Implement AI-Enabled Solutions
Evaluate, implement, and manage AI-enabled solutions that integrate people, processes, and technology to improve organizational performance.
Program Design
Program Overview
The proposed 120-unit Bachelor of Science follows a 2+2 pathway from associate-level AI in Business preparation into upper-division study in applied AI for business leadership, organizational strategy, ethics, and human-AI collaboration.
Program Outline of Record Pathway Map KSA Crosswalk Program Costs All Course Outlines
Submitted Program Description
Business leadership for applying AI in real organizations.
The Bachelor of Science in Applied Human-AI Collaboration and Leadership prepares students to lead, design, and manage the integration of artificial intelligence within organizations. Unlike traditional AI programs focused primarily on programming and technical development, this program emphasizes the human, organizational, and strategic dimensions of AI adoption.
Students learn how to work alongside AI systems to enhance decision-making, improve productivity, and drive innovation across industries. The program integrates applied AI literacy, data-informed decision-making, organizational leadership, and ethical governance, equipping graduates to bridge business and technology.
Business Strategy
Data Insight
AI Workflows
Leadership
Ethics
120Total degree units
2+2Stackable pathway model
43Upper-division units
6Capstone units
Vision 2030
A degree at the intersection of three CCCCO strategic directions.
The proposed pathway advances equitable baccalaureate attainment, workforce and economic development, and generative AI literacy. Its local 2+2 structure, living-wage occupational alignment, and responsible AI curriculum connect the program to Vision 2030's goals for equity in access, success, and support.
View the Full AlignmentLearning Outcomes
Students will be able to:
Lead Organizational Change
Lead organizational change and digital transformation across teams and stakeholder groups in AI-enabled environments.
Govern Responsible AI
Apply ethical, legal, regulatory, and societal considerations to responsible AI governance and organizational decision-making.
Develop and Communicate Strategy
Develop and communicate AI strategies aligned with organizational goals, workforce needs, data, and emerging technologies.
Lower Division
AI in Business Foundation
The lower-division component includes Cal-GETC, the general education pattern Fullerton College uses for its bachelor’s degrees, and major preparation through the Artificial Intelligence in Business AS or equivalent preparation.
Upper Division
Human-AI Leadership Core
The upper-division component advances students into applied AI leadership, strategy, governance, project management, and human-centered interaction design.
- BUS 300 - Foundations of Human-AI Collaboration
- BUS 310 - Applied AI for Organizational Decision-Making
- MATH 320 - Data Analytics and Visualization for Leaders
- BUS 340 - Organizational Leadership in AI-Enabled Environments
- BUS 350 - AI Strategy and Implementation
- BUS 360 - Ethics, Governance, and Responsible AI
- CIS 370 - Managing AI Projects and Cross-Functional Teams
- BUS 380 - Human-AI Interaction and Experience Design
- BUS 371 - Advanced Organizational Behavior and Leadership in AI-Enabled Environments
Course Sequence
Proposed major and degree structure.
| Category | Units | Courses |
|---|---|---|
| Lower Division Required | 15 | BUS 108 F, BUS 256 F, BUS 257 F, CIS 201 F, CIS 258 F |
| Restricted Lower Division Electives | 13 | BUS 255 F, BUS 271 F, CIS 142 F, Statistics |
| Upper Division Core | 28 | BUS 300, BUS 310, MATH 320, BUS 340, BUS 350, BUS 360, CIS 370, BUS 380, BUS 371 |
| Upper Division General Education | 9 | ENGL 301 F (existing course; see catalog), PHIL 361 F (existing course; see catalog), MATH 321 Quantitative Reasoning in the Age of AI |
| Capstone | 6 | BUS 495A AI Implementation Capstone I, BUS 495B AI Implementation Capstone II |
| Restricted Electives | 15 | Choose five: MKT 256 F, CIS 210 F, CIS 235 F, CYBR 256 F, BUS 180 F, CISG 105 F |
| Major Only Total | 86 | Combined lower-division, upper-division core, upper-division general education, capstone, and restricted elective units. |
| Cal-GETC | 34 | General education completed with the AS pathway or equivalent preparation. |
| Total Degree Units | 120 | 86 major units plus 34 Cal-GETC units. |
Course Development Detail
Submitted upper-division courses translate AI capability into organizational leadership.
The course descriptions and learning outcomes below reflect the curriculum included in the Cycle 9 BDP submission.
BUS 300 Foundations of Human-AI Collaboration
This course introduces advanced concepts in human-AI collaboration, focusing on how artificial intelligence systems augment human capabilities in organizational settings. Students examine AI capabilities, limitations, and the design of effective human-AI workflows across industries.
