Prepare yourself for the AI Product Development for Business Leaders course

This AI Product Development for Business Leaders training course equips leaders with the strategic and commercial capabilities to turn AI opportunities into viable products, services and business solutions. Successful AI product development requires more than selecting a technology or launching an AI feature. Leaders need to identify valuable problems, understand user needs, evaluate AI feasibility and build a credible business case before committing resources.

The training course follows the AI product lifecycle from opportunity identification and product strategy through design, development oversight, validation, launch and scaling. Participants will examine generative AI, predictive AI and other practical product applications without requiring coding expertise. Particular attention is given to data readiness, build-versus-buy decisions, product metrics, responsible AI, governance and cross-functional leadership. By the end of the course, participants will be able to lead AI product initiatives with clearer priorities, stronger governance and greater focus on measurable business value.

This AI Product Development for Business Leaders training course will highlight:

  • Identifying high-value opportunities for AI-enabled products
  • Translating business problems into clear AI product requirements
  • Evaluating feasibility, data readiness and commercial value
  • Leading AI product development without requiring technical expertise
  • Managing responsible AI, governance and product risks
  • Launching, measuring and scaling successful AI products

The learning journey

Course Summary Outline

Day 1

AI Product Strategy & Opportunity Identification

Day 2

Business Case, Feasibility & Product Requirements

Day 3

Leading AI Product Development

Day 4

Responsible AI, Risk & Product Governance

Day 5

Launching, Measuring & Scaling AI Products

Key Learning Outcomes and Objectives?

By the end of this AI Product Development for Business Leaders training course, participants will be able to:

  • Identify and prioritise viable AI product opportunities.
  • Develop a business case and value proposition for an AI product.
  • Translate business and user requirements into AI product requirements.
  • Lead cross-functional AI product development and validation.
  • Apply responsible AI and governance principles across the product lifecycle.
  • Develop practical strategies for launching, measuring and scaling AI products.

The Excentra Learning Approach

This training course uses a practical, executive-focused approach combining expert-led presentations, business scenarios, AI product examples and structured decision exercises. Participants will evaluate AI opportunities, develop product concepts, assess feasibility and consider product, data and governance requirements. The methodology focuses on the decisions business leaders need to make rather than coding, programming or detailed model engineering.

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.
01

Data Intelligence

Assessing data availability, quality and rights as part of the day-two readiness check.
02

Intelligent Monitoring

Defining success metrics and post-launch performance monitoring for your product.
03

Document Intelligence

Generative applications are discussed as product types but not practised.
04

Workflow & Agent Design

The AI development lifecycle, MVP scoping and prototyping, seen from the sponsor’s seat.
05

Responsible Implementation

Risk register and lifecycle controls built in the day-four lab with human oversight defined.
06

Business Transformation

Opportunity portfolio, business case and scaling roadmap built, challenged and defended.

Is This Course Right for You?

This training course is designed for business leaders responsible for identifying, sponsoring, developing or commercialising AI-enabled products and services. It will be particularly valuable for:

  • Business Owners and Entrepreneurs
  • CEOs and General Managers
  • Business Unit Leaders
  • Strategy and Transformation Leaders
  • Product Directors and Managers
  • Innovation Leaders
  • Digital Transformation Professionals
  • Business Development Leaders
  • Commercial Leaders
  • Executives sponsoring AI initiatives

Frequently Asked Questions

The AI Product Development for Business Leaders Training Course covers the lifecycle of an AI-enabled product, from identifying opportunities and setting product strategy to development oversight, validation, launch and scaling. Participants will learn to assess user needs, AI feasibility, data readiness and commercial value before committing resources. The course also addresses product requirements, metrics, responsible AI, governance and cross-functional leadership.
This course is designed for business leaders responsible for identifying, sponsoring, developing or commercialising AI-enabled products and services. It is particularly relevant to business owners, entrepreneurs, CEOs, general managers, business unit leaders, product leaders and executives sponsoring AI initiatives. Strategy, transformation, innovation, digital transformation, business development and commercial leaders can also use the learning to support their professional responsibilities.
The course helps leaders distinguish potentially valuable AI opportunities by connecting business problems, user needs, technical feasibility and commercial value. Participants will learn to identify and prioritise viable concepts rather than beginning with a technology or isolated AI feature. This approach supports clearer investment decisions and helps leaders focus resources on AI-enabled products, services and business solutions with a credible value proposition.
Yes, participants will learn how to develop a business case and value proposition for an AI product. The course connects opportunity assessment with user needs, feasibility, data readiness and expected commercial value, enabling leaders to consider whether a concept merits investment. This knowledge is relevant when seeking executive sponsorship, prioritising resources or communicating why an AI-enabled product should proceed through development.
Participants will learn to translate business problems and user requirements into clear AI product requirements. This involves defining what the proposed product or service needs to achieve before development resources are committed. The learning helps product sponsors and business leaders communicate priorities more clearly across commercial, product, data and technical functions while maintaining attention on user value and business objectives.
Yes, the course covers data readiness, AI feasibility and build-versus-buy decisions as important parts of product planning. Participants will learn what leaders should consider when assessing whether an AI concept has suitable data and whether its proposed approach is credible. These considerations help decision-makers evaluate internal development and external solutions without requiring detailed model engineering expertise.
Yes, the course examines generative AI, predictive AI and other practical product applications without requiring participants to code or undertake detailed model engineering. Its focus is on the strategic, commercial, product and governance decisions that leaders need to make. Participants will develop a clearer basis for overseeing cross-functional AI product development and validation while working effectively with product, data and technical specialists.
The course addresses responsible AI, governance and product risks across the AI product lifecycle. Participants will learn to apply governance principles while an AI-enabled product moves through strategy, design, development oversight, validation, launch and scaling. This supports executives and product sponsors in maintaining appropriate oversight rather than treating governance as a separate consideration introduced only after development.

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