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AI & Data Best Practices

The Critical AI and Data Skills you need as a Project Manager

Table of Contents

AI Project Management: Essential Skills for Success

What Skills Do You Need for an AI Project Manager?

In the dynamic world of AI project management, a blend of specific skills sets you apart. As AI and data projects continue to evolve, the demand for skilled AI project managers is skyrocketing. Whether you’re starting or enhancing your career, understanding these skills is crucial​​.

Communicating Across Boundaries

Effective AI project managers excel in cross-organizational communication. Bridging the gap between technical and business teams, they ensure projects stay on track, within budget, and all stakeholders remain informed and involved​​.

Iterative Delivery: Agile AI Project Management

AI and Data projects demand rapid, iterative delivery. Unlike traditional projects taking months or years, AI projects thrive on swift, regular model implementation, aligning with the fast-paced nature of the field​​.

Navigating the AI and Data Scope

Managing the scope of AI and data projects is a delicate balance. It’s about understanding the data’s quantity and quality, aligning it with AI capabilities, and ensuring manageable project life cycle iterations​​.

Foundational Data Understanding

In the realm of AI, a foundational understanding of data is not just beneficial; it’s essential. AI and data project managers need to grasp the core concepts of data, AI, and machine learning. This includes knowledge about data sources, preparation methods, and data quality issues​​. A deep dive into data helps in navigating the complex and technical aspects of AI projects.

Critical Thinking for Complex Challenges

AI project management is not for the faint-hearted. It involves complex problem-solving and logic-driven thinking. A successful AI project manager must exhibit strong critical thinking skills to navigate the intricate web of AI and data challenges​​.

Beyond General Project Management: The AI Edge

AI project management transcends traditional approaches. While foundational skills in project management are valuable, they often don’t suffice for the unique demands of AI projects​​. AI initiatives are data-dependent, iterative, and rapidly evolving, requiring a specialized skill set.

The Technical Nature of AI Projects

AI projects are distinctly technical, driven by data and model life cycles that constantly change. This requires AI project managers to be adept in data-specific methods, adjusting to evolving requirements and maintaining flexibility in project approaches​​.

Continuous Learning and Adaptation

Unlike traditional projects, AI projects are never a “set it and forget it” endeavor. They demand ongoing attention and adaptation. Mastery in data and resilience to change are key for AI project managers to thrive in this dynamic environment​​.

Embracing AI and Data Project Management

AI and data project management is a field that constantly challenges and rewards. Embracing its complexity and technical nature, while applying AI-specific methodologies, positions project managers for long-term success in this ever-evolving landscape.

Why Existing Project Management Approaches Aren’t Enough

General project management skills provide a good foundation for managing schedules, resources, and the people and talent needed to meet those goals. General project management approaches such as PMP, Agile, PRINCE2, and other project management approaches and certifications give a project manager a baseline for successful project delivery. 

However, AI and data projects provide their own unique challenges that need to be understood and addressed. This is where those general project management approaches fall short.

General project management approaches are geared towards dealing with non-technology specific project management concerns such as project integration management, project scope, time management, cost management, resource management, communication management, and procurement. 

It’s one thing to apply this knowledge to manage construction, manufacturing, or engineering projects that might take many months to years to complete, but general strategies focused on budgeting, managing timelines, contractors, and physical deliverables don’t usually translate well for AI projects. 

Why? Because AI projects are data-dependent, iterative, quickly evolving, and more technical in nature.

The critical AI and data skills you need as a project manager are focused on data-specific methods, iterative approaches in environments of uncertainty, and dealing with constantly changing data and model lifecycles.  AI project management is focused on dealing with the complexities of dealing with data, managing highly iterative and constantly changing requirements, and allowing teams to be flexible in their approach to the project. 

AI Project Managers need to know how to communicate with both the technical as well as business teams, understand core concepts related to data, AI and ML, as well as understand that AI projects are driven by functionality that isn’t like application development projects. 

Applying AI-Specific Project Methodology

Traditional project methodologies fall short in the face of AI’s unique challenges. AI project managers need to apply specific methodologies, such as the Cognitive Project Management for AI (CPMAI) methodology, for project success. This involves a step-by-step approach tailored to the AI project’s lifecycle​​.

CPMAI: AI Project Management Methodology

The most widely accepted best-practice, vendor-neutral methodology for AI is the Cognitive Project Management for AI (CPMAI) methodology. If you are looking to run and manage AI projects, or currently running AI projects, or you’re looking to get hired into a project or program management role related to AI, getting certified in CPMAI is crucial. 

Based on hundreds of real-world implementations to develop a methodology optimized for the delivery of in-production, high value, successful AI projects, the Cognitive Project Management for AI (CPMAI) Methodology leverages decades of real-world methodology experience for running big data projects combined with the latest best practices expertise learned from running real-world AI projects. 

AI & big data project management success is rooted in successful planning, expectation setting, and establishment of best practices based on Agile, CRISP-DM, and other proven approaches to managing big data & AI projects. When CPMAI certification is combined with the critical PM skills listed above, you’re well on your way to PM success.

Increasingly, AI project owners, managers, and employers are looking for skill sets related to AI project management that will help ensure AI project success. 

Interested in learning more about CPMAI and how an AI project management course can enhance your career? By getting your CPMAI certification you are joining the fastest growing certification for running and managing AI projects, with an annual growth rate of 220%. 

With your CPMAI certification, you will prosper in this quickly growing community of data and Artificial Intelligence project management professionals and thrive in your AI project management role and career.

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