What happens in the AI adoption workshop?

At *instinctools, we provide virtual and in-person workshops. Whichever the format and wherever you are on your AI journey—just starting with a single use case, scaling across departments, or introducing AI capabilities to the market—our flexible, modular approach adapts to your timeline, goals, and level of readiness.

We don’t walk in blind. After signing an NDA, we do the homework by:

• Diving into your business context by interviewing key stakeholders to see your challenges and opportunities.
• Assessing your as-is state, including overall AI readiness and current AI prototypes, if there are any.
• Exploring meaningful processes and areas of potential impact where AI can add value.
• Drafting an initial vision of your future AI-enabled to-be state.

• Translating your business objectives and pain points into visual mind maps to reveal AI opportunities.
• Presenting our ideas of the to-be state with a chart of relevant high-value, low-barrier AI use cases.
• Defining clear success criteria for your AI initiative to measure results.
• Running a validation session to ensure alignment after a day of discussions.

• Outlining the required tech environment.
• Preparing a prioritized project backlog.
• Drafting an initial architecture vision.
• Sharing UX/UI concepts.
• Creating a strategic roadmap.
• Outlining project timelines and budget.
• Planning for market or employee validation through a pilot program.

And because every organization is different, our workshops are truly agile. We recalibrate the program to bring value to your unique business, such as staff AI upskilling or establishing an AI center of excellence.

Even a structured, facilitated AI discussion is of little value if the insights go undocumented. Practical, no-fluff takeaways are what drive companies to turn their AI ambitions into actions. Here’s what *instinctools’ clients get:

• Vision & Scope: A complete breakdown of your AI-related problems, goals, risks, opportunities, metrics, scope, and roadmap.
• Architecture Overview: A review of your current tech stack and the envisioned AI system—data management, model training, and software integration.
• UX/UI Concepts: Initial wireframes for AI development.
• Budget & Timeline: High-level estimates covering data cleansing, model fine-tuning, and project delivery phases.