How to transition into a career in AI as a senior leader
By: Janice Mejías Avilés, Edited by: Gabriela Pérez Jordán
Published: March 19, 2025
The adoption of artificial intelligence (AI) in the workplace is reshaping roles, often creating skill gaps that organizations must address. Senior executives are no exception to this shift.
Discover how AI is transforming leadership and explore three steps you can take to position yourself as an AI-driven senior leader.
Why should you consider a career in AI as an executive?
Business leaders — and those aspiring to leadership positions — who gain AI knowledge and experience may be better positioned to drive operational efficiency and remain competitive amid workplace transformations. Those with AI expertise may also stand out as stronger candidates for senior leadership roles than peers who have yet to adapt.
By integrating AI into your leadership approach, you may:
- Drive business growth by implementing AI models to optimize operations or launch new ventures.
- Increase efficiency and employee engagement by automating repetitive tasks, allowing you and your team to focus on valuable initiatives.
- Future-proof your career by developing AI expertise.
Three steps to transition into AI as an executive
Step 1: Learn the fundamentals of AI
You don't need to become an AI engineer, but as an executive, you must understand AI's business applications and governance challenges.
Some core AI business concepts you may want to explore include:
- Machine learning (ML) and automation, which may improve operational efficiency and data-driven decision-making.
- Large language models (LLMs) and natural language processing (NLP), which are used for predictive analyses and customer-facing tools (such as chatbots).
- Robotics, which may streamline operational processes in specific industries.
- AI ethics and responsible use for transparency, accountability, and compliance.
The best way to learn about AI is to use it. Leaders should experiment with AI to understand its capabilities firsthand. Building a simple project that applies to your industry can be a great way to start.
Another effective way to gain AI skills is through AI executive education programs tailored for business leaders, senior managers, and entrepreneurs. edX delivers online Executive Education programs from MIT Sloan School of Management, Harvard Business School, and the University of Oxford, focusing on AI strategy rather than coding.
Executive education programs provide the opportunity to learn alongside peers and analyze real-world case studies where AI has been successfully implemented. Some programs may also guide executives in developing an AI implementation roadmap for their organization.
Step 2: Understand how AI is transforming your industry
Analyzing case studies from your sector and beyond may help you identify AI-driven solutions to improve processes, scale operations, or unlock new business opportunities.
Explore some examples of how AI models and systems are being used across industries:
- Retail and e-commerce: Personalize user experiences, predict delivery times, and implement LLM-powered chatbots for customer support.
- Fintech and banking: Detect fraud, identify inconsistencies in financial ledgers, and improve the cardholder experience.
- Media: Recommend content, summarize content, and target contextual advertising.
- Healthcare: Enhance diagnostics, personalize treatment plans, and optimize biotech and pharmaceutical research.
For executives seeking industry-specific AI insights, some of edX's AI executive education programs offer specializations in healthcare and business strategy. These programs provide practical use cases that apply to your field and may inform strategic planning and leadership decisions.
Step 3: Implement AI strategically in your organization
Once you've built solid foundational knowledge of AI, explored industry use cases, and gained hands-on experience on a low-stakes project, you may be ready to develop AI strategies for your organization.
This strategy could involve:
- Designing a roadmap for AI adoption in your company.
- Implementing existing AI tools to automate processes or improve efficiency with minimal development effort.
- Developing proprietary AI solutions tailored to your organization's needs.
- Creating new AI-powered products and services.
- Supporting the creation of an in-house AI team by upskilling or reskilling employees.
By building AI expertise through practical applications, continuous learning, exploring AI applications in your sector, and promoting its strategic and ethical implementation in your organization, you may position yourself for an AI-driven leadership role.