Role-Based Programme
RB1235

AI for Product Lifecycle Management

Advanced Portfolio Intelligence, Lifecycle Optimisation & Product Value Management

IMAGE REQUIRED
Duration
32 Hours
Level
Advanced
Delivery
Instructor-Led
Format
Capability Development

Programme Objectives

  • Develop advanced capability to apply AI across the complete product lifecycle, from introduction and growth to maturity, optimisation, renewal, and retirement.
  • Use AI-assisted research and analytics to monitor market demand, customer adoption, product performance, competitive changes, and lifecycle risks.
  • Apply AI to lifecycle planning, portfolio decisions, product enhancements, roadmap updates, cost-value analysis, and end-of-life planning.
  • Use AI-assisted insights to improve product value, customer outcomes, investment decisions, lifecycle efficiency, and portfolio health.
  • Build responsible AI-enabled Product Lifecycle Management workflows with strong governance, evidence quality, data protection, and human oversight.

Tools covered

Generative AI AssistantsAI Search & Deep ResearchProduct Portfolio AnalysisLifecycle AnalyticsCustomer Feedback AnalysisProduct Performance IntelligenceDemand & Adoption AnalysisRoadmap IntelligenceProduct DocumentationEnd-of-Life AnalysisWorkflow AutomationAI AgentsDecision-Support Tools

Who should attend

  • Product Lifecycle Managers
  • Product Managers
  • Senior Product Managers
  • Product Portfolio Managers
  • Product Strategy Professionals
  • Product Operations Professionals
  • Product Owners
  • Service Portfolio Managers
  • Product Analysts
  • Product Planning Professionals
  • Commercial Product Managers
  • Innovation Managers
  • Product Governance Professionals
  • Portfolio Operations Professionals
  • Leaders Responsible for Product Lifecycle & Portfolio Performance

Prerequisites & Participant Readiness

  • Experience in product management, product planning, portfolio management, product operations, or service management
  • Familiarity with product roadmaps, launches, adoption, customer feedback, performance metrics, and portfolio decisions
  • Basic awareness of Generative AI and common business applications
  • Comfort working with market, product, customer, financial, and operational information
  • No programming knowledge required

TOC Modules

Concepts
  • Understanding Generative AI, reasoning models, analytics, automation, and AI agents
  • Exploring AI applications across product introduction, growth, maturity, optimisation, and retirement
  • Distinguishing AI-assisted lifecycle management from automated product decision-making
  • Understanding hallucinations, weak evidence, data quality, and human accountability
Practical activities
  • Mapping AI opportunities across the Product Lifecycle
  • Identifying activities suitable for augmentation, automation, or continued human ownership
  • Creating an AI opportunity map for lifecycle-management teams

Scenarios

Mature Product to Lifecycle Extension Strategy

Market Trends → Product Performance → Customer Usage → Competitive Pressure → Lifecycle Stage → Enhancement Options → Investment Case → Updated Roadmap

Participants use AI to assess a mature product, identify declining relevance or growth constraints, evaluate enhancement and repositioning options, and create a lifecycle-extension strategy.

Declining Product to End-of-Life & Migration Plan

Product Economics → Usage Decline → Support Cost → Customer Dependency → Strategic Fit → Retirement Decision → Migration Plan → Customer Communication

Participants use AI to evaluate a declining product, assess commercial and customer impact, determine whether retirement is appropriate, and create a structured end-of-life and customer migration roadmap.

Related programmes

Continue with programmes from the same capability area.

Take the next step

Ready to make this programme work for your team?

Customise modules, duration and business scenarios for your team.

Instructor-ledVirtualHybrid

Designed around your roles, tools and real workflows.