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Change Management Consultant – Financial Transformation & AI Adoption
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Job Description - Change Management Consultant – Financial Transformation & AI Adoption
Role Overview
Job Title: Change Management Consultant – Financial Transformation & AI Adoption
Experience: 10 to 15 yrs
Location: Cheshire, UK
Duration: Initially 8 weeks
Work type: Onsite
Job Description
Finance AI Adoption & Transformation Consultant
We are seeking a Finance AI Adoption & Transformation Consultant to support the Finance function in accelerating the adoption of Generative AI and delivering measurable improvements in productivity, efficiency and ways of working.
The successful candidate will bring a strong combination of Finance domain understanding, hands-on AI capability, training and enablement skills, and practical change management experience. They will work directly with Finance teams to understand their processes, identify high-value AI opportunities, demonstrate practical applications of tools such as Microsoft Copilot, ChatGPT/GPT and Claude, and help teams adopt new AI-enabled ways of working.
This is a hands-on consulting role that combines use-case identification, AI enablement, training, process improvement and change management. The ideal candidate will be comfortable moving between business discussions, practical AI demonstrations, user training and stakeholder engagement.
Finance AI Adoption & Enablement
- Work directly with Finance teams to understand their activities, challenges and productivity opportunities.
- Identify practical opportunities where AI can improve Finance processes and user productivity.
- Demonstrate the application of Microsoft Copilot, ChatGPT/GPT, Claude and other relevant AI platforms to real Finance activities.
- Deliver practical training, workshops and coaching sessions for Finance users.
- Develop practical exercises, guides, prompt libraries and reusable AI resources.
- Coach users in applying AI effectively to their day-to-day responsibilities.
- Help teams move from initial AI experimentation to repeatable and sustainable usage.
- Build confidence and capability in the effective use of AI across Finance.
Finance AI Use Case Discovery
- Facilitate discussions and discovery workshops with Finance stakeholders to identify AI opportunities.
- Understand Finance processes and identify opportunities for productivity improvement, process redesign and AI enablement.
- Translate business challenges into practical AI use cases.
- Assess and prioritise use cases based on business value, feasibility, user impact and adoption potential.
- Develop practical roadmaps for high-priority Finance AI opportunities.
- Support Proof of Value initiatives and help demonstrate measurable business outcomes.
- Work with Digital, Data and Technology teams to ensure solutions remain aligned with genuine Finance requirements.
Prompt Engineering & Practical AI
- Apply and demonstrate effective prompting techniques across Finance use cases.
- Develop reusable prompts and prompt frameworks for common Finance activities.
- Coach users on structuring context, instructions, data and expected outputs.
- Demonstrate iterative prompting, refinement and output validation.
- Help users apply AI to activities including analysis, research, summarisation, reporting, documentation, drafting and knowledge management.
- Assess the appropriate application of different AI tools based on the business requirement.
- Promote responsible, secure and effective use of enterprise AI.
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Finance Transformation & Process Improvement
- Understand current Finance processes and identify opportunities to improve efficiency, quality and user experience.
- Apply Finance domain knowledge to assess processes critically and identify where AI and process redesign can create value.
- Support transformation across areas such as:
- Record-to-report and financial close
- Reconciliations
- Accounts payable and accounts receivable
- Treasury and cash forecasting
- Financial controls
- Financial reporting and analysis
- Help define AI-enabled future ways of working.
- Support continuous improvement initiatives across Finance.
Change Management & Adoption
- Support the development and execution of practical change and adoption strategies for AI initiatives.
- Identify the people, process and behavioural impacts associated with introducing AI into Finance.
- Develop stakeholder engagement and communication approaches.
- Identify potential adoption barriers and work with stakeholders to address them.
- Help Finance teams understand the benefits and practical implications of new AI-enabled ways of working.
- Engage with users throughout the adoption journey and incorporate feedback into the approach.
- Monitor adoption and identify opportunities to strengthen engagement and usage.
- Help embed successful AI practices into everyday Finance operations.
Training, Workshops & Coaching
- Design and deliver engaging Finance-focused AI training sessions.
- Conduct hands-on demonstrations using real business scenarios.
- Deliver workshops covering AI awareness, practical application, prompting and Finance use cases.
- Provide individual and group coaching to help users apply AI effectively.
