GenAI Opportunities (across the Value Chain) (PowerPoint PPTX Slide Deck)

BENEFITS OF THIS POWERPOINT DOCUMENT

1. Provides over 100+ GenAI opportunities across the Value Chain, which can drive significant revenue enhancements, productivity gains, and cost savings.
2. Allows you to prioritize your GenAI initiatives by corporate function or formulate a cross-functional, holistic AI Strategy.
3. Lay the foundation to your Digital Transformation Program or AI Strategy with targeted GenAI initiatives.

ARTIFICIAL INTELLIGENCE PPT DESCRIPTION

GenAI Opportunities PPT: Explore Generative AI use cases across Michael Porter’s Value Chain. Download this PowerPoint for actionable AI insights by function. GenAI Opportunities (across the Value Chain) is a 95-slide PPT PowerPoint presentation slide deck (PPTX) available for immediate download upon purchase.

Explore Slides inside the Deck:

GenAI Deployment Opportunities Mapped to Porter Value Chain Functions Identification of 19 AI Deployment Opportunities in Firm Infrastructure AI Deployment Opportunities in Human Resource Management Processes

Generative Artificial Intelligence (GenAI) refers to foundation models that create new content, code, analyses, and decisions based on large-scale training data. Unlike traditional automation and analytics, GenAI operates as a reasoning and production layer embedded directly into daily workflows, knowledge processes, and decision systems.

GenAI has moved from experimentation to everyday operations across industries—customer, supply chain, finance, and technology. Organizations are no longer testing isolated tools. They are redesigning how work gets done, how insights are generated, and how value is delivered at scale.

Organizations that adopt GenAI systematically are widening performance gaps in speed, cost, and experience. In McKinsey's 2025 State of AI, 71% of respondents say their organizations regularly use GenAI in at least one function, up sharply from early 2024. This rapid diffusion shifts the focus from adoption to disciplined execution and measurable returns.

This pervasiveness makes structured, reusable GenAI frameworks essential for value capture at scale. Without clear prioritization, governance, and integration into core processes, most deployments remain productivity tools rather than enterprise performance drivers.

Organizations that embed GenAI into core workflows outperform peers. McKinsey finds that top economic performers from AI generate more than 3x the value of average adopters. The opportunity is no longer experimentation. It is systematic execution at scale.

This PPT presentation provides a catalog of 100+ GenAI opportunities. These GenAI opportunities are categorized by the 9 functional activities of the Michael Porter Value Chain:

1. Inbound Logistics
2. Operations
3. Outbound Logistics
4. Marketing & Sales
5. Service
6. Firm Infrastructure
7. Human Resource Management
8. Technology
9. Procurement

Mapping opportunities to the classic Value Chain ensures every function sees relevant, actionable use cases and enables cross-functional prioritization tied directly to business outcomes.

This PowerPoint is organized around these 9 functions. For each function, we delineate a series of GenAI opportunities, including clear descriptions, examples, enabling technologies, business owners, potential financial and operational impact, and realistic deployment horizons.

ARTIFICIAL INTELLIGENCE PPT SLIDES

GenAI Deployment Opportunities Mapped to Porter Value Chain Functions

This PPT slide outlines over 100 GenAI deployment opportunities aligned with the nine functions of the Porter Value Chain. GenAI applications are tailored for support functions like firm infrastructure, human resource management, technology, and procurement, including tasks such as drafting narratives and developing RFx packs. Primary functions—like inbound logistics, operations, outbound logistics, marketing, sales, and service—are mapped with examples of GenAI streamlining processes, enhancing communication, and generating content. The visual layout uses color coding to differentiate support (gray) and primary functions (blue), indicating where GenAI adds value. Each function specifies GenAI capabilities, such as writing job descriptions and powering self-service portals, emphasizing automation, efficiency, and decision-making. The slide suggests quantifying impact, specific AI technologies, and implementation timelines, providing a framework for organizations to prioritize initiatives and accelerate AI adoption across operations.

