AI Solutions Manager

Department: IT

Employment Type: Permanent

Location: Jersey

Description

Ogier is looking for an AI Solutions Manager to identify, shape and deliver practical business process improvements across prioritised areas of the business.

This is a business-facing role for someone who can work directly with stakeholders, understand current ways of working, identify where improvement is needed, and translate opportunities into safe, useful and measurable AI-enabled solutions.

The role will make practical use of structured prompt engineering, reusable prompt patterns, AI-enabled workflows, agentic workflow concepts, automation and approved technology platforms. The successful candidate will combine experience in applied AI, business analysis, process improvement and stakeholder engagement. They will not be expected to build machine learning models, but they will need to understand how AI can be applied responsibly to improve business outcomes.

Key Responsibilities

Identify business process improvement opportunities

• Work proactively across Ogier teams to understand current processes, pain points and improvement opportunities.
• Run discovery sessions, interviews and workshops with stakeholders
• Identify processes that are manual, repetitive, inconsistent, high-friction or suitable for improvement.
• Translate business challenges into clear opportunity statements, including the problem, users affected, expected benefit, risks and dependencies.
• Prioritise opportunities based on measurable business value, not simply whether AI could be used.

Shape practical AI-enabled solutions

• Identify where AI, automation or existing approved technology can improve how work is done.
• Map business processes to practical AI scenarios such as drafting, summarisation, search, analysis, extraction, workflow support and quality review.
• Design repeatable workflow patterns that help teams use AI safely and consistently.
• Work with IT, AI specialists, Knowledge Management, Risk, Compliance and business stakeholders to shape usable solutions.
• Ensure proposed improvements fit naturally into day-to-day working practices.

Develop reusable prompts and workflow guidance

• Create and refine reusable prompts, prompt templates, workflow guides, AI playbooks and adoption materials
• Apply structured prompt and context engineering techniques, including task decomposition, context supply and clear output specifications.
• Test prompt approaches with users and improve them based on clarity, reliability, usefulness and business value.
• Develop guidance on when human review, source checking, quality control or escalation is required.
• Help standardise, update or retire prompts and workflow patterns based on feedback, risk and measured value.

Support adoption and change

• Act as a trusted adviser to business teams on practical AI-enabled process improvement.
• Help stakeholders understand what AI can and cannot do.
• Provide hands-on support during pilots, early adoption and transition to sustainable use.
• Build user confidence through practical examples, safe usage guidance and clear success measures.
• Produce concise enablement materials such as quick-start guides, FAQs, process notes, playbooks and adoption assets.

Support governance, risk and responsible AI

• Ensure AI-enabled process improvement activity follows agreed governance, testing and review processes.
• Consider confidentiality, data protection, quality, security and responsible AI requirements when shaping solutions.
• Support risk assessments and document mitigations where required
• Escalate issues where risks, uncertainty or ownership questions require further review.
• Reinforce that AI outputs are assistive and subject to appropriate human review where judgement, client service, regulatory or operational outcomes may be affected.

Measure value and continuously improve

• Define and track adoption, usage and value metrics for each improvement initiative.
• Capture measures such as active users, depth of use, time saved, quality improvements, stakeholder feedback and risk posture.
• Maintain clear reporting inputs for the process improvement pipeline.
• Capture lessons learned from pilots and implemented workflows.
• Recommend whether solutions should be refined, scaled, redesigned or decommissioned based on evidence.

Skills, Knowledge and Expertise

Essential experience

The successful candidate should have experience in several of the following areas:

• Business analysis, business process improvement, business relationship management, product adoption, digital transformation or AI-enabled change.
• Working with business stakeholders to understand requirements, map processes and shape practical improvements.
• Supporting AI, automation, Microsoft 365, digital workplace tools or other technology-enabled business improvements.
• Producing process maps, opportunity statements, user stories, acceptance criteria, business cases, workflow documentation, prompt guidance, playbooks or adoption materials.
• Working in an environment where governance, testing, validation, risk assessment, compliance or quality review are important.
• Supporting change with business users, including adoption planning, guidance, feedback gathering and continuous improvement.

Essential skills

• Strong business analysis skills, including requirements gathering, process mapping and stakeholder validation.
• A process improvement mindset, with the ability to simplify workflows and identify practical interventions.
• Practical understanding of prompt engineering, prompt evaluation and reusable prompt pattern design.
• Ability to identify where AI, automation, agentic workflow concepts or existing technology can improve business outcomes.
• Excellent communication and facilitation skills, with the ability to explain AI and technology concepts in clear business language.
• Strong stakeholder management skills, including the ability to build trust, influence constructively and manage competing priorities.
• Data literacy, including the ability to define and interpret adoption, usage, value and risk measures.
• Good understanding of responsible AI risks, including confidentiality, hallucination, bias, provenance, data quality, security and human review.

Desirable experience or qualifications

• Experience in legal, professional services, corporate services, financial services or another regulated environment.
• Business analysis qualification such as BCS Business Analysis, PMI-PBA or equivalent.
• Process improvement qualification such as Lean Six Sigma or equivalent.
• Microsoft certifications such as AI-900, MS-900, PL-900 or SC-900.
• Project, Agile, change management, adoption or training-related qualifications.
• Demonstrable hands-on experience using AI tools in a work setting, such as Microsoft 365 Copilot, ChatGPT or Claude, with practical examples of where they have improved a task, process or output.