AI Change & Enablement Manager

Company: Total Negotiation Group
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Job Description:

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 



Posted: July 1st, 2026