AI FOR COMPANIES
AI and Data Mini MBA
Master AI to Lead Business Change.
A transformative 12-week program for business leaders to master AI, giving them the confidence and skills to drive growth, boost efficiency and outpace the competition.
25 participants
48 hours, 12 weeks (4 hours a week)
Virtual delivery
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AI Skills Training
Turn Potential into Practice. Then into Progress.
This hands-on program brings together high-potential business leaders in small peer groups to explore, apply and lead AI transformation. Through real-world projects, you’ll build strategic AI and data fluency, experiment with tools like ChatGPT and Microsoft Copilot, and drive change aligned to your organization’s goals.
Starts Monday 1st September 2025
Master Generative AI Tools
Learn what generative AI can and can’t do, gain hands-on experience applying real business challenges to tools like ChatGPT and Microsoft Copilot, and create a practical playbook to confidently deploy AI across your own business.
Build a Business Case for AI
Separate real value from buzz. Analyze emerging AI capabilities, evaluate real use cases, and identify the data foundations needed to build a business case that drives action, not just interest, to implement high-impact AI solutions.
Drive Sustainable AI Transformation
Explore what it takes to lead sustainable AI transformation, from ethical risks and future trends to leadership behaviours and what your business needs to do right now.
AI COURSE BREAKDOWN
What This Course Includes
Work alongside a select group of business leaders to build AI capability through hands-on projects. Gain strategic insight, experiment with real tools like ChatGPT and Microsoft Copilot, and learn how to lead AI initiatives that deliver meaningful business impact in line with your organization’s goals. Each week includes around 4 hours of work, spread across workshops, learning kits, application tasks and group coaching.
This module provides an introduction to the fundamentals of generative AI, examining the organisation's current use of AI and identifying future goals. Participants will explore AI’s capabilities, opportunities, limitations, and where it can automate or augment tasks.
Learning Outcomes:
• Understand the key capabilities and limitations of AI.
• Identify opportunities for AI integration within their role.
• Gain clarity on the organisation’s internal AI policies.
This module provides an introduction to the fundamentals of generative AI, examining the organisation's current use of AI and identifying future goals.
Participants will explore AI’s capabilities, opportunities, limitations, and where it can automate or augment tasks.
Learning Outcomes:Understand the key capabilities and limitations of AI.
Identify opportunities for AI integration within their role.Gain clarity on the organisation’s internal AI policies.
This module introduces participants to prompt engineering, teaching them how to craft effective prompts to interact with AI tools. Participants will develop their own prompts relevant to their roles, and explore a structured framework for advanced prompting techniques.
Learning Outcomes:
• Develop a more sophisticated approach to crafting AI prompts.
• Learn how to use a structured framework for prompt engineering.
• Gain practical experience creating prompts for immediate application.
In this module, participants will learn how to use AI for data analysis, reducing the time spent on data processing and reporting. They will work with AI tools to visualise data and generate insights, including exporting findings into presentations.
Learning Outcomes:
• Analyse and visualise data using AI tools.
• Learn how to use AI to automate data reporting processes.
• Gain the ability to export AI-driven insights into professional visualisations.
This module focuses on identifying opportunities for automation within workflows. Participants will prototype automation flows and AI agents without the need for coding, exploring how AI can streamline processes within their teams.
Learning Outcomes:
• Identify automation opportunities in individual and team workflows.
• Design and prototype an AI automation flow.
• Understand how to deploy automation solutions with technical support.
Participants will explore the latest AI tools and assess their potential impact on business operations. They will be encouraged to identify relevant tools and pitch innovative ideas for their application within their organisation.
Learning Outcomes:
• Stay up-to-date with emerging AI tools and trends.
• Assess the relevance and business impact of new AI tools.
• Develop and pitch a business case for adopting an AI tool.
Participants will explore the latest AI tools and assess their potential impact on business operations. They will be encouraged to identify relevant tools and pitch innovative ideas for their application within their organisation.
Learning Outcomes:
• Develop a change-management mindset towards AI adoption.
• Create actionable plans to implement AI strategies within their teams.
• Foster an entrepreneurial approach to driving AI innovation.
Module 1 - Now: Master Generative AI Tools
This module demystifies generative AI tools and helps participants learn how to use them confidently to business challenges. Working in small groups, participants will learn how to prompt tools like ChatGPT, Microsoft Copilot, Google Gemini and Claude. They will also conduct a gap analysis to identify team-level needs, and begin creating a practical AI playbook aligned to your companies internal platforms, tools, and policies.
