AI Change & Enablement Manager

Reports to: Chief Solutions Officer

Location: Home Based - UK

Context and Overall Purpose of Role

Total Negotiation Group is hiring an AI Change & Enablement Manager to drive practical AI adoption across internal teams and client delivery. This is a hands-on transformation role focused on behaviour change, workflow redesign, capability building, and productising proven AI use cases.

This role is less about defining high-level AI strategy and more about making AI work in day-to-day operations and client outcomes.

Key Responsibilities:

1) AI Change Management & Adoption

• Lead structured AI adoption across non-technical and commercial teams.
• Design and run communication, training, coaching, and reinforcement programmes.  
• Define practical responsible-AI usage standards and team playbooks.  
• Track adoption and usage outcomes; remove blockers and improve uptake.  

2) Workflow Redesign & AI Implementation   

• Identify manual/high-friction workflows and redesign them using AI and automation.  
• Build or coordinate practical solutions using appropriate tooling (directly or via partners).  
• Ensure workflows are usable, secure, and embedded into operating routines.  

3) Client Delivery Enablement  

• Equip consultants/facilitators with AI methods, prompts, templates, and assets.  
• Integrate AI into workshops, training programmes, and client engagements.  
• Help teams translate business problems into practical AI-enabled interventions.  

4) Productisation & Commercial Application  

• Turn successful internal/client use cases into repeatable, sellable offerings.  
• Define value proposition, scope, delivery model, and pricing logic.  
• Support go-to-market messaging with practical proof points.  

Tooling & Platform Fluency: - 

The role requires broad tooling literacy, with ability to work hands-on where appropriate and lead cross-functional implementation where deeper specialists are needed.  

Expected platform awareness  

• Cloud AI ecosystems: Azure AI services, AWS AI/ML services (and equivalent) 
• Workplace AI platforms: Microsoft Copilot ecosystem, Anthropic Claude, enterprise assistants  
• Automation/orchestration: n8n, Make, Zapier, Power Automate  
• LLM application stack: prompt design, copilots/agents, RAG concepts, evaluation basics  
• Data/knowledge integration: document sources, vector/search patterns, basic data readiness  
• Governance/security basics: access controls, privacy, model risk, responsible use  
• Direct vs indirect expectation  
• Direct: Can prototype workflows, test tools, and run pilots.  
• Indirect: Can scope architecture-level decisions, evaluate vendors/platforms, and coordinate with IT/data/security/engineering for production rollout.  

Skills Required:

Change, Adoption & Capability Building  

• Change management leadership  
• Facilitation & capability transfer  
• Stakeholder influence & communication   

Applied AI Delivery & Tooling Fluency  

• Workflow automation & process redesign  
• Cross-platform AI tooling literacy (Azure, Copilot, automation stack)  
• Practical LLM fluency and execution discipline   

Experience Required: - 

• 2-5 years experience  
• Strong change/adoption transformation track record.  
• Demonstrated experience embedding AI into real workflows and team behaviour.  
• Broad AI tooling exposure across enterprise ecosystems (not limited to one toolset).  
• Comfortable working both hands-on and through specialist partners.  
• Product-minded and commercially credible in client-facing environments.  

Benefits: -

• Performance Bonus  
• Competitive Salary  
• Paid Birthday leave  
• 27 days annual leave  
• Employer supported volunteering  
• Flexible working hours  
• Study allowances  
• Private Health Cover  
• Electric car scheme  
• Employee Ownership Trust