Generative AI in the Workplace
ONE OF THE THINGS we are best known for is our ability to explain difficult technologies in a way that people will understand and feel confident about. Just as we did in the 1990s when Microsoft Windows was a new thing, and all the way through these fast-moving decades, we have delivered learning sessions that really work. That's why we are so proud of this course, Generative AI in the Workplace. It has been designed for leaders, and managers and regular team members who are interested, hesitant or curious about bringing Generative AI technologies into their organizations. This program will deliver the knowledge and skills necessary to identify potential use cases, understand ethical considerations, prepare teams and organizations for its adoption, provide implementation plans and undergo the change process.
Class 1: Introduction to Generative AI
To understand the fundamental concepts of Generative AI and its applications in various industries.
- Understanding AI and its subsets (Generative vs. Discriminative)
- Definitions: generative AI, Large Language models, basic AI and ML
- Case studies of successful Generative AI implementations in different industries
- How AI does what it does
- What can it not do (at this point), including the dangers of hallucinations
- How pervasive is AI? How much of a threat is it?
- How will generative AI impact jobs?
- Resources: where you can go to find out more - and keep on finding out
Class 2: Ethical and Legal and Human Considerations in Generative AI
To explore the ethical dilemmas and legal implications associated with using Generative AI in the workplace.
- Ethical considerations in AI development and deployment
- Bias and fairness in Generative AI
- Legal frameworks and regulations related to AI in different industries
- Developing a plan for incorporating transparency and accountability into an AI system.
- Data, security, compliance, culture
- Developing a policy—even if you’re not yet using generative AI
- Security risks
Class 3: Assessing your workplace in preparation for the adoption of Generative AI
- Identifying business goals
- Prioritizing AI solutions against business goals
- SWOT analysis/problems/opportunities/ROI
- The ease of implementation vs. the potential impact on the organization
- Developing a list of use cases to define problems, value proposition, requirements and user experience
- Building a knowledge base
- Identifying low-risk testing grounds and specific primary domains such as customer service, marketing, IT
- Assessing industry specific generative AI tools
- Balancing agains customer needs
- Building an improvement ecosystem
- Taking stock of cultural attitudes – are your people ready for this?
- Competitive analysis – what are your competitors/alies using it for
- Planning how to integrate AI into existing workflows
- Testing and evaluating Generative AI models prior to and after installation
Class 4: Preparing your organization and team for the AI change
To provide definitions, explanations, change management and leadership to an organization
- Principles of change management Offering skills development and learning opportunities including in a sandboxed environment
- Dealing with resistance
- Communication and education issues and opportutnities
- Leading through change in the adoption of generative AI
- Creating a tiger team to develop your generative AI pilot
- Defining objectives, goals, outputs, and OKRs
- Using STEP nd ADKAR techniques
Our sessions are interactive, and wherever possible, used anonymized case studies drawn from the pre-course assessments. Participants are encouraged to work through and solve their challenges, and ongoing post-session support is always available at no charge. Available as a live online classrom event and private coaching.