Internal How People Are Using Generative & Agentic AI Today 1 SUPERCHARGING PRODUCTS, PROJECTS, SERVICES AND VALUE STREAMS 

Internal Helen Beal Helen leads the ambassador program at PeopleCert for DEVOPS INSTITUTE, ITIL, PRINCE2 and LanguageCert. She is the founder of Flowtopia, the global community for value stream practitioners. She’s the lead author of the State of VSM Report, the State of Availability Report and an adjunct researcher at IDC. She is a co-author of the book about DevOps and governance, Investments Unlimited, published by IT Revolution. Bringing joy to work 2 

Internal 3 About PeopleCert We are in the business of dream making, turning dreams into reality and fuelling the dream economy. PeopleCert is the global leader in the development of best practice frameworks and certifications that improve organizational efficiency and enhance the lives and careers of people. Our vision | To empower organizations and people to achieve what they are capable of. Millions of candidates and individuals 50,000 leading companies (82% of Fortune 500) 800 government departments in 45 countries Our values | Quality | Innovation | Passion | Integrity | Clarity | Velocity Our guiding principles 

Internal talk map OUR FLOW TODAY SCOPE: products, projects, services & value streams PULSE CHECK: where’s our AI at? REALITY: what’s happening now? In conclusion The outlook 4 

Internal 5 Concept Definition Focus Time Horizon Product 🍎 A thing (or system) created to satisfy a customer or market need. It is a long-lived asset with continuous development and funding. Customer Outcome and Value realization. Continuous, long-term (Product Lifecycle) Project 🚧 A temporary endeavor undertaken to create a unique product, service, or result. It has a defined start, end, scope, and budget. Output or Deliverable completion within constraints (Time, Budget, Scope). Temporary, short-term (Project Timeline) Service 🤝 A means of enabling value co-creation by facilitating outcomes that customers want to achieve, without the customer having to manage the specific costs and risks. Co-creation of Value and Utility/Warranty (fitness for purpose and use). Continuous, operational (Support & Delivery) Value Stream 🌊 The end-to-end sequence of activities required to turn a customer need (trigger) into a delivered, measurable value (outcome). Flow Efficiency and Optimization of the entire system. Continuous, overarching (Systemic Flow) 5 

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Internal 7 MyOrg Product A Product A Sales Legacy platform Project 223 Operations platform Service A Mobile platform Service B Cloud platform Project 225 Product B HR You Live in a Value Stream Network 

Internal Custom built Off-the-shelf Internal Customer facing 8 Product A Product A Sales Legacy platform Project 223 API platform Service A Mobile platform Service B Cloud platform Project 225 Product B HR Data Lakehouse Value Streams Often Interconnect 

Internal 9 1. We have to talk about AIs, plural. 2. Their ability to answer questions is probably the least important thing about them. 3. You are not late. Kevin Kelly 

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Internal 12 Gen AI for Products What People Are Doing Why Ideation & Feature Generation: Analyzing market reports, competitor data, and customer feedback (NPS, reviews) for suggestions for new features, design concepts, and product roadmaps. ● Faster time-to-market ● Increased feature innovation ● Stronger alignment with customer needs Prototyping & UX/UI: Generating initial wireframes, mockups, or design code based on simple text prompts, to speed up the visualization and iteration phases. ● Rapid prototyping ● Reduced dependency on immediate design resources Content & Marketing: Drafting product documentation, release notes, user guides, blog posts, and marketing copy. ● Consistent messaging ● Reduced manual documentation effort 

Internal 13 Gen AI for Projects What People Are Doing Why Documentation & Reporting: Generating project plans, risk registers, stakeholder updates, and technical specifications from high-level input. ● Reduced administrative overhead ● Standardized, professional documentation Risk & Scenario Analysis: Identifying potential risks by analyzing patterns in historical projects and simulates mitigation strategies to predict outcomes. ● Proactive risk management ● Better-informed contingency planning. Meeting Automation: Providing real-time transcription, summarizing key decisions, extracting/assigning action items from meeting transcripts, and analyzing meeting effectiveness against target agendas. ● Improved team alignment ● Less time spent on manual note-taking 

Internal 14 Gen AI for Services What People Are Doing Why Tier 1 Customer Support (Chatbots): Powering intelligent virtual agents to provide conversational, human-like answers to user queries, resolving a high percentage of tickets autonomously. ● Lower support costs ● 24/7 self-service availability ● Faster resolution times. Agent Assistance: Creating ticket summaries for support agents and suggesting personalized responses or links to relevant knowledge articles based on ticket content. ● Increased agent productivity and consistency ● Improved customer satisfaction Knowledge Base Management: Generating new knowledge articles or automatically updating existing ones from incident resolution data and technical documents. ● Improved knowledge accuracy and currency ● Reduced MTTR 

Internal 15 Gen AI for Value Streams What People Are Doing Why Constraint Identification: Analyzing end-to-end data (from tools like Jira, GitHub, etc.) to pinpoint hidden bottlenecks in the flow of work (e.g., excessive wait times, too many handoffs). ● Optimized flow efficiency ● Faster realization of customer value Data Interpretation & Insights: Treating AI as a "Virtual Analyst" by having it summarize flow metrics (like cycle time, flow load) and answering natural language queries about performance. ● Democratized insights ● Faster, data-driven decision-making across all organizational levels Process Optimization Suggestions: Listening to suggested actionable steps for continuous improvement (CI) and allowing AI to automatically execute tasks like reassigning work or adjusting resource allocation to balance the flow. ● Continuous, automated improvement ● Elimination of non-value-add activities (waste) 

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Internal 17 Agentic AI for Products The Agent The Job Autonomous Product Manager Feature Prioritization & Roadmapping: Analyzes real-time user metrics, market trends, and business KPIs to dynamically prioritize backlog items and update the feature roadmap. Customer Insight Agent Proactive Data Synthesis: Independently gathers and analyzes data from support tickets, social media, and sales logs to identify emerging pain points and automatically generate a summary brief of the most critical issues. Development Orchestration Autonomous Prototyping/Testing: Can reason about a product requirement, generate the initial code/design assets, and autonomously deploy it to a test environment for A/B testing or user feedback collection. 