- Analyze the roles of humans and AI systems in collaborative workflows.
- Evaluate the capabilities and limitations of AI technologies in organizational contexts.
- Design human-AI collaboration models to improve efficiency and outcomes.
BUS 310 Applied AI for Organizational Decision-Making
This course explores the application of AI tools and technologies to support organizational decision-making. Students learn to interpret AI-generated insights and integrate them into structured decision frameworks.
- Analyze AI-generated outputs to support business decision-making.
- Evaluate AI tools for effectiveness in solving organizational problems.
- Apply decision-making frameworks using AI-driven insights.
MATH 320 Data Analytics and Visualization for Leaders
This course develops advanced data literacy skills for leaders working with AI systems. Students learn to interpret complex datasets, create visualizations, and communicate insights to stakeholders.
- Interpret complex data outputs and visualizations for decision-making.
- Develop data visualizations to communicate insights effectively.
- Evaluate data quality and limitations in AI-driven environments.
BUS 340 Organizational Leadership in AI-Enabled Environments
This course examines leadership strategies for managing organizations undergoing AI-driven transformation, including workforce adaptation, human-AI role design, and leading change in technology-enabled environments.
- Evaluate leadership strategies for AI-enabled organizations.
- Design workforce adaptation strategies for AI integration.
- Apply change management principles to support AI adoption.
BUS 350 AI Strategy and Implementation
This course focuses on the development and execution of AI strategies within organizations. Students assess readiness, identify use cases, and design implementation plans aligned with organizational goals.
- Develop AI implementation strategies aligned with organizational objectives.
- Assess organizational readiness for AI adoption.
- Evaluate the impact and value of AI initiatives.
BUS 360 Ethics, Governance, and Responsible AI
This course explores ethical, legal, and governance issues associated with artificial intelligence. Students examine bias, fairness, accountability, and regulatory considerations in AI systems.
- Evaluate ethical risks associated with AI systems.
- Apply governance frameworks for responsible AI implementation.
- Analyze legal and regulatory considerations related to AI technologies.
CIS 370 Managing AI Projects and Cross-Functional Teams
This course prepares students to manage AI-related projects and collaborate across technical and non-technical teams. Emphasis is placed on project management methodologies, communication, and stakeholder alignment.
- Apply project management methodologies to AI initiatives.
- Coordinate communication across cross-functional teams.
- Evaluate project performance and outcomes.
BUS 380 Human-AI Interaction and Experience Design
This course examines the design of effective human-AI interactions, focusing on usability, trust, and user experience. Students explore how design influences adoption and system performance.
- Analyze factors influencing user trust and adoption of AI systems.
- Design human-centered AI interaction frameworks.
- Evaluate usability and user experience in AI-enabled systems.
BUS 495A AI Implementation Capstone I
Students identify a real-world organizational problem and develop a proposal for an AI-enabled solution. Emphasis is placed on research, feasibility, and project planning.
- Define a real-world problem appropriate for AI-enabled solutions.
- Develop a structured project proposal including scope and methodology.
- Conduct feasibility and stakeholder analysis.
BUS 495B AI Implementation Capstone II
This culminating course requires students to design, implement, and present an AI-enabled solution to an organizational challenge. Students integrate technical, leadership, and ethical considerations.
- Design and implement an AI-enabled solution addressing an organizational need.
- Evaluate the effectiveness and impact of the implemented solution.
- Present findings and recommendations to professional audiences.
KSA Alignment
A workforce competency framework for applied AI leadership.
The National Applied AI Consortium KSA framework is useful as an external benchmark because it separates what students should know, what they should be able to do, and how they should adapt in applied AI workplaces.
Knowledge
AI and data foundations, data governance, analytics, machine learning awareness, generative AI, human-centered design, AI maturity, legal considerations, cloud platforms, systems thinking, NLP, and computer vision awareness.
Skills
Data readiness, visualization, dashboards, prompt engineering, AI tool use, business use-case evaluation, AI-supported problem solving, legal and ethical evaluation, business process automation, and storytelling for business impact.
Abilities
Translate AI into business value, collaborate across technical and business teams, communicate with stakeholders, lead change responsibly, keep current with emerging tools, and apply professional judgment in ambiguous settings.
Capstone
AI Implementation Capstone I & II
Students identify a real organizational problem, develop a proposal for an AI-enabled solution, analyze feasibility and stakeholders, then design, implement, evaluate, and present the solution to a professional audience.
Sources: Proposed Baccalaureate Degree Program Description, AHAI proposed course sequence documents, Fullerton College catalog search links, and National Applied AI Consortium Applied AI Knowledge, Skills, and Abilities report provided by the planning team.