The AI is ready. Are your people?

Client Context & Challenge

A large enterprise with approximately £120m in annual addressable third-party spend operated a late-stage and transactional procurement function. Legal acted as a bottleneck, contract cycles averaged six months, and procurement was involved in only 15% of initiatives at ideation, with savings skewed 70% to price and 30% to value/innovation. Forecast accuracy was 25%, and supplier risk visibility was manual and quarterly.

Approach

The team deployed an AI-first procurement model anchored in an enterprise performance framework to redesign roles, workflows and decision rights across Procurement, Legal, Finance, Product, Marketing, Sales, R&D and Compliance.

• AI-enabled contract intelligence: internal AI trained on approved clauses, historic contracts and compliance standards to enable self-service compliance checks and automated supplier risk visibility.
• Stakeholder personas: Finance, Product, Marketing, Sales, Customer, Compliance and Legal personas to tailor narratives and reduce rework in approvals.
• Upstream collaboration: structured engagement at idea stage with Product, Marketing and R&D to co-design business requirements and solutions.
• Market intelligence and supplier innovation showcases: shift from reactive RFQs to continuous insight generation and solution-led supplier engagement.
• Integrated planning: proactive demand planning and MOQ optimisation with Commercial and Finance teams to reduce forecast variance.

Impact

Within the first cycle, procurement shifted from gatekeeper to strategic partner.

• Contract cycle time reduced from 6 months to 1 month; legal touchpoints dropped from 88% to 22%.
• £1.05m annualised cost savings, plus £6.3m innovation-led savings at 9.5% on £66m strategically influenced spend.
• Procurement involvement at ideation increased from 15% to 65%.
• Customer experience improved by 10–15%, time-to-market accelerated by 12–20%.
• Forecast variance reduced by 68%, from 25% to 8%.

Organisational & Behavioural Shift

• Procurement repositioned as a strategic co-creator of solutions, not a transactional negotiator.
• Legal concentrated on high-value risk, Finance benefited from earlier, more reliable forecasts, and Product/Marketing co-designed fit-for-purpose solutions.
• Suppliers evolved from bidders to innovation partners, reinforcing a value flywheel of insight, innovation and trust.

Partner Context & Challenge

An AI engineering provider designs bespoke solutions, including intelligent document processing (IDP) for complex, document-heavy sectors such as infrastructure and construction. While technical solutions could automate document handling, clients often lacked the cultural and behavioural foundations to turn project-level success into enterprise-wide business-as-usual improvements.

Approach

• Technology partner role: build IDP agents to automate management of lengthy, complex project documents, reducing bid costs and strengthening programme-management effectiveness.
• Transformation partner role: work with leaders and project teams to create the mindset shifts, curiosity and leadership buy-in needed to make these agents the "go-to" tool in daily work.
• Culture and habit change: coach teams to see surfaced insights not only as compliance aids but as catalysts for innovative, client-centric solutions during bids and contract negotiations.

Impact

• IDP reduced the manual burden associated with compliance, change management and error rectification, directly lowering bid and delay-related costs.
• Teams exceeded contractual briefs with more creative, data-driven proposals using IDP insights.
• The partnership created a replicable pattern for turning technical wins into improved business-as-usual operations.

Organisational & Behavioural Shift

• Clients moved from a binary view of AI ("tool vs no tool") to an adaptive mindset centred on strategic possibilities.
• Teams treated IDP agents as default copilots in complex document work rather than occasional utilities.
• Leaders championed AI-generated insights in strategic conversations, reinforcing the expectation that AI-enabled thinking is standard.

Client Context & Challenge

A global consultancy and construction group delivering complex infrastructure projects required robust knowledge management, stakeholder coordination and operational agility. Despite clear AI potential, much knowledge remained siloed across systems and individuals, leading to delays, duplicated work and missed opportunities.

Approach

• Smarter knowledge management: AI to organise and retrieve information from diverse sources, enabling faster bid preparation and stronger proposals.
• Decision support: AI to automatically extract contractual obligations from live project data, meetings and emails.
• Staff utilisation: automation of administrative and reporting tasks to free specialists for optimisation and risk management.
• Stakeholder coordination: AI-enabled synthesis of updates, engagement tracking, alignment support and regulatory communication.

Impact

• Bid team cut research time by 40% through AI-supported retrieval.
• Administrative automation reduced compliance workload by 30%; meeting documentation cut by 50%.
• Automated tracking reduced missed deadlines by 30%.

Organisational & Behavioural Shift

• AI was embedded into existing workflows as the standard way to access knowledge and track obligations.
• Leadership aligned around AI as a strategic enabler, using high-impact, low-risk pilots to build confidence.
• Teams developed the capability to integrate AI into everyday work, turning it into a durable competitive advantage.

Partner Context & Challenge

A global hardware and AI platform ecosystem was advancing powerful AI solutions, but many end-clients struggled to convert pilots into sustained, ROI-positive adoption. Traditional levers—technology deployment, skills training and hackathons—were insufficient to overcome human-centric barriers in culture, mindset and workflows.

Approach

• Strategic alignment (pre-sale): co-creation of a shared AI vision, explicit success metrics and identification of untapped AI opportunities.
• Adoption and transformation (implementation): immersive sessions using design-thinking, gamification and rapid prototyping to trigger an AI EQ identity shift.
• Embedding value (post-implementation): coaching internal champions, embedding AI habits in daily routines and decision-making, and tracking impact.
• Structured framework: a repeatable Align–Prototype–Embed–Expand path from experimentation to enterprise-wide adoption.

Impact

• Up to 20% productivity increase, senior decision-makers saving up to two hours per day.
• Reporting cycles 65% faster, with 20–40% uplift in output quality.
• 35% increase in team satisfaction and 25% quarterly performance improvement.

Organisational & Behavioural Shift

• Teams adopted adaptive mindsets, viewing AI as a collaborator on critical challenges rather than a threat or add-on.
• AI was woven into workflows and decision forums, creating a culture of innovation from the ground up.
• The ecosystem value proposition shifted from "deploying technology" to enabling durable, in-house AI capability and ROI.

Client Context & Challenge

A large organisation had deployed a generative AI assistant, but licence usage plateaued because workflows, KPIs and behaviours had not adapted. AI accelerated individuals but did not translate into measurable organisational outcomes, limiting appetite for additional licences.

Approach

• Pre-alignment (30 minutes): confirm licence holders by SKU, usage by role, target expansion roles and workshop logistics.
• Role-spanning discovery workshop: immersive session across business leads, licensed and unlicensed end users, platform administrators, IT/security and risk/compliance.
• Micro-experiments: co-selection of 2–3 experiments in a critical workflow, with metrics spanning speed, reviewer effort, control adherence and confidence.
• Value-expansion playbook: expansion criteria, a "not now" list, replication blueprints per area, and light governance with named champions and coaching cadence.

Impact

• The client achieved an internally owned pilot outcome demonstrating decision-readiness and control-adherence improvements.
• The playbook produced a named set of adjacent processes and teams with clear expansion logic.
• Experiments operated as "licence multipliers," tying additional seats directly to business outcomes rather than generic enablement.

Organisational & Behavioural Shift

• The AI assistant became the default path for specific workflows rather than an optional tool.
• Behavioural and KPI alignment ensured success was measured in operational terms familiar to sponsors.
• Enablement was translated into sustained daily usage patterns, differentiating the provider with a value-led expansion path.