategy from collecting everything to use intentionally. The real value now comes from proprietary, well understood data rather than sheer volume.
  • Treat data cleanup as an ongoing parallel workstream, not a pause button. Run cleanup alongside innovation and A/B testing rather than choosing one over the other.
  • Use consent and transparency as trust building tools. Clearly communicating the value trade off of data collection makes customers more comfortable and more forgiving.
  • Let your analytics and data science teams tell the full story, including the bad news. Surfacing messy or low quality data early prevents flawed business decisions down the line.
  • Use AI to extend expertise, not replace it. AI works best when it helps existing experts test ideas and bridge gaps between disciplines rather than standing in for real knowledge.
  • Break down silos between privacy, product, analytics, and operations. Cross functional collaboration leads to faster, more informed decisions and stronger products.
  • When presenting data strategy to leadership, connect it directly to revenue and long term customer relationships, not just protection and compliance.

Quote of the Show:

  • "It's the ability to actually have a relationship with your customer and allow you to collect more, but of the right thing. That's maybe the most valuable now, because it's unique to you." - Abbey Keck


Links:


Ways to Tune In:

]]> Wed, 21 Oct 2026 05:00:00 -0400 Transcend Watch on YouTube Transcend 2862 Abbey Keck has spent her career sitting at the intersection of product, data, and privacy, building foundational teams and products at companies like Walmart, Google, Facebook, and Oracle. In this episode, she joins Kate Parker to unpack what she calls the shift from collecting as much data as possible to actually knowing how to use it well. Abbey explains why the old data lake mentality is giving way to a cleanup phase, where companies are learning to prioritize clean, proprietary, well understood data over sheer volume.


The conversation covers how consent, transparency, and clear value trade offs build long term trust with customers, why AI works best when it's fed high quality data rather than treated as a shortcut to expertise, and how privacy, product, analytics, and operations teams are increasingly collaborating instead of working in silos. Abbey also shares how her love of escape rooms and scavenger hunts shaped the way she approaches problem solving in her day to day work.


Takeaways:

  • Shift your data strategy from collecting everything to use intentionally. The real value now comes from proprietary, well understood data rather than sheer volume.
  • Treat data cleanup as an ongoing parallel workstream, not a pause button. Run cleanup alongside innovation and A/B testing rather than choosing one over the other.
  • Use consent and transparency as trust building tools. Clearly communicating the value trade off of data collection makes customers more comfortable and more forgiving.
  • Let your analytics and data science teams tell the full story, including the bad news. Surfacing messy or low quality data early prevents flawed business decisions down the line.
  • Use AI to extend expertise, not replace it. AI works best when it helps existing experts test ideas and bridge gaps between disciplines rather than standing in for real knowledge.
  • Break down silos between privacy, product, analytics, and operations. Cross functional collaboration leads to faster, more informed decisions and stronger products.
  • When presenting data strategy to leadership, connect it directly to revenue and long term customer relationships, not just protection and compliance.

Quote of the Show:

  • "It's the ability to actually have a relationship with your customer and allow you to collect more, but of the right thing. That's maybe the most valuable now, because it's unique to you." - Abbey Keck


Links:


Ways to Tune In:

]]> No From Risk to Speed with Aimee Cardwell - The New Data Economy 2 2 From Risk to Speed with Aimee Cardwell - The New Data Economy full d544f143-4fa5-44c8-b4c4-a262a8cc870e https://share.transistor.fm/s/11aeeeb6 Aimee Cardwell has spent her career inside some of the most regulated industries in the country, from American Express to UnitedHealth Group, and she brings that vantage point to a candid conversation about what it actually takes to compete in the new data economy. She unpacks why treating data as a true asset (not just a byproduct of doing business) is the difference between companies that lead and companies that lag, and she explains the concept of consent events, a practical way for regulated companies to build direct, permissioned relationships with their customers.


The conversation also digs into how boards have shifted their thinking on AI over the past year, moving from a posture of pure risk avoidance to one that weighs the existential risk of moving too slowly. Aimee shares real world examples from healthcare, financial services, and her own board experience, along with candid advice for leaders trying to balance compliance with the need to move fast.


