The problem
From theory to practice, without doing damage
Defining an AI strategy is relatively easy; implementing it effectively is another matter. This is where many initiatives stall: unclear vendors, tools chosen hastily, integration neglected.
The Operational Implementation service supports leadership in all practical phases of AI adoption.
Audience
Typical audience
▸Mid-market SMEs that have decided to introduce AI but lack sufficient internal skills.▸General managers and IT leaders evaluating vendors and coordinating the first projects.▸Entrepreneurs who prefer an external reference point to building an AI team from scratch.▸Companies that have already experimented without expected results and want a structured restart.
Scope
What the service includes
Six operational areas, from vendor selection to results measurement.
01Vendor selectionComparative analysis of relevant AI providers. Technical, commercial, contractual and compliance assessment.
02Pilot launchDefinition of pilot scope, process selection, tool configuration. Clear result objectives from the outset.
03AutomationsDesign of intelligent automations connecting AI to existing business processes, on existing platforms.
04Knowledge managementOrganising corporate knowledge into an internal AI assistant accessible to employees.
05AI agentsConfiguration of AI agents for repetitive tasks: email classification, data extraction, recurring reports.
06Results measurementConcrete success indicators and continuous monitoring of pilot projects.
The method
How an engagement unfolds
01ScopingAnalysis of context, target process, available data and concrete goals.
02SetupTool selection, initial configuration, access management, usage policies.
03PilotPilot launch in a controlled environment. Feedback collection and results measurement.
04Scale-upGradual extension to the rest of the company with governance review and continuous training.
Deliverables
What you receive
▸Scoping document — detailed description of the pilot project.▸Vendor selection report — comparative analysis of evaluated providers.▸Configured tools — operational AI tools, ready for use.▸Basic training materials — operational guides, prompt examples, checklists.▸Pilot phase report — measurement of results and recommendations.▸Scale-up plan — roadmap to extend the solution.
Principles
Five principles that guide every engagement
01Start smallAI projects deliver value when starting from narrow domains. Starting big is almost always a mistake.
02Don’t buildMost mid-market use cases can be solved with existing tools, properly configured.
03Work with processesAI must fit into existing workflows. The most effective solutions are the ones staff use without noticing.
04Confidentiality firstVendor and configuration choices always prioritise the highest standards of data protection.
05Vendor independenceNo commercial agreements with AI providers. Recommendations are neutral.
