- AI adoption and data literacy for executives and non-technical roles
- Digital skills for frontline teams and middle management
- Sustainability and circular economy in operations
- Innovation leadership and intrapreneurship toolkits
- Custom academies with micro-credentials and capstone projects
Corporate learning designed for measurable capability growth.
Start Attractor designs customized upskilling and reskilling paths with HR and business leaders to support green and digital transitions, technology mastering and AI adoption across organizations.
Online live
Blended
Projects
KPI tracking
Programs built around your learning priorities
Each learning path is designed around the capabilities your organization needs to strengthen, from leadership and innovation to digital, sustainability and AI.
Programs can be delivered in Pisa, on-site, online live or in blended format, with a structure designed to support participation, application and measurable progress.
A pragmatic design-to-impact approach
We design learning paths with the same logic used in strong innovation programs: start from priorities, test what works and build for scale.
Identify skills gaps, business priorities and stakeholder expectations.
Build the journey, exercises, assessments and supporting materials.
Run an initial cohort, gather feedback and improve what matters most.
Extend across teams with dashboards, iteration and continuous improvement.
We can also align learning paths with broader open innovation initiatives, pilots and venture programs.
Examples of ready-to-run courses
Choose a module as it is, or use it as a starting point for a tailored corporate learning path.
How to lead AI adoption in your company: value creation, the role of a Chief AI Officer, governance, risk and regulation.
Understand where and how AI can generate concrete value (revenue, efficiency, risk). Define an AI operating model (CoE, BU teams, partnerships) and the CAIO mandate. Evaluate AI initiatives with essential business/adoption/risk KPIs readable at board level. Frame ethical, reputational and legal risks (AI Act, GDPR, sector regulations). Draft a first AI roadmap and a company AI Charter (principles + baseline rules).
- Senior advisor with experience in:
- - AI and data-driven transformation in industrial contexts
- - C-level roles and governance models
- - AI governance, risk, compliance and regulation
- AI as a competitive advantage (decisions + automation)
- AI operating models: centralized, federated, hybrid
- AI portfolio, standards, policies and governance
- Value metrics: business, adoption, risk/quality
- AI Act / GDPR: risk levels, obligations, practical implications
- Building an AI Charter (5-point framework)
- Interactive session with executives
- Realistic sector case discussions
- Short group work: use-case mapping, operating model design, KPI dashboard, AI Charter
- Plenary sharing and cross-sector comparison
- Course slides (PDF)
- Templates: AI use-case mapping, KPI definition, operating model, AI Charter
- Executive summary after the course with priorities and next steps
- Slide deck
- Templates & worksheets
How to identify, structure and execute AI initiatives in operational processes, aligned with top management AI strategy.
Spot concrete AI opportunities in the processes you own. Structure an AI use case in a way that is readable by C-level, IT and data teams. Define and monitor essential KPIs (business, adoption, risk). Manage change and adoption in your team, reducing fear and resistance. Translate the company AI Charter into day-to-day decisions.
- Senior advisor with experience in:
- - AI and data-driven transformation
- - C-level roles (CAIO/CDO) and governance
- - AI governance, risk, compliance and regulation
- Process mapping and AI opportunities
- Use case anatomy: problem, process 'as is', actors, data, constraints
- Project lifecycle: discovery → MVP/PoC → pilot → scale
- Basic technical metrics (false positives/negatives, thresholds)
- KPIs: business, adoption, risk/quality; incident handling
- Operational change management and a 90‑day action plan
- Interactive lessons and case discussions
- Group work on participants' real roles and scenarios
- Templates: Use Case Canvas, KPI sheet, 90‑day plan
- Plenary sharing and peer learning
- Course slides (PDF)
- Templates: process/use-case mapping, KPI definition, operating model, AI Charter
- Executive summary after the course with priorities and next steps
- Slide deck
- Templates & worksheets
A live workshop to learn how to write prompts that reliably produce useful outputs for everyday work.
Understand what a prompt is and why it impacts output quality. Apply 4 basic rules for good prompts. Use model prompts for daily tasks (emails, summaries, ideas, tables, translations, procedures). Iterate prompts (draft → refinement) to improve relevance. Use prompting responsibly, aligned with company AI policies.
- Senior advisor with experience in:
- - AI and data-driven transformation
- - C-level roles (CAIO/CDO) and governance
- - AI governance, risk, compliance and regulation
- Prompt fundamentals: context, role, objective, output format
- Good vs bad prompts; live demos
- Rewrite and improve texts, lists and tables
- Translations and adaptations
- Safety rules, verification and control
- Interactive lab with live demos
- Short explanations followed by exercises
- Pair work and plenary mini-exercises
- Course slides (PDF)
- Generic prompt template
- 10 ready-to-use common prompts
- Slide deck
- Prompt templates
Tell us the challenge you want to address
Share your context and we will propose a tailored learning path with objectives, format, timing and expected outcomes.
- Industry and organizational context
- Target audience and cohort profile
- Skills priorities and expected business relevance
- Preferred timing and delivery format
- Objectives and recommended structure
- Workshop or academy format
- Timeline and participation model
- Outputs such as capability maps, projects, certifications and KPI dashboards