Enterprise GenAI Governance and Adoption Acceptance Lead

The mandate

The defined problem is that enterprise GenAI pilots lack a common route from promising capability to accepted operating use. Evaluation, permission, user behaviour and support ownership are being assessed separately. The consultant will build and test one governance and acceptance framework for agreed pilot families, not implement a new model platform.

Deliverables are a decision-rights model, evaluation and adoption criteria, and a pilot-to-service acceptance pack. The framework must identify who can authorise a use, what evidence is needed and how exceptions are resolved. It should remain proportionate: a low-consequence drafting aid and a consequential agent workflow cannot be approved through identical evidence requirements.

The six-month engagement starts on 19 October 2026 and finishes on 18 April 2027. Milestone one on 30 November provides the current-state decision map and pilot evidence inventory. Milestone two on 1 February delivers the framework and acceptance tests. Milestone three on 18 April provides validation across agreed pilots, revised guidance and operating-owner transfer. Four days weekly are reserved.

Acceptance is by the transformation sponsor and designated risk and service owners. They must process a fresh pilot through the framework, identify the required evidence and reach a documented stop, revise or accept decision. Tests must include an inadequate evaluation and a failed adoption prerequisite. A framework that always produces approval regardless of evidence will not be accepted.

The sponsor provides authorised pilot records, nominated users and access to risk and service representatives. Bengaluru is primary, with scheduled remote enterprise workshops. Model procurement, production implementation and legal certification are excluded. Additional pilot families with materially different risk or operating mechanics require scope approval; the fee buys a tested framework, not unlimited AI programme management.

What you will own

• Map existing pilot decisions and evidence gaps, identifying where authority, evaluation or service ownership is missing before proposing a governance route.
• Define proportionate acceptance criteria for agreed use families, connecting the evidence burden to consequence and operating reliance rather than model novelty alone.
• Build decision-rights and exception procedures that preserve risk and service approval boundaries, preventing the framework author from becoming an unauthorised deployment approver.
• Specify adoption tests that observe useful behaviour and human escalation, distinguishing positive user feedback from evidence that the workflow can be relied upon.
• Validate the framework on pilots with inadequate evaluation and failed prerequisites, recording whether users reach a defensible stop or revise decision.
• Revise guidance from observed owner execution, removing ambiguous steps and retaining the evidence that makes an acceptance judgement reproducible by a fresh service or risk owner.
• Transfer the acceptance pack and maintenance method through fresh-pilot processing, obtaining explicit ownership of criteria updates and unresolved framework limitations.

Candidate qualifications

• Demonstrate enterprise GenAI transformation or operating-model work beyond prototype delivery. Explain how evaluation, permissions and service ownership were connected before a use became operationally accepted.
• Show hands-on governance design with proportionate criteria. Candidates should describe two use cases requiring different evidence and explain why a uniform approval checklist would have been inadequate.
• Evidence adoption assessment that measured useful behaviour, escalation and operating reliability rather than satisfaction alone. Provide a failed prerequisite and the action recommended before scale.
• Show consulting delivery with real acceptance tests and internal owner transfer. Explain a framework step that failed during user execution and the revision made before sign-off.
• Be able to work with confidential evaluation and pilot records under controlled access. Proven AI practice scope, methodological clarity and authority discipline are required; the project does not confer legal certification, model procurement or production risk-acceptance powers. Provide a framework validation case where risk and service owners disagreed about acceptance. Explain how the evidence burden, consequence classification and decision authority were clarified, and how a fresh user later reached a defensible conclusion without asking the framework author to arbitrate.

Application

Applications for this mandate are received in one way only: through the India Board Terminal's application process. It is automated end to end. Your Executive Passport travels to the mandate holder in its confidential form, your answers to the three questions below are read before anything else in your file, and every stage that follows is recorded on your applications page.

There is no address to write to and no intermediary to call. The mandate holder reads what the Terminal delivers and nothing else, which is what keeps the process the same for every applicant and keeps your name out of it until you release it. Applications close on 12 October 2026. Mandate reference PCT-CON-2026-IND-10.