Planning & Implementing an AI Strategy for Business & Technology Leaders

Session Overview: 

1. Introduction to AI and Its Impact:Brief overview of AI concepts. Real-world examples of AI applications in various industries. The transformative potential of AI for businesses. 
2. Understanding Business Objectives: How AI aligns with overall business goals. Identifying key business challenges that AI can address. Assessing the potential benefits and risks of AI adoption. 

 Morning Session: Planning AI Strategy 

1. AI Readiness Assessment: Evaluating the organization's current state of AI readiness. Identifying existing data assets, technology infrastructure, and talent. 
2. Defining AI Use Cases: Interactive exercises to brainstorm and identify specific AI use cases relevant to the organization. Prioritizing use cases based on business impact and feasibility. 
3. Data Strategy and Governance: Importance of quality data for successful AI implementation. Developing a data governance framework. Ensuring compliance with data privacy regulations. 
4. Technology Infrastructure: Overview of AI technologies (machine learning, deep learning, natural language processing, etc.). Assessing the organization's technology stack and potential upgrades. 

 Afternoon Session: Implementing AI Strategy 

1. Talent and Skills Development: Identifying skill gaps within the organization. Strategies for hiring, upskilling, or partnering to acquire necessary AI expertise. 
2. Building an AI Team:Structuring cross-functional AI teams. Defining roles and responsibilities. Fostering a culture of collaboration and innovation. 
3. Vendor Selection and Partnerships: Criteria for selecting AI vendors. Considerations for building partnerships in the AI ecosystem. Case studies of successful collaborations. 
4. Risk Management and Ethical Considerations: Addressing potential biases in AI algorithms. Mitigating risks associated with AI implementation. Ensuring ethical AI practices. 

 Closing Session: 

1. Creating an Action Plan: Developing a roadmap for AI implementation. Setting milestones and timelines. 
2. Q&A and Discussion: Engaging participants in a discussion to address specific concerns and questions. 
3. Next Steps: Providing resources for ongoing learning and support. Encouraging continuous feedback and adaptation of the AI strategy. 
4. Learning Outcomes:  The key decisions around customer focus, integrating products  & services, improved pricing, and competitive dynamics and how we align these with AI tools such as LLMs, Machine Learning, Reasoning, Analytics and automated tools and personalized AI's doing intelligent work.

 Practical Elements 

• Interactive Elements:  Case studies, group discussions, and hands-on activities to enhance engagement. 
• Practical Tools: Introduce tools and frameworks for AI strategy development and project management. 
• Customization: Tailoring examples and discussions to the specific industry or context of the participants. 
• Networking Opportunities: Facilitating networking among participants to encourage knowledge sharing. 

We plan to adapt the content based on the audience's existing knowledge and each organization's unique characteristics. This outline provides a comprehensive structure, but the depth of coverage will be adjusted based on time constraints and the specific needs of the audience.

Instructor: Bruce Matichuk, MSc., MBA, PhD (abd), CTO Health Gauge (https://healthgauge.com )

Bio: Bruce is a Co-Founder and CTO of Health Gauge, holds an MSc in Computing Science from the University of Alberta, an MBA (Welch Scholar) in Health Administration from Jack Welch University, and is nearing the completion of his PhD in AI at the University of Alberta in 2024. His research is focused on improving intelligence in Large Language Models for Enterprise applications. With a rich history as CTO for various AI startups like Celcorp, Poynt, Clinitrust, AiDANT, and MedWatch Technologies, his innovations span AI-integrated systems, blood glucose detection, medical communication platforms, electronics, face recognition technologies, machine learning, and conversational AI. At HealthGauge.com , he leads projects in machine learning-driven blood pressure estimation, telehealth, and conversational agents. Esteemed for his published AI research and ground-breaking patents, Bruce frequently delivers industry talks on AI's rise and application and is currently leading the Certified AI Professional program with Kewal Dhariwal at ICCP.org . Bruce is a member of the DAMA Edmonton Chapter Board of Directors.

Time & Location  

Dec 14, 8:00 a.m. – 4:30 p.m.,   

NAIT Productivity Innovation Center (PIC),   

10210 Princess Elizabeth Ave NW, Edmonton AB 

Breakfast, Coffee Breaks and Lunch included.

Cost:

Members: $825

Non-Members $950