An Interactive 5-Day Training Course

Cognitive Project Management in AI (CPMAI)

Strengthen the ability to manage AI projects through a cognitive, structured approach that supports sound judgement and practical delivery. This training course develops clearer decision-making, adaptive planning and effective oversight across the project lifecycle. It helps align AI initiatives with defined objectives while navigating complexity and change.

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Prepare yourself for the Cognitive Project Management in AI (CPMAI) course

The Cognitive Project Management in AI (CPMAI) training course develops a structured understanding of how artificial intelligence initiatives progress from an initial business need to sustained operational use. It connects business understanding with disciplined exploration of data, showing why project direction, information quality and preparation must remain aligned. Participants examine the relationships between these phases rather than treating model development as an isolated technical task.

Building on this foundation, the course follows the progression from prepared data into model development, evaluation and operationalisation, with continuous improvement treated as part of the management lifecycle. It clarifies how evaluation informs readiness for use, how operational experience can prompt renewed analysis or preparation, and how each phase contributes to coherent oversight. This end-to-end perspective explains the dependencies, feedback loops and management priorities that shape AI project delivery.

The highlights of this Cognitive Project Management in AI (CPMAI) training course includes:

Connecting business needs with clear AI project direction
Understanding and preparing data across the project lifecycle
Progressing systematically from prepared data to model development
Evaluating models to determine their operational readiness
Managing operationalisation through continuous improvement feedback loops

The learning journey

Course Summary Outline

Day 1

Laying the Foundations for AI Project Management & Responsible AI

Day 2

Identifying AI Business Needs and AI-Project Planning

Day 3

AI Data Management and Data Readiness

Day 4

AI Model Development, Training, and Evaluation

Day 5

AI Deployment, Governance, and Operationalization

Who should attend

Is This Course Right for You?

This course is intended for professionals responsible for planning, delivering, governing or supporting artificial intelligence initiatives across their organisation. It is particularly relevant to those who must align AI projects with business objectives, manage data and technology dependencies, coordinate multidisciplinary teams, address risk and compliance requirements, and establish structured approaches to AI programme execution and oversight.

This Cognitive Project Management in AI (CPMAI) training course is designed for:

AI Project Managers
AI Programme Managers
AI Product Managers
PMO Managers
Digital Transformation Managers
Data Governance Managers
AI Governance Managers
Technology Risk Managers
Business Analysts
Solution Architects

Overview

About this course

Want the full outline?

Key Learning Outcomes and Objectives?

The Cognitive Project Management in AI (CPMAI) training course equips professionals to structure and govern AI initiatives across the CPMAI project lifecycle. It focuses on selecting viable business use cases, defining scope, assessing risk and return on investment, and applying better governance through six project phases. Participants will also establish measurable performance indicators and monitoring controls to support accountable decisions, sustained business value and effective oversight of AI projects.

Apply the six CPMAI phases to structure an AI project lifecycle.
Evaluate AI business opportunities against feasibility, value and strategic alignment.
Define project scope, objectives, stakeholders and resource requirements.
Assess AI project risks, governance needs and expected return on investment.
Develop relevant performance metrics and KPIs for AI initiatives.
Establish monitoring mechanisms to track outcomes, risks and business value.

The Excentra Learning Approach

This training course will utilise a variety of proven adult learning techniques to ensure maximum understanding and retention of the information presented. The facilitator will introduce each of the core topics using a lecture format. Presentations are supported by reinforcement exercises to emphasize the application of theory in real-world project settings. Peer learning is promoted as delegates are encouraged to discuss how techniques may apply within their own environments.

Excentra capability map

Six capabilities, and how far this course takes each one

Every Excentra course is mapped against the same six AI capabilities, so you can see at a glance what a course builds and compare it with any other in the catalogue.

Data Intelligence

Specifying data requirements, validating sources, exploratory analysis and bias checks for a readiness assessment

Intelligent Monitoring

Model drift, performance degradation, KPI dashboards and incident triggers in the monitoring plan

Document Intelligence

Not taught; document-based use cases are scoped like any other AI opportunity

Workflow & Agent Design

Solution architecture, integration planning and organisational embedding of an AI solution

Responsible Implementation

Governance, privacy, explainability and oversight gates built into every phase of the plan

Business Transformation

Opportunity selection, business case, readiness, change management and transition to operations

Ready to take the next step?

Reserve your place, ask us a question, or arrange private training for your team.

Frequently Asked Questions

The Cognitive Project Management in AI (CPMAI) training course explains how to manage AI initiatives from opportunity identification through operational deployment and handover. Participants will learn the CPMAI™ framework, its six core phases and the distinctive governance requirements of AI projects. The course also addresses scope, risk, return on investment, performance metrics, KPIs and continuous monitoring within enterprise environments.

The course focuses on management requirements that distinguish AI initiatives from traditional IT and software projects. These include data governance, model management, ethical oversight, iterative development, operationalisation and continuous monitoring. Participants learn a structured, vendor-neutral methodology for coordinating these areas across the AI project lifecycle rather than treating an AI implementation as a conventional software initiative.

The Cognitive Project Management in AI (CPMAI) training course covers Business Understanding, Data Understanding, Data Preparation, Model Development, Model Evaluation and Model Operationalisation with Continuous Improvement. Participants learn how these phases structure an AI initiative from its initial business purpose to its ongoing operation. This lifecycle perspective helps managers coordinate business, data, technical, governance and operational responsibilities.

The course helps participants assess AI opportunities and use cases within a structured project lifecycle. Business Understanding provides the foundation for connecting a proposed initiative with organisational needs, while attention to scope, risks, governance and return on investment supports informed evaluation. This is relevant to professionals who must prioritise AI initiatives, define their business rationale or advise decision-makers.

This course is designed for professionals responsible for selecting, governing, managing or supporting enterprise AI initiatives. It is particularly relevant to project and PMO professionals, AI product managers, digital transformation leaders, technology managers, business analysts, solution architects and data governance specialists. Risk and compliance teams, strategy leaders, engineering managers, technical managers and consultants managing AI initiatives may also benefit.

Participants will learn to develop performance metrics, key performance indicators and monitoring mechanisms for AI initiatives. The course also addresses return on investment alongside project scope, risk and governance, helping participants consider both business value and delivery control. These capabilities are relevant when defining success criteria, evaluating progress and maintaining management oversight throughout the AI lifecycle.

The course treats data governance, model management and ethical oversight as core management concerns in AI initiatives. Participants learn how better governance relates to the six CPMAI™ phases, including data understanding, preparation, model development and evaluation. This knowledge supports professionals who must coordinate accountability, risk and control across business, data, technical and governance teams.

The Cognitive Project Management in AI (CPMAI) training course covers the transition from model evaluation to operational deployment, handover and continuing oversight. Participants learn why AI models require monitoring mechanisms and ongoing improvement after implementation rather than a one-time delivery approach. This is particularly relevant to managers responsible for operational readiness, performance tracking and coordination between project and operational teams.