Change & Adoption Lead

Sheffield, United Kingdom Posted on 11/06/2026

Level /Location GCB4/ 5 typical - Various -co-located with the FDTTech

She sit within the FDT Tech team and close to users (business teams, delivery pods, transformationsquads) as the accountable Change/Adoption Lead for rapidrollout and sustained adoption of AI-enabled solutions (including GenAI wherein scope). Build and execute a change and adoption plan aligned to releaseincrements-turning real user needs into embedded ways of working quickly,safely and repeatably. This role bridges product intent, delivery execution andoperational ownership, accelerating time-to-value while ensuring solutions aretrusted, responsibly used, and aligned to enterprise controls and guidance.

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

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

This role exists because AI-enableddelivery changes behaviour, trust and accountability, not just screens andprocesses. Users need plain-language guidance on what AI can/can't do, how toverify 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-dayoperations.

• Change strategy and stakeholder alignment - Build a change andadoption plan aligned to the release roadmap (who changes, what changes, when,and why). Map stakeholders and impacted user groups; identify changechampions/super-users across regions/teams. Shape the narrative: "what's in itfor me", expected impacts on workload, risk, customer outcomes, and controls.
• User journey, operating model, and process change - Define the future-stateprocess including hand-offs, decision rights, and escalation paths (especiallyimportant when AI introduces "human-in-the-loop" steps). Update SOPs/knowledgearticles/playbooks and ensure operational ownership is clear. Ensure roleimpacts 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 withProduct/Delivery to adjust backlog based on feedback and data. Run pulse checksand qualitative feedback loops (surveys, floor-walks, listening sessions).
• Trust, transparency, and responsible use -Drive user trust byexplaining AI limitations, confidence cues, and when to override or escalation 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 readinesscheckpoints 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 barriersinto actionable backlog items (UX friction, unclear outputs, missingintegrations, policy confusion). Ensure enhancements prioritise real user painpoints and operational realities.
• AI-specific responsibilities - Manage perceived risk and build confidence by addressing "black box" concerns withplain-language explainability, examples, and clear do/don't guidance. Drivebehaviour change around verification by teaching users how to validate AIoutputs (especially for GenAI) and how to report issues (hallucinations, unsaferesponses, bias). Ensure enablement is policy-aware: guidance aligns withrequired controls (data handling, customer information, record keeping) androutes users to the correct procedures where needed.

HSBC Success Profile - criticality for this role Criterion Criticality Experience Delivering change and adoption plansaligned to incremental releases

Stakeholder mapping andchampion/super-user network mobilisation

Training, comms and self-serve enablementtailored to roles and regions

Adoption measurement and benefitsrealisation (KPIs, baselines, feedback loops)

Future-state process / operating modelchange (handoffs, decision rights, escalation, ownership)

AI-specific enablement(trust/limitations, verification behaviours, responsible use guidance)

Capability Customer / Client Centricity

Judgment and decision-making

Influencing and stakeholder alignment

Championing innovation through rapiditeration

Strategic technical thinking

Inspirational Leadership

Talent stewardship

Personal Attributes Leadership Span

Calibration rationale This is a hands-on,user-adjacent change role optimised for speed-to-value and sustained adoptionof AI-enabled solutions. Core capabilities around customer centricity,stakeholder alignment, delivery discipline and pragmatic decision-making areEssential. Broader strategic leadership and talent stewardship are Desirable,as the role contributes to scaling patterns and mentoring but does nottypically own enterprise-wide strategy.

Experience - Required

• Proven experience delivering change and adoption fordigital products, including stakeholder mapping, comms, training and readinessplanning.
• Strong ability to align change plans to incrementaldelivery/release roadmaps and operate readiness gates (training completion, SOPupdates, champions in place).
• Experience designing future-state user journeys andoperating model/process changes (handoffs, decision rights, escalation paths)and clarifying ownership.
• Experience creating role-based enablement materials (FAQs,launch packs, demos, quick guides) and tailoring messaging across user groupsand regions.
• Experience defining adoption KPIs and benefits realisationmeasures, establishing baselines, and running feedback loops to refine thebacklog.
• Comfortable operating in ambiguous environments withshifting requirements, while maintaining delivery discipline and transparency.

Experience - Preferred

• Experience rolling out AI-enabled solutions, includingbuilding trust through explainability and "responsible use" guidance, andteaching verification behaviours.
• Experience delivering within regulated/controlledenvironments (risk, audit, security, data handling) and ensuring comms/trainingalign to required controls and procedures.
• Experience coordinating champion/super-user networks acrossregions/teams and using champions to accelerate adoption.
• Experience running hypercare and structured feedbackintake, converting themes into prioritised product improvements.
• Experience working in Value Streams / product-led delivery,transformation pods, or embedded/forward-deployed models.
• User-obsessed change partner; stays close to users, listenshard, and removes barriers to adoption.
• Pragmatic and outcomes-led; focuses on measurable adoptionand benefits, not just activity (emails sent, training delivered).
• Clear communicator under pressure; explains what'schanging, why, and what users need to do in plain language.
• Trust builder; acknowledges limitations, encouragesverification, and reinforces responsible decision accountability.
• Collaborative and inclusive; works well across roles,regions and backgrounds; welcomes different perspectives to improve enablement.
• Proactive risk management; identifies adoption, process,and policy/control risks early; escalates with options, not surprises.

Derailers / red flags

• Treats adoption as a launch event rather than a sustainedbehaviour change effort with measurement and iteration.
• Over-indexes on generic comms/training and fails to reflectreal workflows, roles/entitlements, or regional realities.
• Avoids discussing AI limitations, leading to misplacedtrust, misuse or disengagement.
• Fails to connect enablement to required controls (datahandling, record keeping), creating audit or compliance issues.
• Lacks an adoption baseline or measurable KPIs; cannotdemonstrate benefits realisation.
• Fails to establish clear operational ownership, leaving a"who owns this now?" gap post go-live.

• Change impact assessments and stakeholder maps consistentlyproduced, improving clarity on who is impacted and how click apply for full job details