Innovation and Process Governance Lead

<p><strong>Role: Innovation and Process Governance Lead</strong></p><p>The Innovation and Process Governance Lead is responsible to drive the client’s AI innovation roadmap to transform traditional end-user computing services to new generation of AI centric services and automation while establishing robust governance, risk, and process management frameworks. The role blends innovation leadership and ITIL/ITSM process governance to ensure AI-enabled solutions are achieving the expected outcomes, compliant, and deliver measurable business value back to the client.</p><p><strong>Key responsibilities</strong></p><ul><li>Support client stakeholders to deliver the enterprise AI innovation roadmap, aligned to business strategy, digital transformation, and operations priorities.</li><li>Work with domain experts to identify, qualify, and prioritize AI/automation use cases across functions (operations, service delivery, customer experience, back office), including GenAI, copilots, intelligent workflows, and analytics.</li><li>Lead discovery and design workshops with business and IT stakeholders to translate problem statements into AI-enabled solution concepts, PoCs, and scalable patterns.</li><li>Establish and maintain the AI governance framework covering use‑case intake, risk assessment, approvals, model lifecycle controls, and compliance with internal policies and regulations.</li><li>Ensure guardrails for responsible AI (data usage, security, privacy, bias, explainability, human-in-the-loop) are embeded into processes, templates, and technical platforms.</li><li>Set enterprise standards for AI and automation process design, documentation, and change control (playbooks, SOPs, process maps, RACI, decision trees).</li><li>Design and run intake, evaluation, and approval processes for new AI initiatives, ensuring alignment to architecture, security, and risk guidelines.</li><li>Drive Digital Employee Experience (DEX) strategy, governance, and reporting to support data-driven service improvements.</li><li>Define KPIs and scorecards to track AI portfolio value (productivity, experience, quality, risk reduction) and process maturity/compliance across domains.</li><li>Lead cross-functional change management for AI adoption with client stakeholders, including communications, training, and stakeholder engagement for new ways of working.</li><li>Ensure integration of AI solutions into existing ITSM and transform operational processes (incident, problem, change, knowledge, request) to new ways of working, including operating model and RACI updates.</li><li>Oversee the creation and maintenance of a central repository of AI use cases, models, process assets, standards, and lessons learned.</li><li>Assess external trends, regulatory developments, and vendor capabilities supported by domain experts to continuously evolve internal AI and process governance practices.</li></ul><p><strong>AI Innovation & Orchestration</strong></p><ul><li>Provide the framework to ensure AI innovation and orchestration outputs are aligned with AI transformation roadmap goals.</li><li>Identify use cases for AI innovation such as low complexity/high volume tickets, ticket summarization, AI-assisted agent, knowledge base for faster triage/resolution.</li><li>Design end-to-end orchestration with domain experts to achieve proactive detection, auto-remediation and smart routing of issues to reduce human interventions.</li><li>Scale and refine workflows to unlock automation benefits with each level of AI maturity and adoption level.</li></ul><p><strong>ITIL Process Governance</strong></p><ul><li>Own ITIL process governance for incident, request, problem, change, knowledge, CMDB, and service level management practices.</li><li>Define process policies, RACI, standards ensuring clear accountabilities across teams.</li><li>Embed AI/automation into ITIL processes (triage, routing, remediation) with safeguards.</li><li>Ensure that process docs (maps, SIPOCs, SOPs) are kept current, versioned, auditable.</li><li>Analyse ITSM KPIs/SLAs/OLAs (MTTR, FCR, change success) and drive off-track improvements.</li><li>Mitigate process risks (e.g., unauthorized changes, poor routing) via controls/training.</li></ul><p><strong>Knowledge & Self-Service (KCS)</strong></p><ul><li>Build Knowledge-Centred Service framework for AI-powered self-service.</li><li>Create/maintain validated KB articles enabling self-resolution and automation.</li><li>Use KCS analytics to identify high-value automation opportunities.</li><li>Ensure continuous improvement keeps self-service/automation current/scalable.</li></ul><p><strong>Stakeholder management</strong></p><ul><li>Work closely with CDO/CIO/CTO, business leaders, risk, legal, compliance, and security to align AI initiatives with enterprise strategy and risk appetite.</li><li>Partner with service delivery, operations, and product teams to embed AI into day‑to‑day workflows and ensure sustainable ownership post‑implementation.</li><li>Collaborate with architecture and platform teams to standardize on approved AI platforms, tools, and patterns, avoiding fragmentation and shadow IT.</li><li>Engage with HR and Learning teams to design capability-building programs on AI literacy, responsible AI, and standardized process practices for different role groups.</li><li>Manage relationships with key AI, cloud, and automation vendors, ensuring solutions comply with governance requirements and contractual obligations.</li></ul><p><strong>Required experience and qualifications</strong></p><ul><li>Bachelor’s Degree in Information Systems, Computer Science or equivalent.</li><li>At least 10 years’ experience in IT/digital/AI/service management with 5+ years leadership role.</li><li>Led AI/automation/DEX initiatives end-to-end in large scale end user computing environments using tools such as ServiceNow and Tanium DEX.</li><li>Strong background in process management or ITSM (e.g., ITIL, BPM, Lean/Six Sigma), including designing and governing cross-functional processes.</li><li>Practical understanding of AI/ML concepts, GenAI, data platforms, and MLOps practices (model lifecycle, monitoring, retraining, observability).</li><li>Experience establishing governance frameworks, policies, and standards, preferably covering technology, data, risk, or compliance domains.</li><li>Proven ability to lead cross-functional teams and influence senior stakeholders without direct authority.</li><li>Excellent communication skills, with the ability to explain complex AI concepts and risk considerations in business language.</li></ul><p><strong>Competencies and attributes</strong></p><ul><li>Strategic and innovative mindset with strong analytical and problem-solving skills.</li><li>Strong governance orientation, with attention to detail in controls, documentation, and auditability.</li><li>High level of stakeholder empathy and change leadership capability to drive behavior change and adoption of new processes.</li></ul><p></p>

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