Identification of 19 AI Deployment Opportunities in Firm Infrastructure

This PPT slide outlines 19 opportunities for AI deployment in firm infrastructure activities, focusing on finance, legal, risk, real estate, tax, and ESG. It categorizes these into 2 initiatives: a continuous close narrative and variance explainer, and a board pack and CEO brief co-pilot. The first initiative automates the close process, reducing manual effort and speeding up cycles by 25-40% using AI technologies like generative narrative drafting and document AI, with a 4 to 6-week implementation timeline. The second initiative enhances board and executive reporting, generating monthly memos with reconciled metrics, also within 4 to 6 weeks, using AI to minimize restatements and prep times. This framework maps AI tools to business needs, providing a blueprint for similar initiatives and demonstrating actionable, measurable efficiency gains.

AI Deployment Opportunities in Human Resource Management Processes

This PPT slide outlines 15 AI deployment opportunities in Human Resource Management, categorized into initiatives with descriptions, target objectives, users, and examples. Key examples include the Talent Sourcing Outreach Co-Pilot, which personalizes recruiter outreach using AI-driven messaging, achieving faster candidate response times (3 to 5 weeks) and higher reply rates through technologies like GenAI and bias filters. The JD Rewriter & Competency Mapper aims to enhance applicant fairness and resume quality, utilizing HRBPs, TA, and hiring managers. These initiatives fall under the GenAI Opportunities across the Value Chain framework, highlighting actionable, measurable AI applications that improve sourcing, hiring, and retention outcomes.

AI Opportunities in Inbound Logistics: Communication and Discrepancy Management

This PPT slide identifies 16 opportunities for AI deployment in inbound logistics, focusing on predictive ETAs, dock optimization, and vision-enabled receiving. Two use cases are highlighted: Supplier Communications Co-Pilot and ASN Discrepancy Explainer. The Supplier Communications Co-Pilot automates inbound supplier email reviews, generating replies and RFIs based on playbooks, aiming for a 30-50% improvement in email turnaround and fewer miscommunications. Key technologies include NLP and retrieval-augmented generation, with a deployment timeline of 4 to 6 weeks. The ASN Discrepancy Explainer automates detection of ASN data mismatches, providing root cause analysis and resolution steps, targeting a 25-40% reduction in discrepancies. Its development timeline is 6 to 8 weeks, emphasizing rapid deployment to enhance accuracy in inbound logistics.

Operational AI Deployment Opportunities and Expected Impact

This PPT slide outlines 20 opportunities for AI deployment in operations, including yield optimization, scheduling, quality control, energy management, and safety. Each use case has defined business objectives and typical users. For example, the "Frontline SOP & Work Instruction Assistant" reduces errors and ramp time by providing step-by-step guidance, primarily for frontline associates and supervisors, resulting in 15-30% fewer defects and 20-40% faster training. The implementation timeframe is 4 to 6 weeks. Technologies enabling these use cases include GenAI, NLP, and human-in-the-loop systems. Another opportunity, "Troubleshooting Co-Pilot for Lines & Stations," interprets error codes to reduce mean time to repair, targeting operators and maintenance techs, also with a 4 to 6-week deployment cycle.

AI Deployment Opportunities in Outbound Logistics Activities

This PPT slide outlines 16 opportunities for deploying AI in outbound logistics, focusing on routing, reliability, packing, and last-mile capacity. Use cases include customer delivery communications and promise-date explanations, linked to business objectives like reducing failed attempts and improving transparency. Implementing these initiatives can lead to a 20-40% reduction in "where is my order" contacts and a 3-6% uplift in checkout conversion. AI technologies such as GenAI for message drafting and RAG with TMS/OMS data enhance customer communication and promise-date improvements, streamlining processes and improving post-purchase experiences. The structured layout supports a broader framework for AI-driven logistics initiatives, emphasizing quick deployment and targeted use cases for immediate impact.

Source: Best Practices in Artificial Intelligence, Value Chain Analysis, GenAI PowerPoint Slides: GenAI Opportunities (across the Value Chain) PowerPoint (PPTX) Presentation Slide Deck, LearnPPT Consulting