What's included in week 1:
This week sets the strategic context for the program. Participants gain a high-level understanding of how Generative AI tools work, where they’re being used across functions, and what the risks and opportunities are for their business. As part of this, they will conduct a gap analysis to assess their team’s current AI maturity and identify areas of opportunity.
Learning Outcomes:
- Understand the mechanics and limitations of generative AI tools.
- Identify and evaluate high-potential use cases for GenAI in your business area.
- Conduct a team-level gap analysis to benchmark AI maturity and surface opportunities.
- Discuss risks, compliance issues, and ethical considerations in applying AI at scale.
What's included in week 2:
Participants dive deep into prompt engineering, learning the structure and strategy behind effective prompting. They’ll experiment with prompt chaining, breaking down complex business problems into sequences of prompts, and solving real tasks like report drafting, meeting prep, or stakeholder communication.
Learning Outcomes:
- Apply prompt frameworks and chains to complete complex, multi-step business tasks.
- Use Generative AI tools to enhance efficiency in planning, writing, and decision support.
- Analyze and improve the quality of outputs using structured iteration techniques.
- Create a shared prompt library relevant to their function or team.
What's included in week 3:
In this week, participants build on the previous week and apply Generative AI tools to real, day-to-day work. Each participant chooses a recurring task and uses AI to redesign or augment it, using internal platforms where possible. Groups will also begin building the first version of their team AI playbook, documenting approved use cases and prompts.
Learning Outcomes:
- Redesign a real business process or workflow using Generative AI.
- Ensure that Generative AI usage aligns with your organization’s platforms, tools, and governance frameworks.
- Begin documenting use cases, prompts, and safe usage guidelines for inclusion in your team AI playbook.
What's included in week 4:
This study week is dedicated to consolidating learning and producing a tangible output: the AI playbook. Working in groups, participants will finalize a document that outlines where, when, and how to use Generative AI in their function.
Learning Outcomes:
- Finalize a team-level AI playbook that includes: use cases, tool guidance, prompts, and risk considerations.
- Synthesize group insights into a clear, actionable guide that aligns with business goals and internal policy.
- Prepare to present and socialize the playbook internally as a starting point for broader adoption.
Module 2 - Next: Build a Business Case for AI
This module shifts the focus from individual productivity to broader workflow and process transformation. Participants will explore the emerging world of agentic AI, learn how to map AI-enabled workflows, and build a strong, business-oriented case for implementing AI within their function or business area. The module culminates in writing a business case for AI investment into a specific area, outlining both opportunities and risks.
What's included in week 5:
This week introduces participants to the concept of agentic AI which can take multi-step actions across workflows. Participants will explore where agent-based systems are already being used in business today, assess their maturity, and consider where these capabilities could be applied within their own teams.
Learning Outcomes:
- Understand the evolution from Generative AI tools to agentic systems.
- Identify workflows or tasks that are suitable for agentic automation.
- Assess readiness and risks of adopting agentic workflows.
What's included in week 6:
This week focuses on how to use data more strategically to support better business decisions, especially in the context of AI-enabled workflows. Participants will explore how to think like a data analyst without needing technical skills, learning how to ask the right questions, define clear success metrics and interpret outputs. We will also explore why first-party data is becoming a strategic advantage in a world where AI is becoming democratized.
Learning Outcomes:
- Learn to approach problems like a data analyst: define a question, gather relevant data, and interpret results with business impact in mind.
- Understand the business value of first-party data as a defensible asset in a commoditized world of AI.
- Use data insights to strengthen your AI business case by linking opportunities to measurable outcomes.
What's included in week 7:
This week equips participants with the frameworks and tools to articulate the value of an AI initiative. Participants will learn to scope an AI-enabled workflow, quantify the potential benefits (time, cost, quality), identify risks, and structure a business case that can frame an opportunity to invest in AI.
Learning Outcomes:
- Scope an AI-enabled process or workflow opportunity.
- Calculate potential ROI based on time savings, efficiency gains, or quality improvements.
- Identify risks, barriers, and stakeholder concerns that must be addressed in the business case.
- Structure a business case for AI using a pre-defined template from Sequioa Capital.
What's included in week 8:
This project week is dedicated to creating a pitch for a formal business case for AI investment. Working in groups, participants will consolidate their findings into a concise presentation that is ready to pitch internally. The business case will be structured using an established Sequioa framework.
Learning Outcomes:
- Finalize a complete business case for an AI opportunity.