Takeaways:

  • Treat data as a strategic asset rather than a byproduct of serving customers, especially in industries with fragmented, acquisition heavy data environments
  • Build consent events into your customer relationships so you earn the right to communicate directly, opening the door to new products and offers down the line
  • Recognize that many companies are only using a small percentage of their data because they are unsure how to get proper consent, and that is a solvable problem
  • Understand that different data types (care data versus marketing data, for example) come with different rules, so know what each dataset is actually cleared to be used for
  • Put a prompt redactor in place before scaling AI use so you have auditability and confidence around PHI and PII without shutting down experimentation
  • Recognize that legacy review processes (security, legal, vendor evaluation) were built for a slower era and may need to be redesigned to match the speed AI now demands
  • Reframe the boardroom conversation from "what is the risk of moving fast" to "what is the risk of not moving fast enough"

Quote of the Show:

  • “It's a distinction without a difference, really. If you're being really safe and if you're going really slow, then you're losing out because your competitors are going faster." - Aimee Cardwell


Links:


Ways to Tune In:


]]> Aimee Cardwell has spent her career inside some of the most regulated industries in the country, from American Express to UnitedHealth Group, and she brings that vantage point to a candid conversation about what it actually takes to compete in the new data economy. She unpacks why treating data as a true asset (not just a byproduct of doing business) is the difference between companies that lead and companies that lag, and she explains the concept of consent events, a practical way for regulated companies to build direct, permissioned relationships with their customers.


The conversation also digs into how boards have shifted their thinking on AI over the past year, moving from a posture of pure risk avoidance to one that weighs the existential risk of moving too slowly. Aimee shares real world examples from healthcare, financial services, and her own board experience, along with candid advice for leaders trying to balance compliance with the need to move fast.


Takeaways:

  • Treat data as a strategic asset rather than a byproduct of serving customers, especially in industries with fragmented, acquisition heavy data environments
  • Build consent events into your customer relationships so you earn the right to communicate directly, opening the door to new products and offers down the line
  • Recognize that many companies are only using a small percentage of their data because they are unsure how to get proper consent, and that is a solvable problem
  • Understand that different data types (care data versus marketing data, for example) come with different rules, so know what each dataset is actually cleared to be used for
  • Put a prompt redactor in place before scaling AI use so you have auditability and confidence around PHI and PII without shutting down experimentation
  • Recognize that legacy review processes (security, legal, vendor evaluation) were built for a slower era and may need to be redesigned to match the speed AI now demands
  • Reframe the boardroom conversation from "what is the risk of moving fast" to "what is the risk of not moving fast enough"

Quote of the Show:

  • “It's a distinction without a difference, really. If you're being really safe and if you're going really slow, then you're losing out because your competitors are going faster." - Aimee Cardwell


Links:


Ways to Tune In:


]]> Wed, 07 Oct 2026 05:00:00 -0400 Transcend Watch on YouTube Transcend 2891 Aimee Cardwell has spent her career inside some of the most regulated industries in the country, from American Express to UnitedHealth Group, and she brings that vantage point to a candid conversation about what it actually takes to compete in the new data economy. She unpacks why treating data as a true asset (not just a byproduct of doing business) is the difference between companies that lead and companies that lag, and she explains the concept of consent events, a practical way for regulated companies to build direct, permissioned relationships with their customers.


The conversation also digs into how boards have shifted their thinking on AI over the past year, moving from a posture of pure risk avoidance to one that weighs the existential risk of moving too slowly. Aimee shares real world examples from healthcare, financial services, and her own board experience, along with candid advice for leaders trying to balance compliance with the need to move fast.


