AI Solutions Lead

AI Solutions Lead

Reports to: Chief Solutions Officer

Location: Home Based – UK

Context and Overall Purpose of Role

Total Negotiation Group is looking for an AI Solutions Lead to help shape how AI is embedded across our business, our client delivery, and our future service offering. This is a strategic and hands-on role focused on turning AI into practical commercial impact, internally and externally.

The successful candidate will help drive AI adoption across the business, support consultants and facilitators in using AI effectively with clients, and identify opportunities to create new AI-enabled products, services, and ways of working. We are looking for someone who can combine strong commercial thinking, consulting capability, innovation, and practical AI knowledge to help evolve the way we work.

Key Responsibilities:-

1) Enterprise AI Strategy & Transformation

• Lead the development and execution of Total Negotiation Group’s internal AI strategy, ensuring AI capabilities are embedded across the organisation to improve productivity, decision-making, operational efficiency, and innovation.
• Lead the identification, design, and implementation of AI-enabled workflows across Total Negotiation Group’s internal operations. Focus on replacing and improving manual, repetitive processes through practical automation using AI tools and workflow platforms.
• Work closely with teams across the business to map existing ways of working, identify inefficiencies, and build scalable solutions that improve productivity, decision-making, and operational efficiency. This includes developing and deploying AI-assisted workflows, lightweight internal tools, and automation solutions that embed AI into day-to-day operations in a practical and usable way.
• Drive adoption of these solutions across the organisation, ensuring teams are effectively trained and supported to use AI tools in their workflows. Establish clear, pragmatic guidelines for responsible AI use and ensure solutions are secure, reliable, and appropria2ete for internal use cases.
• Identify and prioritise opportunities where AI and automation can deliver measurable time savings, quality improvements, and commercial impact through better execution and reduced manual effort.

2) Client AI Application, Capability Building & Delivery Enablement

• Support clients in understanding and applying AI in practical, commercially relevant contexts and commercial decision-making. Focus on identifying where AI can meaningfully enhance performance and helping clients build the capability to use it effectively within their day-to-day business processes and teams.
• Ensure Total Negotiation Group’s delivery teams are equipped with the right AI knowledge, tools, and frameworks to integrate AI naturally into client engagements, workshops, and training programmes, embedding AI into our core consulting and capability-building work.

3) 3. AI Productisation & Commercial Growth

• Identify, develop, and commercialise AI-driven products, tools, and service offerings that create new revenue streams.
• Drive the transition from AI experimentation to scalable commercial solutions, to bring innovative AI capabilities to market.
• Build repeatable propositions and frameworks that position Total Negotiation Group as a leader in commercially focused AI solutions.

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: -

• AI strategy & roadmapping - Define where AI creates leverage across the business. Set priorities, governance, and a phased delivery plan tied to commercial outcomes.

• Workflow automation & process design - Map, redesign, and automate manual processes using AI tooling. Hands-on familiarity with platforms like Make, Zapier, or n8n is essential.

• Change management & AI adoption - Drive uptake across non-technical teams. Build training, guidelines, and responsible-use frameworks that make AI tools stick in day-to-day operations.

• Consulting & commercial problem-solving - Identify where AI meaningfully improves client performance. Translate business challenges into practical AI interventions rather than technology for its own sake.

• Facilitation & capability transfer - Equip consultants and client teams to use AI effectively. Design workshops, training programmes, and frameworks that embed AI into live engagements.

• Commercial AI application - Apply AI specifically in commercial contexts, negotiation, pricing, deal analysis, decision support. Domain fluency in how AI enhances commercial performance is highly valued given TNG’s focus.

• Product thinking & service design - Turn AI experiments into scalable propositions with clear value, pricing, and repeatable delivery. Experience taking new products from concept to launch.

• Commercial development - Position AI offerings, develop go-to-market narratives, and contribute to revenue growth. Ability to sell as well as build is a real differentiator.

• Practical AI & LLM fluency - Hands-on experience with modern AI tools — LLMs, prompt engineering, agents, RAG pipelines, and evaluation. Not a deep engineering role, but enough technical depth to scope, build prototypes, and evaluate third-party solutions credibly.

Experience Required: -

• 5-8 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