- Create a clear, value-driving presentation to pitch the idea, focusing on opportunities and risks.
- Practice pitching this business case to other teams.
Module 3 - Long: Lead Long-Term Transformation
This module helps participants step back from tools and use cases to consider the broader strategic implications of AI. Through an exploration of emerging trends, participants will develop a clear hypothesis about how AI will reshape part of their business or industry, and work with their groups to create a whitepaper demonstrating thought leadership on the topic.
What's included in week 9:
This week introduces participants to the evolving landscape of AI capability, drawing on frameworks such as OpenAI’s five levels of AI progression. Participants will examine how fully autonomous, AI enabled organizations could be a reality by 2030, and what this means for incumbent businesses.
Learning Outcomes:
- Identify and describe key trends shaping the future of AI capabilities.
- Apply a structured framework (e.g. OpenAI’s Five Levels) to assess the direction of your industry or sector.
- Evaluate how emerging capabilities could impact your company.
- Begin forming a strategic hypothesis for your whitepaper based on industry trends.
What's included in week 10:
This week focuses on how people and culture are an integral part of AI transformation. Participants will reflect on digital transformation, and identify the operational and leadership requirements that helped organizations adapt.
Learning Outcomes:
- Identify key enablers and blockers of successful AI transformation, with a focus on growth mindset.
- Evaluate how team structures, responsibilities, and capabilities need to evolve in a VUCA environment.
- Assess organizational readiness for sustained change and innovation.
- Define clear leadership behaviours that will help drive AI adoption at scale.
What's included in week 11:
In this week, participants turn their focus to building resilience and adaptability into their organization’s approach to AI through Agile workflows. They’ll explore how to move beyond pilot projects toward scalable innovation, and the value of AI Minimum Viable Products (MVP’s). They’ll also explore how adaptability and risk mitigation are crucial as part of their group whitepaper.
Learning Outcomes:
- Describe what continuous, responsible innovation looks like.
- Link AI adoption to long-term performance metrics (e.g. speed, cost, quality, resilience).
- Position your perspective in a way that is credible and actionable, whilst also accepting that agility can sometimes be messy.
What''s included in week 12:
This final week is focused on producing a short, insight-driven whitepaper that presents a well-reasoned hypothesis about how AI will impact your business, team, or sector.
Learning Outcomes:
- Deliver a whitepaper that synthesises research, insight, and business impact around AI.
- Clearly articulate a hypothesis about where AI is heading and what it means for your team or organization.
- Position yourself as a credible internal voice on AI transformation with a portfolio piece that can be shared both internally and externally.
This program is for teams that want to
Boost AI skills and data literacy
Equip decision-makers to guide AI adoption with clarity, setting direction, aligning teams, and driving measurable results across the business.
Bridge the AI Knowledge Gap
Build practical, future-ready skills that empower leaders to go from AI-aware to AI-capable - no technical background required.
Operationalize AI, Fast
Move from experimentation to execution. Identify high-impact use cases, deploy tools effectively, and scale AI solutions that deliver immediate business value.
Testimonials
How Edifai Makes an Impact
"It was absolutely outstanding. Perfect amount of content and application of content. Tone was amazing, and All very applicable to leadership. Best training I have ever had."
“Very instructive session and all use cases were very well explained. A great introduction for people unfamiliar with AI.”
“The facilitators are clearly experts and very helpful. A great, interactive approach to learning.”
“The exercises were productive and allowed for helpful real-world examples of ways to use AI. I came away with a much better grasp of CoPilot and how to use it and I'm looking forward to exploring it more. Thank you!”
"It was a really great and insightful session. I’ll be taking a lot of this away with me to use in my everyday work and share the knowledge with my team."
Meet the Experts
Martin Talks
AI Expert
At the edge of AI, society and data ethics, Josefin brings a desire to help shaping a desirable, more responsible future. Josefin has worked with digital & emerging technology transformation and learning programs spanning across all business functions.
Josefin Ittichai
Facilitator
At the edge of AI, society and data ethics, Josefin brings a desire to help shaping a desirable, more responsible future. Josefin has worked with digital & emerging technology transformation and learning programs spanning across all business functions.
Pilar Barrio
Facilitator
Pilar Barrio is a digital transformation consultant and a facilitator, who has been at the forefront of emerging technology and its application to business, media and customer experience since 2006.
Niall McKinney
Non-exec Chair
Jeremiah Johnson
Community Manager
Daniel Solomons
Digital Transformation
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