Change & Adoption Lead

Level / Location: GCB4/5 typical Various co-located with the FDT Tech

Sit within the FDT Tech team and close to users (business teams delivery pods transformation squads) as the accountable Change/Adoption Lead for rapid rollout and sustained adoption of AI-enabled solutions (including GenAI where in scope). Build and execute a change and adoption plan aligned to release incrementsturning real user needs into embedded ways of working quickly safely and repeatably. This role bridges product intent delivery execution and operational ownership accelerating time-to-value while ensuring solutions are trusted responsibly used and aligned to enterprise controls and guidance.

Reporting & stakeholders: Solid line into FDT Tech Lead / Delivery Lead. Strong day-to-day partnership with Product Owner(s) business SMEs and delivery pod leads on scope prioritisation and trade-offs. Close collaboration with operations frontline teams risk/compliance change training comms and support teams to ensure readiness and sustainable adoption. Engage with regional teams to identify champions/super-users and ensure materials land effectively across geographies.

Scope & authority: Accountable for shaping and owning the change strategy adoption approach and business readiness for AI-enabled prototypes and production-viable thin-slice releases close to users. Owns local change decisions required to deliver outcomes at pace within approved governance controls and communications standards. Authority includes defining adoption KPIs setting readiness gates (training/comms/SOP updates) coordinating champions networks and escalating material adoption risks policy/control gaps or operational readiness blockers

Role description & core accountabilities

This role exists because AI-enabled delivery changes behaviour trust and accountability not just screens and processes. Users need plain-language guidance on what AI can/cant do how to verify outputs and how responsibility remains with people. The Change/Adoption Lead keeps releases moving while ensuring adoption is measurable benefits are realised and responsible use is embedded into day-to-day operations.

Change strategy and stakeholder alignment - Build a change and adoption plan aligned to the release roadmap (who changes what changes when and why). Map stakeholders and impacted user groups; identify change champions/super-users across regions/teams. Shape the narrative: whats in it for me expected impacts on workload risk customer outcomes and controls.

User journey operating model and process change - Define the future-state process including hand-offs decision rights and escalation paths (especially important when AI introduces human-in-the-loop steps). Update SOPs/knowledge articles/playbooks and ensure operational ownership is clear. Ensure role impacts are managed (new tasks removed tasks new skills capacity shifts).

Training comms and enablement - Create role-based training (frontline operations risk support managers) with practical scenarios. Deliver communications: launch packs FAQs demo sessions what changed notes and release highlights. Build self-serve assets: short guides videos in-tool tips prompt guides and troubleshooting steps.

Adoption measurement and benefits realisation - Define adoption KPIs (active users frequency task completion rates time saved error reduction case deflection customer outcomes). Track benefits vs baseline and work with Product/Delivery to adjust backlog based on feedback and data. Run pulse checks and qualitative feedback loops (surveys floor-walks listening sessions).

Trust transparency and responsible use - Drive user trust by explaining AI limitations confidence cues and when to override or escalate. For GenAI: set safe usage guidance (what not to input how to verify outputs how citations/grounding works). Coordinate human-in-the-loop and decision accountability messaging-AI assists; people remain responsible.

Readiness cutover and hypercare - Own business readiness checkpoints for go-live: training completion comms sent SOPs updated champions in place. Coordinate hypercare: feedback intake incident themes quick-fix loop with the squad and comms for known issues.

Feedback to product and continuous improvement - Convert adoption barriers into actionable backlog items (UX friction unclear outputs missing integrations policy confusion). Ensure enhancements prioritise real user pain points and operational realities.

AI-specific responsibilities - Manage perceived risk and build confidence by addressing black box concerns with plain-language explainability examples and clear do/dont guidance. Drive behaviour change around verification by teaching users how to validate AI outputs (especially for GenAI) and how to report issues (hallucinations unsafe responses bias). Ensure enablement is policy-aware: guidance aligns with required controls (data handling customer information record keeping) and routes users to the correct procedures where needed.

HSBC Success Profile criticality for this role

Calibration rationale: This is a hands-on user-adjacent change role optimised for speed-to-value and sustained adoption of AI-enabled solutions. Core capabilities around customer centricity stakeholder alignment delivery discipline and pragmatic decision-making are Essential. Broader strategic leadership and talent stewardship are Desirable as the role contributes to scaling patterns and mentoring but does not typically own enterprise-wide strategy.

Experience Required

Change impact assessments and stakeholder maps consistently produced improving clarity on who is impacted and how.

Change & adoption plans aligned to release increments increasing readiness and reducing go-live friction.

Comms packs delivered (FAQs launch notes demos champion toolkit) that land well across regions and user groups.

Role-based training delivered with completion tracking and practical scenarios; users understand verification behaviours and safe usage.

SOPs/playbooks/knowledge articles updated with clear operating model and support ownership reducing confusion post-release.

Adoption dashboards established with benefits realisation tracking and a working feedback loop; measurable improvements in adoption and outcomes over time.

Recognised as a dependable embedded change partner who accelerates adoption while strengthening responsible AI use.