Topic starter
08/06/2026 4:33 pm
TL;DR: C1.ai finds that building identity governance in-house can cost more than three times as much as buying over five years once engineering, integration, maintenance, and infrastructure overhead are counted. The real risk is not just cost inflation but a governance model that lags human, non-human, and AI identity growth.
Editorial analysis by NHI Mgmt Group, based on content published by C1.ai: “Build vs. Buy for IGA: Why C1 Wins Every Time”.
Key questions
Q: How should teams decide whether to build or buy identity governance?
A: Teams should compare five-year total cost, connector effort, policy maintenance, and the business value of engineering time.
Q: Why does in-house IGA become more expensive over time?
A: In-house IGA accumulates cost because every integration, policy exception, bug fix, and platform change requires internal engineering time.
Q: What breaks when identity governance is coded from scratch?
A: What breaks first is usually maintainability.
Practitioner guidance
- Map total cost over five years Include engineering labour, connector maintenance, infrastructure hosting, testing, security updates, and the opportunity cost of diverting developers from core products.
- Inventory the identity and application graph first Document the applications, entitlements, nested relationships, and identity types the governance model must represent before you choose build or buy.
- Stress-test policy maintenance against change Model how often new apps, API changes, role exceptions, and certification rules will require code changes in a homegrown platform.
Bottom line: The article’s core warning is that identity governance build projects accumulate hidden work across development, integration, and maintenance.
What's in the full article
C1.ai's full blog covers the operational detail this post intentionally leaves for the source:
- Five reasons the vendor says buying beats building, including development, policy, integration, automation, and AI-scale arguments
- Examples of the connector and workflow burdens that in-house teams inherit when applications and APIs change
- The vendor’s framing of how its data model handles access paths, orphaned accounts, and nested entitlements
- The cost narrative behind the five-year total cost comparison, including the internal labour assumptions behind the build case
👉 Read C1.ai's build-vs-buy analysis for identity governance →
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This topic was modified 4 days ago by NHI Mgmt Group
08/06/2026 6:15 pm
Build-versus-buy is really a governance operating-model decision. The article is not just comparing price tags. It shows that the bigger question is whether identity governance should be treated as a bespoke internal platform or as a managed capability with ongoing lifecycle demands. For practitioners, the decisive issue is whether the organisation wants to own policy engineering forever.
A few things that frame the scale:
- Nearly 60% of IT leaders cite restrictive cost and complexity as a weakness of legacy identity governance, according to the 2025 State of Identity Governance Report.
A question worth separating out:
Q: What happens to IGA programmes when AI and non-human identities grow faster than the workforce?
A: Programmes built only for workforce users tend to run out of model headroom. They may still manage access, but only after repeated redesigns, new rules, and custom workflows for service accounts, workloads, and AI-driven identities. That slows governance and increases the chance that important access paths are missed.
👉 Read our full editorial: Build vs buy for IGA: what practitioners should weigh
This post was modified 4 days ago by NHI Mgmt Group