The future of work is AI-powered. AI systems are transforming jobs by automating tedious tasks so we can focus on more meaningful work. But most of us have just started to explore the true potential.

What if you could harness AI's capabilities to accelerate your team's skills, increase workplace satisfaction, and build a more inclusive future of work?

• Our AI skills programs make it possible. Learn from AI experts how AI can automate repetitive processes so your people can focus on creativity, critical thinking, and human connection.

• Gain hands-on experience with AI applications that streamline workflows, freeing up time for upskilling, innovation, and more fulfilling work. Discover how AI can augment diverse teams and create new accessible roles.

• We believe AI should empower people to find more joy and purpose in their work. Our graduates will be equipped to lead their teams into an AI-powered future with greater efficiency, capability, and fulfillment.

• The future of work is human-centric. Join us to deeply understand how AI can improve work and prepare your team to flourish.

The future belongs to the AI-fluent.  Artificial intelligence is transforming how we live and work at an astonishing pace. Developing the ability to understand, evaluate, and apply AI through practical use cases is quickly becoming an essential leadership capability.

What if you could unlock the full potential of AI by learning while doing—boosting your career, your business, and your positive impact on the world?

• Our AI education programs focus on practical applications, preparing you and your team with the hands-on AI skills needed to thrive in the age of algorithms.  

• Gain a rigorous yet accessible understanding of the AI technologies reshaping our world and how to apply them to real-world challenges.  

• Learn by doing—prototyping and implementing AI solutions directly tailored to your unique goals. Gain experience with practical techniques for designing inclusive, ethical AI systems that uplift your people and foster trust.  

• Understand best practices and communicate clearly about AI’s role, navigate complex use cases, and strategically integrate AI to drive measurable results. Empower your workforce for the human-AI collaborative future with applied learning that scales impact.  

• Don’t just learn about AI—experience its power through hands-on use cases that prepare you to lead with confidence.

The future is now. Artificial intelligence tools are transforming how we live and work, but most of us have just started to understand the true potential.

What if you could unlock the full capabilities of AI tools to significantly accelerate your future impact by understanding how to compare AI tool choices ?

• At AI415, we don't just teach you how to use AI tools. We teach you how to develop better skills through dynamic, personalized learning pathways that adapt to your goals and expertise.  

• Gain a rigorous yet accessible understanding of how leading AI systems work, how they can support skill development, and how to implement them effectively.  

• We empower you to grow with hands-on applied learning, creating a continuous improvement loop tailored to your specific needs. Explore emerging AI applications designed to refine your abilities, and gain the insight to determine what works, what doesn’t, and how to pivot intelligently.  

• Our blended approach combines skill-building with critical thinking. Learn to ask incisive questions about bias, transparency, and ethics, while refining your technical expertise through design thinking and systems logic.  

• Don't just learn to use AI. Learn to harness it for dynamic skill growth. Join us and build your personalized pathway to excel in the algorithmic age ahead.  

The future of enterprise is AI-infused. As a senior leader, you recognize AI's immense potential to transform your business, but the ideal human-AI configuration takes time to identify. Integrating a learning while doing approach helps employees to organically gain new skills.

What if you could see through the fear and unlock AI's true potential ?

The future of work is AI-enabled, but dependent upon curated data and context for the AI system. As a leader, you recognize AI’s potential while noticing that results are good but not entirely consistent. The real-world capabilities of AI systems can be fully harnessed when the context is curated. 

What if you could make it easy for your team to share feedback that is consistently incorporated into AI generated outputs that improve with use ?

HR is already partially AI-driven. As leaders, you recognize AI’s potential to supercharge innovation and growth. Hype and inconsistent regulation obscures what’s really possible with your skill development for today versus tomorrow. 

What if you could unlock AI’s true potential to augment skills while on-boarding through dynamic learning pathways ?

• AI Fundamentals - Understand core AI concepts like machine learning, neural networks, and natural language processing through interactive videos and demos.

• Responsible AI Principles - Learn principles like transparency, fairness and accountability to ethically design and deploy AI systems.

• Certificate: AI-Ready Leader - Demonstrate core knowledge to contribute to AI projects as an informed leader.

• Identifying AI Opportunities - Conduct structured opportunity assessments to identify high-impact AI use cases aligned to business goals.

• Building an AI Transformation Roadmap - Develop a phased roadmap for AI adoption across operations, products and services using C-suite tools.

• Leading Organizational Change - Simulate strategies for securing buy-in, upskilling staff and managing the human impacts of AI change.

• Certificate: AI Strategist - Apply frameworks to develop an organization-wide AI strategy.

• Scoping AI Projects - Define MVP AI projects including data requirements, risks and mitigation tactics with expert guidance.  

• Managing Data for AI - Gain hands-on practice with data collection, cleansing, labeling and storage to fuel AI using real-world tools.

• Integrating AI Responsibly - Implement bias testing, human oversight and controls to integrate AI safely using ethical design tools.

• Monitoring and Iterating AI Systems - Use provided models to A/B test and monitor AI systems for improving performance and managing risks.

• Certificate: AI Implementer - Lead scoped implementation of AI pilots from design through deployment.

