ONLINE COURSE
AI-Driven Leadership: Strategies for the Future
Lead teams, strategy, and growth in the age of AI
How this learning journey unfolds
Key takeaways
Identify how leaders create the conditions for effective development of generative AI, agentic AI, and predictive analytics capabilities.
Develop a plan to create those conditions, including anticipating likely barriers and strategies for success.
Assess organizational data readiness for AI and promote a culture of data excellence.
Understand how to configure workflows across these technologies, including reskilling needs and change management.
Design and implement workflows and assess their impact.
Assess the evolving role of managers and their responsibilities in the context of increasing reliance on AI technologies.
By the end of this course, you will be able to
Who is this online course for?
Mid- to senior-level executives including CEOs, CTOs, and leaders with decision-making authority who want to integrate artificial intelligence into their organizations
Digital transformation managers and other managers leading organizational digital initiatives who seek to adapt their leadership capabilities for the digital era
Entrepreneurs and business owners looking to implement AI strategies in their businesses
Leaders of data teams seeking to increase their impact within their organization by employing various AI tools and systems
Past participant profiles
Work experience
Top industries
Top profiles
Course outline
Understand the leadership actions that drive adoption and effective use of predictive analytics tools.
Illustrate leadership activities that foster effective implementation of predictive analytics tools and how they influence team members' adoption and utilization of these tools.
Assess current frameworks, organizational structures, and evaluation methods for predictive analytics.
Develop a new framework, propose a novel organizational structure for AI implementation, and outline innovative evaluation procedures for AI initiatives.
Learn how leaders guide the successful implementation of generative AI systems across teams and workflows. Learners will also explore the distinction between agentic and non-agentic systems, including their implications for governance, scaling, and organizational design.
Describe differences between predictive analytics and generative AI, including differing risks and opportunities.
Summarize leaders’ activities that foster effective generative AI implementation and how they shape team members’ adoption and use of these tools.
Evaluate existing framing, structuring, and evaluation schemes for generative AI.
Create new framing for a generative AI strategy, draw up a new proposal for AI structuring, and define new AI evaluation processes.
Understand maturity models for generative and agentic AI adoption, from experimentation to enterprise-scale systems.
Strong AI systems require strong data foundations.
Evaluate your current organizational data culture, focusing on issues related to data quality, misuse, silos, integration, and governance.
Assess organizational data readiness for generative AI.
Formulate a governance, compliance, and ethical framework for sustaining high-quality, well-governed data.
Understand how ML changes processes, workflows, and decision-making.
Discover the different ways that ML workflows are configured.
Predict when a change process or tool is likely to produce resistance or adoption.
Plan or design an ML workflow.
Explore how modern AI systems can be embedded into day-to-day operations.
Understand the different ways in which generative AI workflows are configured.
Recognize essential evaluation practices for generative AI workflows.
Plan or design a generative AI workflow.
Examine how leadership roles evolve when AI becomes part of management systems.
Examine how managers are using AI to design organizations, focusing on AI’s role in decision-making, structuring information flows, and coordinating resources.
Describe the risks and opportunities associated with algorithmic management.
Conceptualize a tool to aid in an organizational or managerial function.
* Familiarity with the human-centered design process is helpful.
Capstone project
In the capstone project, you will apply the core frameworks to plan the implementation of an AI capability within an organization. You will identify and prioritize high-impact use cases, assess organizational readiness, and evaluate the potential impact on workflows, teams, and business performance.
Using the leadership strategies explored throughout the course, you will examine likely barriers to adoption, define approaches for change management and reskilling, and outline the governance conditions required for successful execution. Through this capstone, you will strengthen your ability to lead AI transformation initiatives while applying practical frameworks to real-world organizational challenges.
Frameworks and methods you will use
This course equips you with practical frameworks and approaches to evaluate, apply, and lead AI adoption in organizational settings. The focus is on helping leaders make better strategic decisions in environments in which AI capabilities, workforce expectations, and competitive pressures are rapidly evolving.
