Course Overview

Artificial Intelligence for Leaders equips executives and senior managers with the essential knowledge to lead AI transformation initiatives. Developed and Delivered By Jeruel, this comprehensive course targets C-suite executives, directors, and managers who need to make strategic AI decisions without technical expertise. The program covers practical frameworks for identifying high-value AI opportunities within your organization, with over 40% of participants implementing AI projects within six months of completion.

The curriculum balances strategic and practical elements, covering AI fundamentals (machine learning, natural language processing, computer vision), use-case identification, data requirements, and capability building. Participants gain crucial insights into AI governance, ethics, and risk management while developing leadership skills for managing cross-functional AI teams. Jeruel's hands-on approach ensures you'll leave with actionable strategies to measure AI ROI, establish meaningful KPIs, and successfully embed artificial intelligence capabilities throughout your organization.

Developed and Delivered By Jeruel

Learning Objectives

• Grasp the core AI building blocks: machine learning algorithms that improve with data, deep learning networks that mimic brain function, natural language processing that helps computers understand text, and computer vision systems that interpret images.
• Spot AI opportunities that matter. Evaluate where AI can create real value for your organization. Connect potential use cases directly to your strategy and product roadmaps to ensure meaningful impact rather than chasing trends.
• Create your AI adoption roadmap that maps out data strategy, tech infrastructure, and talent needs. Build a clear path for bringing AI capabilities into your organization.
• Evaluate whether to build AI solutions in-house or buy from vendors. Learn key criteria for assessing AI vendors and making procurement decisions that align with your organization's needs and capabilities.
• Create clear frameworks for AI governance, ethics, and risk management. Set boundaries that protect users while allowing innovation. These guardrails ensure your AI systems remain responsible and compliant.
• Establish clear metrics and KPIs to track your AI initiatives' performance. Build business cases that show real ROI. You'll know exactly what success looks like and can prove when you've achieved it.
• Guide AI transformation across your organization. Build cross-functional teams, create targeted upskilling plans, and lead change that sticks. Break down silos between departments to embed AI capabilities where they'll create the most value.