How DayBlink Consulting modernized a Non-Human Identity program at a Fortune 500 bank to meet the demands of agentic AI
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Introduction
A large bank was concerned that its identity program was not keeping pace as it accelerated adoption of AI agents, automation pipelines, and local LLMs. Its population of non-human identities (NHIs) such as service accounts, workload identities and agents was growing faster than the traditional IAM models built to govern them. Every new agent, MCP server, and CI/CD workflow introduced credentials that must be inventoried, scoped, rotated, and eventually retired.
For large financial institutions, the stakes are amplified. Regulators expect
demonstrable control over privileged access, yet many of the fastest growing identity types now originate at the edges of the enterprise: in developer tooling, agentic workflows, and locally run automation, often outside centralized IAM visibility.
To get ahead of this shift, the DayBlink Consulting team evaluated the NHI management program against the emerging frontier AI threat landscape, and delivered a defensible roadmap, grounded in evidence, for the next two years of NHI investment.
Problem
Our client’s strong IAM foundations were built before the rise of agentic AI, and leadership sought the better understand where and if this new identity risk required additional investment
The bank’s IAM organization had established many identity best practices that it was extending to NHI, including: inventory linkage, lifecycle controls, and Zero Trust principles, but the landscape was changing rapidly. AI agents, automation, and local execution models were materially increasing the number, autonomy, and privilege of non-human identities across the enterprise, frequently outside centralized IAM visibility and control.
The greatest exposure sat at the edges. Local MCP servers, developer tooling, CI/CD automation, and agentic workflows introduced identities that could bypass traditional governance, rely on locally stored credentials, and operate beyond existing detection and monitoring models. Meanwhile, governance and control patterns for agentic AI remained immature across the industry, providing no established playbook.
Leadership faced a prioritization challenge. Without a structured, empirical view of current NHI maturity, it was difficult to determine which gaps were acceptable, which demanded investment in process, tooling, or capacity, and how to sequence that investment credibly for executives, auditors, and regulators.
Solution
DayBlink Consulting built an empirically grounded NHI inventory, evaluated identity maturity, updated the team’s operating model, and then translated it into a prioritized two year roadmap
DayBlink Consulting partnered with the client to evaluate its NHI program through a structured analysis across three complementary methods, designed to ensure defensibility, traceability, and alignment to the scope owned by IAM.
First, we conducted discovery sessions with IAM leaders and technical experts across the cyber organization (spanning identity governance, secrets and credential management, PAM, cloud IAM and workload identity, and AI agent architecture and strategy) to validate operating model realities, tooling coverage, lifecycle friction points, and ownership boundaries.
Second, we performed a maturity assessment across five NHI management domains owned by IAM: Governance & Ownership, Inventory & Classification, Authentication & Credential Controls, Lifecycle Management, and Monitoring,
Visibility & Control Integration. Each capability was rated by implementation level to pinpoint where controls were
consistent and where gaps remained.
Third, we completed an inventory review of active initiatives, documenting backlog items and roadmap artifacts to validate current execution and avoid duplicative recommendations. We also benchmarked the client’s identity control set against a consolidated baseline derived from industry best practices and NIST 800-53r5 to assess coverage, consistency, and relative maturity.
Because agentic AI was the driving threat prompting this effort, we extended the analysis beyond traditional NHIs, mapping where LLM, agent, and local execution (MCP) risks converge, defining AI identity best practices across six domains, and evaluating control options spanning corporate, personal, and shadow AI usage.
The result was a prioritized 2026 to 2027 roadmap of 20+ initiatives, sequenced quarter by quarter across the five NHI management domains and validated with client leadership.
Outcome
We delivered a defensible NHI operating model and a two year roadmap that positions the bank to govern identities at AI scale
We provided the client with a complete NHI management operating model and control landscape, a maturity baseline backed by evidence, and a prioritized roadmap that leadership can defend in executive, audit, and regulatory conversations.
The engagement gave the organization a shared, structured language for NHI risk, clarifying which capabilities are strong, where identity types fall outside traditional governance boundaries, and how emerging AI identities differ from conventional service accounts in lifecycle, security, and governance needs.
The roadmap moves the program from reactive to deliberate. Initiatives are sequenced across six quarters and five management domains, from governance and inventory expansion through credential rotation automation, lifecycle integration, and unified monitoring. Each is traceable to an identified gap and validated against work already underway, ensuring no duplication of effort.
Critically, the analysis positions the bank ahead of the agentic AI curve. By defining AI identity best practices, mapping converged LLM, agent, and MCP risks, and evaluating control options across managed, unmanaged, and shadow usage, the client now has a framework for extending identity governance to AI systems as adoption scales.