Internal 18 Agentic AI for Projects The Agent The Job Virtual Project Manager/Scrum Master Dynamic Plan Management: Continuously monitors task completion and resource load, re-prioritizing dependencies and re-calculating the critical path to proactively avoid predicted delays. Risk & Compliance Agent Proactive Anomaly Detection: Scans financial records and system logs for deviations, flagging potential cost overruns or security risks and initiating a pre-defined mitigation workflow (e.g., locking access or adjusting budget allocation). Stakeholder Communication Automated Status Flow: Automatically pulls data from various tools, generates a customized status report (tailored to the audience), and proactively distributes it to relevant stakeholders on a set schedule. 

Internal 19 Agentic AI for Services The Agent The Job Self-Healing Agent (ITSM) Autonomous Incident Resolution: Detects a system degradation (e.g., slow server response), diagnoses the likely root cause (e.g., resource exhaustion), and autonomously executes the fix (e.g., restarting a service or scaling up a container) without a human agent. Tier 1 Resolution Agent End-to-End Ticket Handling: A customer reports an issue (e.g., "I can't log in"). The agent reasons the problem, resets the password or re-provisions access across connected systems, and sends the resolution confirmation autonomously. Knowledge Management Knowledge Base Maintenance: Monitors support interactions, identifies knowledge gaps, and generates new draft documentation for human review and approval. 

Internal 20 Agentic AI for Value Streams The Agent The Job Flow Optimization Agent Systemic Bottleneck Removal: Analyzes the end-to-end flow state, identifies the constraint (e.g., too much work-in-progress in testing), and autonomously triggers a corrective action (e.g., pausing new work intake for a week or reallocating engineers to the bottleneck stage). Value Realization Agent Outcome Monitoring & Alignment: Tracks the deployment of a new feature against its predicted business outcome (e.g., "increase conversion by 5%) and notifies leadership if the outcome is at risk, suggesting a pivot or further investment. Toolchain Orchestration Seamless Handoffs: Manages the integration and communication between disparate tools (e.g., Jira, GitHub, Jenkins, ServiceNow), ensuring data integrity and triggering the next step in the value stream upon completion of the previous step. 

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Internal 22 Summary Advice from Pragmatic Coders 1. You’re probably being sold the wrong thing first Every vendor is pitching “AI Agents” or “AI-ready data lakes” right now. Start with a use-case that already works (e.g., a process automation enhanced with AI). 2. Knowledge Graphs = cheap insurance If you have any compliance, audit or “explain-this-to-the-board” requirement, bolt a lightweight knowledge graph onto your existing database in a couple of sprints. It’s not sexy, but it de-risks hallucinations and cuts future re-work. 3. AI Engineering is the bill you’ll pay anyway Whether you pick GenAI or Agents, you’ll still need CI/CD for models, drift detection and rollback. Build that pipeline once, so the next model swap is a one-day job instead of a six-week fire-drill. 4. Responsible AI = faster go-live Instead of treating “AI TRiSM” as a separate line item, embed guardrails directly into the product: red-team prompts, audit logs and bias tests ship with v1. Result: regulators sign off faster, your legal team sleeps at night, and you still hit the market before the competition. 5. Edge AI is still a waiting game Unless you’re running robots in a warehouse, park Edge AI for 2027. 

Internal 23 In Summary Domain Generative AI (Immediate Impact) Agentic AI (Future Autonomous Action) Key Benefit Products Assists with ideation, generating features, prototyping, and drafting content (docs, marketing copy). Autonomous Product Manager: Analyzes real-time metrics, market trends, and KPIs to dynamically prioritize the backlog and update the roadmap. Faster time-to-market and increased innovation. Projects Reduces administrative overhead by generating project plans, risk registers, technical specifications, and real-time meeting summaries. Virtual Project Manager: Continuously monitors task completion and resource load, re-calculating the critical path to proactively avoid predicted delays. Proactive risk management and reduced administrative overhead. Services Powers intelligent chatbots for Tier 1 support, creates ticket summaries for agents, and manages the knowledge base by generating/updating articles. Self-Healing Agent (ITSM): Detects system degradation, diagnoses the root cause, and autonomously executes the fix (e.g., restarting a service or scaling a container). Lower support costs and faster resolution times. Value Streams Acts as a "Virtual Analyst" by summarizing flow metrics and identifying/suggesting actionable steps for continuous process optimization. Flow Optimization Agent: Analyzes the end-to-end flow state, identifies the constraint, and autonomously triggers a corrective action (e.g., pausing new work intake). Optimized flow efficiency and faster realization of customer value. 

Internal Dream it, do it. 24 As illustrated by the Hype Cycle projections, while Generative AI and AI Engineering will enter a Trough of Disillusionment due to cost and implementation hurdles, they are projected to mature and reach the Plateau of Productivity by 2029. Similarly, Agentic AI will experience a drop due to reliability and safety concerns, with recovery beginning by 2029. The evolution of AI is inevitable. By focusing on a unified view of value delivery across products, projects, services, and value streams, and by strategically adopting both Generative and Agentic AI, you can empower your people to reach their true potential. FINAL OUTLOOK 

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