Why generic AI tutorials fall short
YouTube tutorials and online courses teach AI features in isolation. They demonstrate how to ask ChatGPT a question or generate an image with Midjourney. What they do not teach is how your marketing manager should use Claude to draft campaign briefs that match your brand voice, or how your sales team can use GPT-4 to summarise client calls and populate CRM notes in a format your pipeline requires.
The gap between general AI knowledge and practical business application is where productivity gains either materialise or evaporate. A salesperson who knows ChatGPT exists is no more productive than one who does not, unless they know how to prompt it for their specific tasks, verify its output against their domain knowledge and integrate the results into their daily tools.
Our training starts from your workflows, not from the AI tool's feature list. We identify the tasks where AI creates measurable time savings, teach your team how to execute those tasks effectively and provide templates and prompts they can use immediately after the session.
What our AI training covers
Each training programme is structured around your team's actual responsibilities. The modules below represent the core curriculum, adapted to the participant profile.
Prompt engineering fundamentals. Writing effective prompts is the skill that determines whether AI produces useful output or generic filler. We teach the principles of structured prompting: role assignment, context specification, output format definition, constraint setting and iterative refinement. Participants practice on real examples from their work: drafting emails, summarising documents, generating reports, analysing data. They leave with a personal library of tested prompts for their recurring tasks.
Tool selection and capabilities. ChatGPT (OpenAI), Claude (Anthropic) and Gemini (Google) have different strengths. ChatGPT excels at general-purpose tasks and integrates with hundreds of plugins. Claude handles long documents and produces nuanced analysis with strong accuracy. Gemini connects natively to Google Workspace. We teach participants when to use each tool and how to evaluate output quality. Understanding the limitations of each model is as valuable as understanding the capabilities.
AI for marketing teams. Marketing professionals learn to use AI for content drafting (blog posts, ad copy, email sequences), keyword research support, competitor analysis, social media content planning and campaign performance interpretation. Each exercise uses real data from your business. The emphasis is on AI as an accelerator, not a replacement: the marketer provides strategy, domain knowledge and quality control; AI handles the time-consuming drafting and analysis.
AI for sales and customer-facing teams. Sales professionals learn to use AI for prospect research, meeting preparation, email personalisation, call summary generation and CRM data entry assistance. Client-facing teams learn to use AI for response drafting, FAQ management and knowledge base maintenance. These applications save 30 to 60 minutes per person per day when applied consistently.
AI for operations and management. Executives and operations managers learn to evaluate AI opportunities within their organisation, assess vendor claims, estimate implementation costs and define governance policies. This module aligns with our AI consulting service and provides the foundational understanding needed to make informed AI investment decisions.
Training formats
We deliver training in formats adapted to your team size, location and schedule constraints.
Half-day workshop (3.5 hours). Focused on one team or function. Covers prompt engineering fundamentals and 2 to 3 role-specific applications. Participants leave with immediately usable prompt templates and a workflow integration plan. Suitable for teams of 4 to 12 people.
Full-day workshop (7 hours). Comprehensive coverage of AI tools, prompt engineering, role-specific applications and hands-on exercises. Includes a session on AI governance and output verification. Suitable for mixed teams where marketing, sales and operations participate together.
Two-day programme. Day one covers fundamentals and tool capabilities. Day two focuses entirely on practical implementation: participants build their own prompt libraries, create workflow automations using AI tools and present their integration plans to the group. Includes a follow-up session 4 weeks later to review adoption and address obstacles.
Remote sessions. All formats are available via video conference. Remote training uses screen sharing, collaborative documents and breakout rooms for small-group exercises. Participants receive the same materials and post-session resources as in-person attendees.
Training sessions are delivered in English, French or bilingual format depending on your team composition. For businesses in the Geneva cross-border region, bilingual delivery ensures both French-speaking and English-speaking team members engage fully.
Our training methodology
Training that produces lasting behaviour change follows a different approach than a lecture with slides.
Every session begins with a diagnostic. We survey participants before the training to understand their current AI familiarity, their daily tasks and their expectations. This input shapes the exercise selection and ensures the content matches the room, not a generic syllabus.
The session itself is 70% hands-on practice. Participants work on their own laptops, using their own accounts, on tasks drawn from their actual work. A marketing manager drafts a real campaign brief. A salesperson summarises a real client call. Immediate application cements the learning and produces artefacts they can reuse the next day.
Each exercise includes output evaluation. Participants learn to identify when AI output is accurate, when it contains fabrications (hallucinations), and when it produces technically correct but strategically wrong content. Critical evaluation is the skill that separates productive AI users from those who publish unverified output.
Post-session materials include a prompt library customised to the team's roles, a quick-reference guide for each AI tool covered, and a list of workflow integration opportunities identified during the training. A follow-up session (included in full-day and two-day programmes) reviews adoption 4 weeks later and troubleshoots any implementation barriers.
AI training and your broader digital strategy
AI training amplifies the return on every other digital investment.
Teams trained in AI produce SEO content faster. A content writer who knows how to use Claude for research summaries, structural outlines and first-draft generation produces publishable articles in half the time. Quality remains under human editorial control; production speed doubles.
Marketing managers who understand AI make better use of GA4 data. They prompt AI tools to identify patterns in analytics reports, generate hypotheses about traffic changes and draft test plans. The analytics data becomes a conversation partner rather than a static dashboard.
Sales teams trained on AI prompting convert Google Ads leads faster. Personalised follow-up emails drafted with AI assistance go out within minutes of lead capture, not hours. Faster response times correlate directly with higher conversion rates.
Executives who understand AI capabilities make informed decisions about AI consulting investments. They can distinguish between vendors offering genuine productivity gains and those selling complexity without substance. Training provides the literacy needed to evaluate AI opportunities critically.