AI Strategy & Enablement Consultant

We're building out our Enterprise Modernisation and AI capabilities and we're looking for an AI Strategy & Enablement Consultant who can help clients turn AI potential into practical business opportunities, structured initiatives and sustainable adoption.

You won't be expected to write production code or independently define enterprise AI strategy. You will connect business needs, stakeholder insight, process understanding, AI opportunity discovery and delivery requirements into clear, actionable outcomes.

Purpose

The AI Strategy & Enablement Consultant is a client-facing role supporting the Enterprise Modernisation and AI teams. The role combines business analysis, consulting and AI advisory capabilities to help organisations identify, prioritise and progress AI opportunities.

The core mission is to translate business challenges into practical AI use cases and enable clients to move from interest and experimentation towards structured, responsible and value-focused adoption.

Working alongside AI strategists, solution architects, delivery leads and client stakeholders, the consultant will:

• Demystify AI and Generative AI in clear, business-relevant language.
• Support AI opportunity discovery, use-case definition and prioritisation.
• Gather, analyse and document business requirements, processes and stakeholder needs.
• Contribute to AI maturity assessments, strategies, roadmaps and adoption plans.
• Translate business needs into structured inputs for solution and delivery teams.
• Support responsible AI, governance, change and value-realisation activities.

Key Responsibilities

Demystifying AI & Business Enablement

• Support the design and delivery of AI and GenAI awareness, discovery and enablement sessions.
• Explain core AI concepts, capabilities, limitations, risks and value levers in practical business language.
• Research and prepare relevant industry examples, use cases and discussion material.
• Adapt content to the client context, maturity, priorities and audience.

AI Opportunity Discovery & Use-Case Shaping

• Facilitate or co-facilitate discovery workshops with cross-functional stakeholders.
• Analyse business challenges, processes, pain points and opportunities for AI-enabled improvement.
• Capture and structure potential AI use cases using agreed templates and canvases.
• Assess use cases against business value, feasibility, data readiness, risk, adoption and change impact.
• Support prioritisation backlogs and develop clear use-case narratives, problem statements and expected outcomes.

Business Analysis & Requirements Definition

• Plan and conduct stakeholder interviews, workshops and requirements-gathering activities.
• Document current-state and future-state processes, user journeys, business rules and requirements.
• Translate business needs into clear artefacts for architecture, product, data and delivery teams.
• Support the definition of acceptance criteria, success measures and traceability from problem to outcome.
• Identify dependencies, assumptions, constraints, risks and information gaps.

AI Strategy, Maturity & Roadmap Support

• Contribute research, analysis and structured insights to AI strategy and maturity engagements.
• Support baseline assessments covering business readiness, data, technology, governance, people and adoption.
• Assist in developing practical AI roadmaps that sequence opportunities, foundations and enablement activities.
• Prepare client-ready recommendations, presentations and decision material.
• Maintain roadmaps, initiative backlogs, action registers and supporting documentation.

Solution & Delivery Enablement

• Work with strategists, architects and technical specialists to translate prioritised use cases into solution requirements.
• Support problem framing, user-journey definition, data-readiness analysis and solution option assessment.
• Participate in proof-of-concept, pilot and mobilisation activities.
• Support evaluation planning, user acceptance, feedback gathering and continuous improvement.
• Help maintain alignment between the original business need, proposed solution and intended value.

Responsible AI, Governance & Risk Support

• Apply awareness of privacy, security, model risk, bias, explainability and human oversight when shaping use cases.
• Support the documentation of governance requirements, decision points, controls and escalation paths.
• Coordinate input from business, risk, legal, compliance, security and technical stakeholders.
• Ensure responsible and human-centred AI considerations are reflected in recommendations and delivery artefacts.

Adoption, Change & Value Realisation

• Support stakeholder analysis, change-impact assessment and adoption planning.
• Contribute to communication, learning, enablement and feedback activities.
• Help define adoption, usage, business-outcome and risk indicators.
• Track agreed actions, benefits and learning from pilots and implemented use cases.
• Use insight and feedback to support roadmap refinement and continuous improvement.

Practice Development & Capability Building

• Contribute to reusable AI advisory assets, templates, use-case libraries and delivery methods.
• Capture lessons, case studies and repeatable patterns from client engagements.
• Stay current on AI and GenAI developments, enterprise adoption patterns and responsible AI practices.
• Share knowledge across the EMA and AI teams and support internal capability-building activities.

Minimum Requirements

Essential

• Typically 3-6 years of experience across business analysis, management consulting, digital transformation, product, process improvement or change-related roles.
• Practical exposure to AI, Generative AI, data, analytics, automation or digital-transformation initiatives.
• Experience gathering requirements, analysing processes and translating business needs into structured recommendations or delivery artefacts.
• Experience facilitating or supporting workshops with business and technical stakeholders.
• Strong written communication and experience preparing presentations, reports, process maps or business cases.
• Ability to work across multiple disciplines and contribute effectively within consulting or project environments.

Advantageous

• Experience in management consulting, AI advisory or enterprise transformation.
• Exposure to Microsoft Copilot, enterprise GenAI tools or AI-enabled business solutions.
• Experience with AI use-case assessment, maturity assessments, roadmaps or adoption programmes.
• Business analysis, Agile, product, design thinking or change management certification.
• Experience in regulated or complex enterprise environments.
• Exposure to responsible AI, governance, data privacy, security or risk requirements.

Skills & Competencies

AI, Data & Digital Understanding

• Sound understanding of AI and GenAI concepts, common enterprise use cases, capabilities and limitations.
• Awareness of the AI solution lifecycle, including opportunity discovery, data readiness, design, evaluation, deployment, monitoring and adoption.
• Working understanding of responsible AI, privacy, security, governance and human oversight.
• Ability to learn new AI tools, methods and market developments quickly.

Business Analysis & Consulting

• Requirements gathering and documentation.
• Process analysis and mapping.
• Use-case discovery, problem framing and prioritisation.
• Business case and value articulation.
• Structured problem solving, research and synthesis.
• Roadmap, backlog and action-plan development.

Communication, Facilitation & Stakeholder Engagement

• Clear written and verbal communication with business and technical audiences.
• Confident workshop facilitation and stakeholder interviewing skills.
• Strong presentation development and structured storytelling.
• Ability to build trust, manage differing perspectives and maintain shared understanding.
• Comfort engaging senior stakeholders while recognising when to draw on more experienced specialists.

Delivery, Change & Collaboration

• Collaborative approach across strategy, architecture, delivery, change and client teams.
• Strong organisation, attention to detail and follow-through.
• Awareness of Agile, product or iterative delivery practices.
• Practical understanding of adoption, change impact, learning and benefits tracking.
• Ability to manage ambiguity, competing priorities and evolving requirements.

Mindset

• Curious, pragmatic and commercially aware.
• Analytical and comfortable working between business and technology.
• Ethically grounded, with a commitment to secure, responsible and human-centred AI.
• Collaborative, low-ego and willing to learn from specialists.
• Focused on practical outcomes, client capability and measurable value.

As all iqbusiness roles require honesty in the handling of or access to cash, finances, financial systems, or confidential information; our recruitment process requires that the following background checks be completed: credit, criminal, ID, and qualification verification.

iqbusiness is committed to sustainable growth and transformation, we embrace diversity and employ previously disadvantaged individuals