AI Adoption & Enablement Intern

Xcel Energy Inc; Colorado; Hybrid; USD 25,000 - 27,000; Full time

Benefits offered by this job

Pension or 401(k) plan

Paid time off (PTO)

Holidays

Job summary

Xcel Energy is seeking an intern to support Enterprise AI Enablement, driving adoption and enablement programs across the company. You will help create training content, communications, and learning materials, and assist with workshops and success-story collection.

The role emphasizes collaboration with Copilot champions and AI leaders to improve productivity and business processes using AI. This paid internship runs May 24, 2027, with potential extension based on performance.

Qualifications

• Current student or higher enrolled in an accredited college or university.
• Pursuing a degree in Computer Science, Software Engineering, IT, MIS, Data Science, Stats or related.
• Able to work full-time during summer (40 h/wk) or part-time during school year (20 h/wk) in-person.

Responsibilities

• Assist with AI adoption and employee enablement programs.
• Help develop training materials, guides, communications, and learning content.
• Support AI workshops, demonstrations, and employee engagement activities.
• Collect and document AI success stories and business value outcomes.
• Analyze usage and adoption data to identify trends and opportunities.
• Support ongoing improvements to AI resources, websites, and knowledge repositories.

Skills

Python

JavaScript

SQL

Power Platform

Copilot

GitHub Copilot

APIs

Low-code

Microsoft 365

Education

Pursuing computer science degree

Job description

Xcel Energy is seeking an intern to support Enterprise AI Enablement, driving adoption and enablement programs across the company. You will help create training content, communications, and learning materials, and assist with workshops and success-story collection.

The role emphasizes collaboration with Copilot champions and AI leaders to improve productivity and business processes using AI. This paid internship runs May 24, 2027, with potential extension based on performance.