NEW! Using Artificial Intelligence in Strategic Analysis and Decision-Making Processes with Esra Tepeli
What You Will Learn
Upon completion of this training, learners will be able to:
- Understand the basics of artificial intelligence and its applications in strategic analysis and decision making.
- Evaluate the potential benefits and risks associated with using artificial intelligence in strategic analysis and decision making.
- Develop strategies and plans for integrating artificial intelligence into existing decision-making processes.
Description
Decision making in projects is a complex and dynamic process that depends on various project parameters and the project environment. Since each project is unique and has specific factors, a thorough analysis of the project context is necessary to develop an objective and reliable decision-making model. Complex projects often hold strategic importance for stakeholders in terms of their business strategy, brand image, and financial and economic opportunities. While front-end planning is essential, not all events and scenarios can be foreseen, especially for long-term projects involving multiple stakeholders. Therefore, strategic analysis is critical in the early phases of the project to identify and analyze major opportunity and risk factors for making informed strategic decisions. However, in the early phases the amount of information available is limited, and predictive tools may be necessary to forecast the project's future.
Artificial Intelligence (AI) can be a powerful tool in strategic analysis and decision-making processes. It can analyze vast amounts of data, develop predictive models, analyze text data, extract valuable insights, provide decision support, and automate decision making. This is particularly important in projects, where numerous variables and factors need to be considered to make informed decisions.
AI can analyze data and identify patterns, correlations, and trends that may not be apparent to humans, providing insights into market trends, customer behavior, and competitor activity. It can develop predictive models that forecast future outcomes based on past performance, identifying potential risks and opportunities, and developing strategies to address them. AI can provide decision support by analyzing multiple scenarios and providing recommendations based on objective criteria, leading to more informed and data-driven decisions. Additionally, AI can automate decision-making processes based on predefined rules and criteria, streamlining decision making, and reducing the time and resources required to make decisions.
In this training, we will explore how AI can be used in strategic analysis and decision-making processes throughout the project life cycle. We will provide a framework for combining the AI model into strategic analysis and decision-making methods, tailored to project characteristics, complexity, environmental factors, project life cycles, project management goals, stakeholders' objectives, project governance, project teams, and corporate strategies.
AGENDA
-
I. Introduction to Artificial Intelligence (AI)
- Definition and history of AI
- Applications of AI in various industries
- AI tools and techniques for strategic analysis and decision-making
II. Benefits and Risks of AI in Strategic Analysis and Decision-Making
- Potential benefits of using AI for decision-making
- Risks and limitations of AI in decision-making
- Ethical and legal considerations
III. Types of AI Tools and Techniques
- Predictive analytics and modeling
- Neural networks and deep learning
- Visualization tools and techniques
IV. Real-World Examples of AI in Strategic Analysis and Decision-Making
- Case studies from various industries, such as finance, healthcare, and marketing
- Success stories and best practices for implementing AI in decision-making
V. Integrating AI Into Existing Decision-Making Processes
- Strategies for incorporating AI into current processes
- Planning for the implementation of AI
- Change management and training for stakeholders
VI. Evaluating and Communicating Results
- Analyzing and interpreting the results of AI-based analysis and decision-making
- Communicating findings and recommendations to stakeholders
- Evaluating the effectiveness of AI-based decision-making
VII. Future Trends and Directions in AI for Strategic Analysis and Decision-Making
- Emerging AI tools and techniques
- Potential future applications of AI in decision-making
- Conclusion, discussions
PDU Allocation Table
Ways of Working | Power Skills | Business Acumen | Total | |
---|---|---|---|---|
CAPM® / PMI-CP™ / PMP® / PgMP® | 2 | 2 | 3 | 7.00 |
PMI-ACP® / Agile* | 0 | 2 | 3 | 5.00 |
PMI-SP® | 0 | 2 | 3 | 5.00 |
PMI-RMP® | 0 | 2 | 3 | 5.00 |
PfMP® | 0 | 2 | 3 | 5.00 |
PMI-PBA® | 0 | 2 | 3 | 5.00 |