The Critical AI and Data Skills you need as a Project Manager
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Organizations of all sizes in every industry around the world are looking to Artificial Intelligence and advanced big data projects to provide a competitive edge, provide efficiencies, and improve ROI in today’s competitive landscape. As a result, this creates tremendous opportunity for people looking to manage these types of projects. There is significant and growing demand for skilled AI project managers and implementers across the whole range of AI capabilities. If you’re looking to get into managing AI projects, machine learning implementations, or advanced data projects of any type, or enhance your current skills, what are the most critical AI and data skills you need as a project manager?
AI project management needs more than general project management skills
While 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.
For AI projects, and therefore AI and data PMs, 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.
AI project managers also need to know that projects are never a “set it and forget it” type thing, lacking a clear project end. In this way the critical AI and data skills you need as a project manager are more technical in nature, more resilient in the face of change, and require specific skills around mastery of data. Adopting an iterative, data-centric project management methodology is key to AI and data project manager long term career success.
What skills should an AI and Data project manager have?
The main skills that an AI or Data project manager needs to have is a mix of both hard and soft skills. AI project managers are required to have an understanding of how to run data projects with data project management competencies, understand how data projects are different from application development projects, understand big data best practices, and also understand how to effectively communicate between the technical and business teams as well as key stakeholders. Critical skills that AI and data project managers should have include:
- Cross-organizational communication skills: The PM needs to communicate with both the technical and business teams, and oftentimes these two communities speak very different languages. An effective AI and Data PM will know how to seamlessly go between these two communities to keep projects running on time, on budget, and keep all key stakeholders up to date and involved in the process.
- Iterative delivery: AI and Data projects should not take months to years to see models get into production. A good PM will follow best practices methodologies to ensure projects are properly scoped, and models are delivered on a highly iterative and regular cycle. To be successful, machine learning and AI solutions need to be operationalized in just weeks or even days in a given iteration.
- AI and data Scope management: Adding to the above skills, AI and data project managers need to understand how to properly scope AI and data projects to make sure the team isn’t tackling more than they can manage in one project life cycle iteration given the quantity and quality of available data matched to the specific AI needs and capabilities.
- Foundational data understanding: AI and data PMs must understand core concepts related to data, AI and ML. At a high level they need to understand data sources, methods of data preparation and enhancement, ways to corral data from multiple sources, and how to work to get access to the data as required. AI and data PMs also need a basic understanding around data quality and data quantity issues.
- Critical thinking: AI and data projects can get complex quickly. A good PM will be able to successfully manage and solve complex problems that require deep logic-driven thinking. Critical thinking skills are key for PMs dealing with AI and data projects.
- Applying AI-specific project methodology: Project managers understand the importance of methodology and how beneficial a step by step approach can be. Modern AI and data project managers use AI and data-specific project methodologies like the Cognitive Project Management for AI (CPMAI) methodology to ensure best practices for project success. AI and data project managers need to understand when and how to apply AI tools for project management success, as well as know the particular order they need to run projects in to ensure success.
Applying CPMAI: AI Project Management Methodology
Those that are looking to advance their careers as AI and data project managers need to know modern, advanced, best practices for AI and data project management. 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. Getting a certification on the best practice methodology for AI projects will add significant value to you and your work.
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.