Module 1 - Evaluating AI for Data Analysis

• Conduct tests using sample data queries and reports

• Evaluate AI capability to interpret spreadsheets and business context 

• Analyze effectiveness in data cleaning, aggregation, and visualization  

Module 2 - Building an Integration Framework

• Identify a set of analysis tasks for initial automation  

• Develop clear protocols for human verification of AI-generated outputs.  

• Define a collaborative workflow between human analysts and AI

Module 3 - Piloting for Quarterly Reporting 

• Set up a pilot project to analyze last quarter's data

• Establish key performance metrics such as accuracy and time savings

• Design a structured testing framework to run in parallel with existing systems 

• Collect detailed feedback from analysts to assess usability benefits

By the end of the course, learners will gain hands-on experience in systematically testing and piloting AI with real company data. They will be equipped to determine whether and how to integrate AI into their team’s quarterly analysis process, enhancing efficiency, generating deeper insights, and boosting productivity.  

Module 1 - Evaluating AI as a tool to support your team

• LLMs for empathy, emotional intelligence and communication skills

• Assess suitability for coaching, mediating and advising teams

• Review privacy safeguards and transparency features

Module 2 - Building an Integration Framework

• Identify team challenges and establish baseline metrics

• Develop protocols for AI access to data and context

• Define human/AI collaboration approach

Module 3 - Piloting for Team Engagement

• Configure pilot for improving team cohesion

• Establish dashboards to track the trend 

• Structure testing with different teams and scenarios

• Gather user feedback on AI coaching ability

By course end, learners will have hands-on experience strategically testing and piloting intelligent systems to determine if and how to integrate AI to help teams communicate, align, and resolve conflicts for greater cohesion, empathy, and productivity.

Module 1 - Evaluating AI Image Generation for Workplace Graphics

• Test image generation for sample motivational prompts

• Assess ability to create customized graphics for teams

• Review considerations for workplace culture and tone

Module 2 - Building an Integration Framework

• Identify types of graphics and messages to generate

• Develop prompts and protocols aligned to company values

• Define workflow for collaborative human/AI design

Module 3 - Creating Motivational Workplace Graphics

• Configure pilot for key graphic concepts

• Establish metrics like iteration speed, adoption, morale

• Structure testing across teams, roles, and events

• Gather feedback from employees on generated designs

By course end, learners will have hands-on experience strategically testing and piloting AI image generation to determine if and how to integrate it to rapidly customize motivational graphics that resonate with their workplace culture and employees.

Module 1 - Scoping AI Applications

• Conduct structured assessment of AI opportunities for your workplace

• Prioritize use cases based on impact and feasibility criteria

• Develop risk mitigation tactics for top projects

Module 2 - Building an Integration Framework 

• Design protocols guiding employee AI access and use

• Create standards for transparent and ethical AI practices

• Define employee training programs on AI collaboration

Module 3 - Implementing the AI Adoption Framework

• Socialize framework across teams and leadership

• Launch pilot projects to test integration support

• Iterate on policies based on user feedback and insights

• Measure adoption success through surveys and engagement

By course end, learners will have developed a comprehensive framework for empowering employees to adopt AI through prioritized use cases, policies and training to ensure responsible and effective integration.

Module 1 - Evaluating Current Capabilities

• Survey team members on data skills and deficiencies

• Audit recent analyses to gauge proficiency

• Identify priority upskilling areas based on goals

Module 2 - Developing Assessment Framework

• Select criteria for data literacy like tools proficiency, analysis skills

• Design assessments tailored to roles and use cases

• Set benchmarks aligned to business analytics needs

• Plan ongoing assessment cadence and methods

Module 3 - Monitoring Progress Over Time

• Implement assessments to benchmark capabilities

• Track proficiency improvements across individuals and teams

• Provide learning resources tailored to identified gaps

By course end, learners will have implemented structured assessments of team data proficiency over time, providing a benchmark for developing targeted educational resources to continuously improve data literacy across the organization.

Module 1 - Evaluating AI Learning Resources

• Curate quality AI education materials from a variety of data ilteracy platforms 

• Assess relevance of courses/content to team needs 

• Prioritize modules with applicable tools/demos

Module 2 - Integrating AI Content 

• Develop learning paths combining AI theory, examples, and hands-on labs

• Contextualize external content with internal data use cases

• Design activities applying AI techniques to company data

• Create supplemental materials filling identified gaps

Module 3 - Monitoring Learning Outcomes

• Deploy tailored AI learning program for employees

• Evaluate proficiency improvements in target skill areas

• Iterate curriculum based on learner feedback and analytics

By course end, learners will have effectively integrated external AI education content into targeted upskilling resources for employees to augment data proficiency with machine learning capabilities.

Module 1 - Identifying Key Datasets

• Catalog available structured and unstructured data

• Map relationships between siloed datasets

• Prioritize high-value datasets to integrate

Module 2 - Strategizing Data Aggregation

• Select tools for extracting, transforming and loading data

• Design aggregated data schema aligned to analysis needs

• Develop data pipelines and ETL workflows

• Establish data governance and access protocols

Module 3 - Monitoring Data Quality

• Implement validation checks in aggregation workflows

• Track key data quality metrics like accuracy, completeness

• Iterate on data pipelines to improve reliability

By course end, learners will have developed an automated workflow to aggregate disparate datasets into a unified analytics platform, enabling more holistic business insights.