Role-Based Programme
RB1234

AI for Product Lifecycle Management

Portfolio Intelligence, Lifecycle Optimisation & Product Value Growth

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Duration
16 Hours
Level
Intermediate
Delivery
Instructor-Led
Format
Capability Training

Programme Objectives

  • Develop practical AI capabilities for managing products across introduction, growth, maturity, decline, renewal, and retirement stages.
  • Apply AI to analyse market trends, customer needs, product performance, adoption, profitability, competition, and lifecycle risks.
  • Use AI to strengthen lifecycle planning, portfolio reviews, product enhancement, roadmap decisions, renewal strategies, and end-of-life planning.
  • Improve cross-functional lifecycle decisions through structured evidence synthesis, scenario analysis, performance intelligence, and stakeholder communication.
  • Apply responsible AI practices related to customer data, confidentiality, source validation, intellectual property, bias, and human decision-making.

Tools covered

Generative AI AssistantsAI Search & ResearchProduct Portfolio AnalysisCustomer Insight AnalysisProduct Performance AnalyticsLifecycle Stage AnalysisDemand & Trend AnalysisRoadmap PlanningRisk AnalysisDocumentation SupportDecision SupportExecutive Summarisation

Who should attend

  • Product Lifecycle Managers
  • Product Managers
  • Senior Product Managers
  • Product Portfolio Managers
  • Product Owners
  • Product Strategy Managers
  • Product Operations Professionals
  • Service Managers
  • Product Planning Professionals
  • Product Analysts
  • Category Managers
  • Innovation Managers
  • Commercial Product Managers
  • Business Unit Managers
  • Product & Service Management Leaders

Prerequisites & Participant Readiness

  • Experience in product management, product strategy, portfolio management, product operations, or service management
  • Familiarity with product roadmaps, product performance, customer needs, and lifecycle concepts
  • Basic familiarity with Generative AI tools is recommended
  • Ability to interpret product, market, customer, and commercial information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, multimodal AI, and AI assistants
  • Exploring AI applications across product introduction, growth, maturity, renewal, and retirement
  • Understanding how AI differs from PLM systems, analytics platforms, and traditional product tools
  • Recognising hallucinations, outdated information, unsupported assumptions, and AI limitations
Practical activities
  • Mapping the product lifecycle to practical AI applications
  • Identifying high-value versus low-value lifecycle use cases
  • Comparing traditional and AI-assisted lifecycle management workflows

Scenarios

Mature Product to Lifecycle Extension Strategy

Product Performance → Customer Trends → Competitive Pressure → Lifecycle Assessment → Value Gaps → Enhancement Options → Prioritisation → Product Renewal Plan

Participants use AI to analyse a simulated mature product, identify emerging market and customer pressures, and develop an evidence-based strategy to extend product value and relevance.

Declining Product to Retirement or Repositioning Decision

Performance Decline → Market Analysis → Customer Dependency → Cost & Value Review → Strategic Options → Scenario Analysis → Migration Impact → Executive Recommendation

Participants use AI to evaluate a simulated declining product, compare repositioning, maintenance, migration, and retirement options, and prepare a structured lifecycle decision recommendation.

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