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How Core Values Drive Real AI Impact

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Manage episode 487066630 series 2833920
Content provided by Elevano. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Elevano or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In this episode of The Tech Trek, Brian Clifford, Chief Data Officer at Amica Insurance, shares how his team translates core company values—like exceptional customer service—into actionable AI and data strategies. We explore how Amica approaches pilots, vendor selection, internal adoption, and governance to scale AI effectively and responsibly.

🔑 Key Takeaways:

Value-Driven Data Strategy: Amica anchors its AI and data strategy in core values like customer service and employee engagement—not just tech for tech's sake.

Practical AI Implementation: Rather than chasing flashy use cases, Brian’s team prioritizes “easy wins” to build momentum and user trust.

Governance & Risk-Awareness: All AI initiatives go through structured cost-benefit reviews and risk assessments, especially critical for a legacy insurance firm.

Internal Enablement Is Key: The company invested heavily in internal L&D, communications, and peer communities to ensure scalable adoption of AI tools like Microsoft Copilot.

⏱ Timestamped Highlights:

[00:00] Intro to Brian Clifford, CDO at Amica; focus on AI, data, and company values.

[01:37] Defining Amica’s core values and how data supports customer satisfaction.

[03:35] Translating strategy into data initiatives; how priorities shape metrics.

[05:04] Taking a deliberate approach to AI—early POCs, team engagement, use cases.

[06:55] Why their first AI project failed—and why that was okay.

[09:52] Measuring value: usage, time saved, improved product quality.

[13:16] Governance model and how they assess AI tools before rollout.

[16:26] Year-long roadmap planning while maintaining flexibility for change.

[20:41] Upskilling the team: leveraging vendor training, L&D, and internal forums.

[23:08] Connect with Brian via LinkedIn.

💬 Quote to Share:

“We didn’t pick the hardest tech or the biggest value. We picked what we could deliver—and that built momentum.”

— Brian Clifford

📚 Resources Mentioned:

  • Microsoft Copilot – actively being used for internal productivity AI initiatives.
  • Internal Communities of Practice – Amica built internal forums to support peer learning and tool adoption.
  • AI Governance Committee – jointly led by the CDO and CIO to vet AI vendors and use cases.

💼 Career Tips from the Episode:

  • Focus on Practical Wins: Don’t aim for the most complex use case; start small, deliver value, and scale.
  • Change Management Matters: Opt-in AI adoption requires more internal marketing, trust-building, and education.
  • Learn Through Pilots: Treat all early tech initiatives as pilots. Be willing to pivot or shut things down if they don’t work.
  continue reading

472 episodes

Artwork
iconShare
 
Manage episode 487066630 series 2833920
Content provided by Elevano. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Elevano or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In this episode of The Tech Trek, Brian Clifford, Chief Data Officer at Amica Insurance, shares how his team translates core company values—like exceptional customer service—into actionable AI and data strategies. We explore how Amica approaches pilots, vendor selection, internal adoption, and governance to scale AI effectively and responsibly.

🔑 Key Takeaways:

Value-Driven Data Strategy: Amica anchors its AI and data strategy in core values like customer service and employee engagement—not just tech for tech's sake.

Practical AI Implementation: Rather than chasing flashy use cases, Brian’s team prioritizes “easy wins” to build momentum and user trust.

Governance & Risk-Awareness: All AI initiatives go through structured cost-benefit reviews and risk assessments, especially critical for a legacy insurance firm.

Internal Enablement Is Key: The company invested heavily in internal L&D, communications, and peer communities to ensure scalable adoption of AI tools like Microsoft Copilot.

⏱ Timestamped Highlights:

[00:00] Intro to Brian Clifford, CDO at Amica; focus on AI, data, and company values.

[01:37] Defining Amica’s core values and how data supports customer satisfaction.

[03:35] Translating strategy into data initiatives; how priorities shape metrics.

[05:04] Taking a deliberate approach to AI—early POCs, team engagement, use cases.

[06:55] Why their first AI project failed—and why that was okay.

[09:52] Measuring value: usage, time saved, improved product quality.

[13:16] Governance model and how they assess AI tools before rollout.

[16:26] Year-long roadmap planning while maintaining flexibility for change.

[20:41] Upskilling the team: leveraging vendor training, L&D, and internal forums.

[23:08] Connect with Brian via LinkedIn.

💬 Quote to Share:

“We didn’t pick the hardest tech or the biggest value. We picked what we could deliver—and that built momentum.”

— Brian Clifford

📚 Resources Mentioned:

  • Microsoft Copilot – actively being used for internal productivity AI initiatives.
  • Internal Communities of Practice – Amica built internal forums to support peer learning and tool adoption.
  • AI Governance Committee – jointly led by the CDO and CIO to vet AI vendors and use cases.

💼 Career Tips from the Episode:

  • Focus on Practical Wins: Don’t aim for the most complex use case; start small, deliver value, and scale.
  • Change Management Matters: Opt-in AI adoption requires more internal marketing, trust-building, and education.
  • Learn Through Pilots: Treat all early tech initiatives as pilots. Be willing to pivot or shut things down if they don’t work.
  continue reading

472 episodes

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