You will work with:
Frameworks to assess areas in which predictive analytics, agentic AI, and generative AI can create value
Methods to identify high-impact use cases and avoid low-value initiatives
Approaches to evaluate organizational readiness across data, teams, and workflows
Decision frameworks for integrating AI into leadership and management systems
Techniques for redesigning workflows to combine human expertise with AI capabilities
Structured approaches to manage governance, adoption barriers, and change effectively
Frameworks to evaluate the maturity and scalability of generative and agentic AI systems within organizations
Course walkthrough
Live sessions with Stanford faculty
Learn with an AI Tutor for a seamless experience
Hands-on assignments to apply AI strategies and workflows
Real-world case studies on AI adoption and transformation
Practical learning to build AI-ready organizations
Certificate of Achievement from Stanford Online
Instructor
Melissa Valentine
Associate Professor of Management Science and Engineering, Stanford University
Melissa Valentine is an Associate Professor at Stanford University in the Department of Management Science & Engineering and a Senior Fellow at the Stanford Institute of Human...
Certificate of Achievement from Stanford Online
All learners who successfully complete the course will be awarded a Stanford Online Certificate of Achievement. This certificate serves as a testament to your dedication and expertise in the subject matter. The Certificate of Achievement for an individual course will be issued in a digital badge format, allowing you to share your accomplishments with your network, verify your credentials to employers, and communicate the scope of your acquired expertise. In addition, you will earn 4 Continuing Education Units.
Learners feedback
I'm excited to be leading at a time when AI is reshaping our world. The focus on human-centered leadership during this technological shift was invaluable, and I'm confident the insights I gained in this course will be crucial in driving companies' successful AI transformation....
Frank Lieber
CEO, Co-founder
AIvolve Leadership Dynamics GmbH
This course gave me an opportunity to systematically learn how to apply ML/AI at work as a leader. The academic approach of teaching by showing evidence with almost unfiltered and very recent real world case studies end-to-end from different industries supplemented with in-depth analysis is refreshing and effective....
Weijuan Davis
Sr. Manager/GenAI Architect,
Capgemini
The AI-driven leadership course offered a profound exploration of how leaders can effectively integrate and harness AI within an organizational context. It wasn’t just about understanding AI technologies; the course delved deep into how leaders can drive cultural and strategic transformations to enable AI's successful adoption and impact....
Chhavi Saxena
Senior Lead Developer,
SAP SuccessFactors
FAQs
Studying online with us extends past a strictly digital learning experience. With Stanford Online, you’ll have the chance to:
Attend international workshops and live webinars.
Collaborate and engage with Stanford professors, instructors, and contributors.
Meet and network with other course participants from all over the globe.
Yes. All participants who successfully complete the course will be awarded a Stanford Online Certificate of Achievement delivered in a digital badge format and verified on the blockchain, along with Continuing Education Units (CEUs). This credential recognizes proficiency in the course material. The digital badge format allows you to share your accomplishments with your network, verify your credentials to employers, and communicate the scope of your acquired expertise.
Applicable taxes will be calculated and added at checkout in accordance with country/state regulations.
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Receive an advanced certificate with this integrated learning journey
Leading with AI: Strategy and Product Transformation
Benefit from up to 7% savings on this learning journey
Leadership in the age of artificial intelligence requires more than understanding the technology. It demands the ability to evaluate where AI creates value, guide its adoption across the organization, and translate those decisions into meaningful product and business outcomes.
Leading with AI: Strategy and Product Transformation is a 12-week integrated learning journey from Stanford Online designed to help professionals develop the judgment required to lead AI initiatives and guide AI-driven product decisions. The program brings together two courses: AI-Driven Leadership and AI-Powered Product Innovation, enabling you to connect strategy with real-world impact.
Register now and boost your professional trajectory.
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