- Develop training materials, practical exercises and user guidance.
- Adapt training approaches based on user capability and feedback.
- Build internal capability so that Finance teams can continue using AI independently and effectively.
Stakeholder Engagement
- Build strong working relationships with Finance leaders, process owners and users.
- Engage effectively with senior Finance stakeholders while remaining closely connected to operational teams.
- Communicate AI concepts clearly to technical and non-technical audiences.
- Facilitate collaboration between Finance, Technology, Data and Transformation teams.
- Present use cases, recommendations and business opportunities in a clear and structured manner.
Adoption & Value Realisation
- Define practical measures for AI adoption, productivity and business impact.
- Track progress across AI use cases and adoption initiatives.
- Capture user feedback and lessons learned.
- Identify opportunities to scale successful use cases.
- Support the development of longer-term AI adoption and Finance transformation roadmaps.
Required Experience
- 10–15 years of relevant professional experience across Finance, Finance transformation, business transformation, consulting, AI adoption, change management or related areas.
- Strong understanding of Finance processes and the ability to engage confidently with Finance professionals.
- Hands-on experience with Generative AI tools, particularly Microsoft Copilot, ChatGPT/GPT and/or Claude.
- Practical knowledge of prompt engineering and effective prompting techniques.
- Experience delivering training, workshops, coaching or business enablement.
- Experience supporting organisational change, user adoption or transformation initiatives.
- Demonstrated ability to identify business opportunities and translate them into practical AI use cases.
- Strong stakeholder engagement, facilitation and communication skills.
- Ability to work directly with business users and senior stakeholders.
- Strong analytical and problem-solving capabilities.
- A practical, hands-on and collaborative approach to technology adoption.
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Finance Domain Capability
Candidates should have a strong working understanding of Finance operations and be able to engage meaningfully with Finance stakeholders. Relevant experience may include:
- Record-to-report and financial close
- Reconciliations
- Accounts payable and accounts receivable
- Treasury and cash forecasting
- Financial controls
- Financial reporting and analysis
- Working capital and liquidity management
A professional accounting qualification such as ACA, ACCA, CIMA or equivalent would be highly advantageous but is not essential. Candidates without a formal accounting qualification will also be considered where they demonstrate strong practical Finance knowledge and the ability to understand, challenge and improve Finance processes. Experience in commodity or asset-intensive environments, including inventory and working-capital management, hedging, duty/excise, borrowing-base arrangements or covenant reporting, would be an advantage.
AI & Technology Capability
Candidates should demonstrate practical, hands-on capability across:
- Generative AI
- Microsoft Copilot
- ChatGPT / GPT
- Claude
- Prompt engineering and prompt optimisation
- AI-assisted business workflows
- AI use-case identification
- AI training and user enablement
- AI adoption strategies
- Responsible and secure AI usage
- AI output validation and quality assessment
Preferred Industry Experience
Experience in one or more of the following sectors would be advantageous:
- Energy
- Oil & Gas
- Manufacturing
- Utilities
- Chemicals
- Commodity or asset-intensive businesses
- Large enterprise organisations
Core Competencies
- Finance Domain Knowledge
- Generative AI & Copilot
- AI Use Case Identification
- Prompt Engineering
- AI Training & Enablement
- Change Management
- User Adoption
- Finance Transformation
- Business Process Improvement
- Workshop Facilitation
- Stakeholder Engagement
- Business Consulting
- Coaching & Knowledge Transfer
- Value Realisation
- Communication & Influencing
- Analytical Problem Solving
Success Measures – Short Version
- Enable Finance teams to use AI effectively in daily work.
- Identify and prioritise high-value Finance AI use cases.
- Deliver practical AI training and coaching.
- Create effective prompts and reusable AI resources.
- Improve productivity, efficiency and quality through AI.
- Drive AI adoption and manage change effectively.
- Embed AI into everyday Finance processes.
- Engage Finance stakeholders and users effectively.
- Demonstrate measurable business value from AI.
- Build a roadmap for sustainable AI adoption.
Ideal Candidate Profile
We are looking for a Finance-focused AI practitioner and transformation consultant who can operate comfortably across four areas: understanding Finance, identifying AI opportunities, enabling people and managing change.
A strong balance of Finance knowledge, practical AI capability, training skills and change management experience is more important than depth in any single discipline.
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