Takeaways:

  • Treat data as a strategic asset rather than a byproduct of serving customers, especially in industries with fragmented, acquisition heavy data environments
  • Build consent events into your customer relationships so you earn the right to communicate directly, opening the door to new products and offers down the line
  • Recognize that many companies are only using a small percentage of their data because they are unsure how to get proper consent, and that is a solvable problem
  • Understand that different data types (care data versus marketing data, for example) come with different rules, so know what each dataset is actually cleared to be used for
  • Put a prompt redactor in place before scaling AI use so you have auditability and confidence around PHI and PII without shutting down experimentation
  • Recognize that legacy review processes (security, legal, vendor evaluation) were built for a slower era and may need to be redesigned to match the speed AI now demands
  • Reframe the boardroom conversation from "what is the risk of moving fast" to "what is the risk of not moving fast enough"

Quote of the Show:

  • “It's a distinction without a difference, really. If you're being really safe and if you're going really slow, then you're losing out because your competitors are going faster." - Aimee Cardwell


Links:


Ways to Tune In:


]]> No Trust as Currency with Serge Kajirian – The New Data Economy 1 1 Trust as Currency with Serge Kajirian – The New Data Economy full 2baacd69-8f1f-4112-8e14-daafb4f83651 https://share.transistor.fm/s/dca8ed0f Serge Kajirian leads data governance and privacy operations at Universal Music Group, the world's largest music company, where he oversees the most valuable catalog on Earth and the fan relationships tied to hundreds of labels and artists. With more than fifteen years of experience across media and entertainment, including stops at Disney Interactive and Fox Network Group, Serge sits at the exact intersection this show is built around: rights, permissions, fan trust, and AI.


In this episode, Serge unpacks how UMG values not just its recordings but the metadata and fandom information collected over decades. He walks through the concept of ring fencing as a governance tool, why trust functions as the true currency behind data sharing, and how AI is forcing the entire music industry to build new semantic layers of understanding. The conversation wraps with a look back at Serge's path through Disney and Fox before landing in music, plus the advice he'd give his younger self.

 

Takeaways:

  • Treat metadata and fandom information as core business assets, not just a byproduct of streaming, and build governance around them from the start.
  • Use ring fencing as a permissioning mechanism so labels and artists can share data safely without exposing it to competitors.
  • Establish clear ownership before building stewardship models. Know who owns the data, the music rights, and the marketing rights before deciding how to share any of it.
  • Treat trust as the real currency behind data sharing. One broken agreement can cause an entire ecosystem to stop participating.
  • Build documented runbooks so both people and AI systems understand the boundaries and rules of engagement.
  • Recognize AI as a new type of actor inside your data ecosystem, one that requires its own access controls, fact checking, and semantic layers.
  • Give fans and artists real input into how their data and preferences get used instead of assuming default consent.


Quote of the Show:


“Trust is the currency. The data has value if everyone in our ecosystem trusts it." - Serge Kajirian


Links:


Ways to Tune In:


]]> Serge Kajirian leads data governance and privacy operations at Universal Music Group, the world's largest music company, where he oversees the most valuable catalog on Earth and the fan relationships tied to hundreds of labels and artists. With more than fifteen years of experience across media and entertainment, including stops at Disney Interactive and Fox Network Group, Serge sits at the exact intersection this show is built around: rights, permissions, fan trust, and AI.


In this episode, Serge unpacks how UMG values not just its recordings but the metadata and fandom information collected over decades. He walks through the concept of ring fencing as a governance tool, why trust functions as the true currency behind data sharing, and how AI is forcing the entire music industry to build new semantic layers of understanding. The conversation wraps with a look back at Serge's path through Disney and Fox before landing in music, plus the advice he'd give his younger self.

 

Takeaways:

  • Treat metadata and fandom information as core business assets, not just a byproduct of streaming, and build governance around them from the start.
  • Use ring fencing as a permissioning mechanism so labels and artists can share data safely without exposing it to competitors.
  • Establish clear ownership before building stewardship models. Know who owns the data, the music rights, and the marketing rights before deciding how to share any of it.
  • Treat trust as the real currency behind data sharing. One broken agreement can cause an entire ecosystem to stop participating.
  • Build documented runbooks so both people and AI systems understand the boundaries and rules of engagement.
  • Recognize AI as a new type of actor inside your data ecosystem, one that requires its own access controls, fact checking, and semantic layers.
  • Give fans and artists real input into how their data and preferences get used instead of assuming default consent.


