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AI Value Track Podcast - Episode 3

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Manage episode 517286951 series 2794254
Content provided by ReThink Productivity. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ReThink Productivity 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://podcastplayer.com/legal.

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We weigh the real trade‑offs of building AI in‑house versus buying and configuring proven tools, and map a practical route from pilot to production without blowing the budget. Clear steps on data, governance, ethics, and IP help you create value you can measure.

  • Build vs buy decisions tied to strategy and IP
  • When generic problems justify off‑the‑shelf tools
  • Niche bottlenecks and owning differentiated capability
  • Real costs of talent, data architecture and compute
  • Governance, scope control and reliability expectations
  • Data quality, sourcing and security by design
  • Measurable pilots, baselines and explainability
  • EBITDA impact, inference costs and ROI discipline
  • Ethics beyond bias, oversight and customer impact
  • Partner contracts, IP protection and reuse limits
  • Scaling blockers across finance, compliance, HR and IT
  • Regulations to watch including EU AI Act and GDPR

#theproductivityexperts
Register for the 2026 Productivity Forum
Find us in the Top 50 Productivity Podcasts
Connect to Simon on LinkedIn
Follow ReThink on LinkedIn

  continue reading

Chapters

1. AI Value Track Podcast - Episode 3 (00:00:00)

2. Setting The Stakes: Build vs Buy (00:00:09)

3. Defining Build, Buy, And Configure (00:00:43)

4. Generic Problems Point To Buying (00:01:59)

5. When Bespoke Makes Strategic Sense (00:03:07)

6. Costs, Talent, And Infrastructure Reality (00:04:52)

7. Niche Use Cases And Monetisable IP (00:06:16)

8. Architecture, Governance, And Compute (00:08:49)

9. Data Quality, Sources, And Security (00:11:02)

10. Pilots, Metrics, And Explainability (00:12:53)

11. EBITDA, Inference Costs, And Run Rates (00:15:38)

12. Ethics, Oversight, And Communication (00:17:24)

13. Scope Control, Reliability, And SLAs (00:19:08)

14. From POC To Rollout: True Costs (00:21:06)

15. Protecting IP And Partner Contracts (00:22:44)

16. Scaling Blockers: Finance, Compliance, HR, IT (00:25:06)

17. Regulation Watch: EU AI Act And GDPR (00:27:17)

300 episodes

Artwork
iconShare
 
Manage episode 517286951 series 2794254
Content provided by ReThink Productivity. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by ReThink Productivity 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://podcastplayer.com/legal.

Send us a text

We weigh the real trade‑offs of building AI in‑house versus buying and configuring proven tools, and map a practical route from pilot to production without blowing the budget. Clear steps on data, governance, ethics, and IP help you create value you can measure.

  • Build vs buy decisions tied to strategy and IP
  • When generic problems justify off‑the‑shelf tools
  • Niche bottlenecks and owning differentiated capability
  • Real costs of talent, data architecture and compute
  • Governance, scope control and reliability expectations
  • Data quality, sourcing and security by design
  • Measurable pilots, baselines and explainability
  • EBITDA impact, inference costs and ROI discipline
  • Ethics beyond bias, oversight and customer impact
  • Partner contracts, IP protection and reuse limits
  • Scaling blockers across finance, compliance, HR and IT
  • Regulations to watch including EU AI Act and GDPR

#theproductivityexperts
Register for the 2026 Productivity Forum
Find us in the Top 50 Productivity Podcasts
Connect to Simon on LinkedIn
Follow ReThink on LinkedIn

  continue reading

Chapters

1. AI Value Track Podcast - Episode 3 (00:00:00)

2. Setting The Stakes: Build vs Buy (00:00:09)

3. Defining Build, Buy, And Configure (00:00:43)

4. Generic Problems Point To Buying (00:01:59)

5. When Bespoke Makes Strategic Sense (00:03:07)

6. Costs, Talent, And Infrastructure Reality (00:04:52)

7. Niche Use Cases And Monetisable IP (00:06:16)

8. Architecture, Governance, And Compute (00:08:49)

9. Data Quality, Sources, And Security (00:11:02)

10. Pilots, Metrics, And Explainability (00:12:53)

11. EBITDA, Inference Costs, And Run Rates (00:15:38)

12. Ethics, Oversight, And Communication (00:17:24)

13. Scope Control, Reliability, And SLAs (00:19:08)

14. From POC To Rollout: True Costs (00:21:06)

15. Protecting IP And Partner Contracts (00:22:44)

16. Scaling Blockers: Finance, Compliance, HR, IT (00:25:06)

17. Regulation Watch: EU AI Act And GDPR (00:27:17)

300 episodes

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