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AI Value Track Podcast - Episode 3
Manage episode 517286951 series 2794254
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
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
Manage episode 517286951 series 2794254
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
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
All episodes
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