AI Operations
Systematic AI implementation through proven methodology
The Challenge of Ad-Hoc AI Adoption
Many organizations begin AI adoption organically—individual staff members discover productivity gains from tools like ChatGPT, adoption spreads informally, and before long the organization has significant AI use without corresponding governance, standardization, or strategic direction.
This creates several challenges: inconsistent approaches across teams, duplicated effort discovering the same prompts independently, compliance gaps from undocumented usage, missed opportunities where AI could provide significant value, and difficulty scaling successful applications beyond individual users.
Systematic Implementation Through AI Operations
AI Operations provides structured methodology for moving from informal adoption to systematic implementation. We apply the AI Exchange framework—a proven approach for identifying high-value use cases, developing standardized operational playbooks, establishing appropriate governance, and building internal capability.
This isn't technology implementation—it's operational transformation. We focus on how your organization actually works, where AI can provide meaningful value, and how to integrate it sustainably into existing processes while maintaining compliance and quality standards.
Discovery & Prioritisation
Understanding your operations
We begin by understanding how your organization actually works—not how processes are documented, but how work gets done day-to-day. This reveals where AI can provide genuine value rather than implementing technology for its own sake.
Process Mapping
Document current workflows across key business functions
Identify time-intensive, repetitive, or inconsistent processes
Understand quality challenges and bottlenecks
Opportunity Assessment
Evaluate AI suitability for each identified process
Estimate potential time savings and quality improvements
Prioritize based on value, feasibility, and compliance consideration
Playbook Development
Creating Standardized Procedures
For each prioritized use case, we develop comprehensive playbooks documenting exactly how to apply AI effectively. This involves iterative testing, refinement based on real-world results, and validation with your subject matter experts.
Each Playbook Includes:
Process Documentation
Step-by-step workflow with decision points
Prompt Library
Tested, optimized prompts for each step
Quality Controls
Validation steps and review requirements
Compliance Guidance
Data handling and regulatory requirements
Training Materials
How to teach this approach to staff
Success Metrics
How to measure effectiveness
Governance & Infrastructure
Establishing Sustainable Foundation
Parallel to playbook development, we establish governance frameworks and technical infrastructure ensuring AI use remains compliant, auditable, and sustainable as it scales across your organization.
Governance Framework
Policies, approval workflows, accountability structures, and compliance procedures tailored to your regulatory context.
Technical Infrastructure
Appropriate AI infrastructure (Data Vault, Private LLM, or hybrid approach) based on your compliance requirements and use case portfolio.
Documentation & Audit Trail
Systems for logging AI use, maintaining compliance records, and demonstrating regulatory adherence.
Frequently asked questions.
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AI tools provide capability—AI Operations provides methodology for applying that capability effectively. Most organizations struggle not with technology access but with knowing how to integrate AI into actual work processes sustainably. We focus on the operational transformation, not just the technology.
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Part of capability building is teaching your team how to evolve playbooks as processes change. We document the development methodology so you can update existing playbooks and create new ones independently. Many clients also engage us for periodic playbook reviews and updates.
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We prioritize based on three factors: potential value (time savings, quality improvement), technical feasibility (AI suitability for the task), and compliance considerations (data sensitivity, regulatory requirements). The discovery phase produces a prioritized roadmap which you approve before playbook development begins.
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The AI Exchange is a structured framework for systematic AI implementation developed through extensive practitioner experience. We've adapted it specifically for UK SME contexts, incorporating UK regulatory requirements and scaling considerations appropriate for organizations with 10-50 staff.
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No. Playbooks are designed for business users, not technical specialists. We handle technical complexity in the background while providing user-friendly procedures for your staff. The "AI champions" we develop are business-focused coordinators, not IT professionals.
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Yes. Some clients begin with 1-2 high-priority use cases to validate the approach before committing to comprehensive implementation. We can structure engagements as initial proof-of-concept followed by broader rollout if results justify investment.