Quote of the Show:


“Trust is the currency. The data has value if everyone in our ecosystem trusts it." - Serge Kajirian


Links:


Ways to Tune In:


]]> Wed, 23 Sep 2026 05:00:00 -0400 Transcend Watch on YouTube Transcend 2620 Serge Kajirian leads data governance and privacy operations at Universal Music Group, the world's largest music company, where he oversees the most valuable catalog on Earth and the fan relationships tied to hundreds of labels and artists. With more than fifteen years of experience across media and entertainment, including stops at Disney Interactive and Fox Network Group, Serge sits at the exact intersection this show is built around: rights, permissions, fan trust, and AI.


In this episode, Serge unpacks how UMG values not just its recordings but the metadata and fandom information collected over decades. He walks through the concept of ring fencing as a governance tool, why trust functions as the true currency behind data sharing, and how AI is forcing the entire music industry to build new semantic layers of understanding. The conversation wraps with a look back at Serge's path through Disney and Fox before landing in music, plus the advice he'd give his younger self.

 

Takeaways:

  • Treat metadata and fandom information as core business assets, not just a byproduct of streaming, and build governance around them from the start.
  • Use ring fencing as a permissioning mechanism so labels and artists can share data safely without exposing it to competitors.
  • Establish clear ownership before building stewardship models. Know who owns the data, the music rights, and the marketing rights before deciding how to share any of it.
  • Treat trust as the real currency behind data sharing. One broken agreement can cause an entire ecosystem to stop participating.
  • Build documented runbooks so both people and AI systems understand the boundaries and rules of engagement.
  • Recognize AI as a new type of actor inside your data ecosystem, one that requires its own access controls, fact checking, and semantic layers.
  • Give fans and artists real input into how their data and preferences get used instead of assuming default consent.


Quote of the Show:


“Trust is the currency. The data has value if everyone in our ecosystem trusts it." - Serge Kajirian


Links:


Ways to Tune In:


]]> No The New Data Economy Trailer! 1 1 The New Data Economy Trailer! trailer 7abc7d8e-5748-4018-98d7-9d5379aa8bcd https://share.transistor.fm/s/dcc958c9
The AI era is rewriting the rules of data, trust, and business growth. That's exactly why we're excited to announce the launch of the New Data Economy podcast!.

In every episode, hosts Mike Farrell, Co-Founder and CTO of Transcend, and Kate Parker, President of Transcend, sit down with the operators, innovators, and executives living at the intersection of AI, data, and customer trust. 

They’ll dive into conversations with the people who are making real decisions about how to build with AI responsibly, how to earn and keep customer trust, and what it means to compete in an economy where data is the primary resource and permission is the primary constraint.

New episodes drop every other Wednesday. Visit newdataeconomy.com and hear from the voices leading the future of data decisions.

]]>
The AI era is rewriting the rules of data, trust, and business growth. That's exactly why we're excited to announce the launch of the New Data Economy podcast!.

In every episode, hosts Mike Farrell, Co-Founder and CTO of Transcend, and Kate Parker, President of Transcend, sit down with the operators, innovators, and executives living at the intersection of AI, data, and customer trust. 

They’ll dive into conversations with the people who are making real decisions about how to build with AI responsibly, how to earn and keep customer trust, and what it means to compete in an economy where data is the primary resource and permission is the primary constraint.

New episodes drop every other Wednesday. Visit newdataeconomy.com and hear from the voices leading the future of data decisions.

]]> Thu, 17 Sep 2026 15:00:00 -0400 Transcend Watch on YouTube Transcend 39
The AI era is rewriting the rules of data, trust, and business growth. That's exactly why we're excited to announce the launch of the New Data Economy podcast!.

In every episode, hosts Mike Farrell, Co-Founder and CTO of Transcend, and Kate Parker, President of Transcend, sit down with the operators, innovators, and executives living at the intersection of AI, data, and customer trust. 

They’ll dive into conversations with the people who are making real decisions about how to build with AI responsibly, how to earn and keep customer trust, and what it means to compete in an economy where data is the primary resource and permission is the primary constraint.

New episodes drop every other Wednesday. Visit newdataeconomy.com and hear from the voices leading the future of data decisions.

]]> No