.png "Implications of AI – StrategyOps Institute")
Duration: 12 hours
Skill Level: Intermediate
Course Overview
This course equips professionals with the essential knowledge and methodologies to define, assess, and communicate AI's business value in practical, economic, and financial terms. It is designed for Sales Professionals, Project Managers, IT Managers, and Customer Success Managers, who must articulate AI's impact on enterprise outcomes, strategic agility, and return on investment (ROI). Participants will learn how to align AI solutions—such as AI Agents, AI Assistants, Generative AI, and any AI-based solution—with operational needs and business objectives while effectively communicating AI's business value to ensure AI investments drive measurable outcomes.
The StrategyOps 2.0 methods presented in this course expertly help participants to understand, define, measure, quantify, and communicate the business value of AI solutions that:• Increase business results (i.e., AI solutions for customer success and revenue growth), • Maintain business results (i.e., AI in cybersecurity),• Recover business results (i.e., AI infrastructure for resilience).
Course Content
Session I: Introduction – Defining AI's Business Value
- Session Description:
- Many enterprises struggle to move beyond the hype of AI to define its tangible business value. This session introduces the foundational methods of the StrategyOps 2.0 framework, equipping participants with a structured approach to articulate AI's value to internal and external stakeholders.
- Key Learning Objectives:
- • Understanding AI's role in enterprise value creation.
- • The distinction between AI's TCO and AI's Total Value of Opportunity (TVO).
- • Presenting types of AI Value Creation and Profit Impacts to decision-makers.
- • Aligning AI with internal and external customers' operational and strategic goals.
Session II: AI for Excellence in Value Creation
- Session Description:
- AI investments often fail when they focus solely on technology rather than their business impact. In this session, participants learn StrategyOps 2.0 methods to identify, define, and communicate how AI capabilities improve and transform operating and business models, allowing enterprises to gain efficiency, innovation, customer success, and competitive advantage.
- Key Learning Objectives:
- • How AI-driven Solutions can increase, maintain, and restore business outcomes.
- • Learn to identify and communicate AI solutions' technical causality and operational causation, resulting in measurable economic benefits.
- • Best practices for presenting the AI solution value to C-level decision-makers.
- • Using case studies, participants will learn how to:
- Define a Value Creation Strategy: Participants will learn to map AI solutions to business and operating models, ensuring AI aligns with enterprise goals by optimizing infrastructure, shared services, supply chains, and customer journeys.
- Identify AI Solutions Using a Layered Approach: Participants will explore how AI capabilities enhance operational layers, from foundational infrastructure to hyperadaptive AI-driven business processes, ensuring AI solutions meet evolving customer and enterprise needs.
- Communicate AI's Impact on Operational Assets and Workflows: Participants will assess how AI transforms operational assets, workflows, and human-machine teams to enable business capabilities that drive measurable strategic agility and financial outcomes.
Session III: AI for Strategic Agility
- Session Description:
- AI plays a crucial role in enhancing an organization's ability to adapt, pivot, and scale and allows an enterprise to reach and sustain a sustainable competitive advantage. However, businesses often fail to quantify and communicate AI's role in the enterprise's strategic agility. This session teaches participants how to define AI's contribution to business responsiveness, decision-making speed, and competitive positioning.
- Key Learning Objectives:
- Understanding the three levels of AI-enabled Strategic Agility:
- o Operational Agility: AI's role in process optimization and automation.
- o Portfolio Agility: AI's impact on business model adaptability.
- o Strategic Agility: AI's role in long-term strategic shifts and resilience.
- Using real-world examples, participants will learn to define strategic agility needs and AI solutions for customer-required financial outcomes in the "AI for Enterprise Strategic Agility" session:
- o Analytical AI: Participants will learn to identify customer inefficiencies using Analytica AI to enable data-driven insights that support financial optimization, risk reduction, and process improvements.
- o Augmented AI: Participants will explore how Augmented AI solutions enhance financial outcomes by forecasting trends, optimizing resource allocation, and generating scenario-based recommendations for business growth and risk management.
- o Autonomous AI: Participants will examine how Agentic and Adaptive AI systems automate workflows, dynamically adjust operations, and reduce manual costs, leading to scalable efficiency and financial resilience.
- o Hyperadaptive AI: Participants will learn how Multi-AI Strategic AI systems autonomously optimize decision-making, reallocate enterprise resources, and accelerate market-driven innovation to maximize financial agility and long-term business value.
Session IV: AI Outcomes and ROI
- Session Description:
- One of the biggest challenges in AI adoption is demonstrating ROI. AI projects often fail due to a lack of a clear business case framework that defines AI's benefits and bottom-line impact. This session provides structured methods for measuring, presenting, and justifying AI investments to decision-makers and executives.
- Key Learning Objectives:
- • Participants will learn StrategyOps 2.0 methods to define Measurable Outcome Agreements (MOAs) for economic impact, Experience Outcome Agreements (XOAs) for stakeholder experience, and Strategic Outcome Agreements (SOAs) for long-term strategic progress.
- • How to present the AI Solution ROI to Decision-Makers using a structured approach to quantify AI's total value opportunity, linking financial gains, operational efficiencies, and strategic benefits to executive-level business objectives.
Session V: Participants' Workshop – Applying AI Business Value Methods
- Session Description:
- Theory is valuable, but real-world application is essential. This interactive workshop ensures that participants can effectively use the concepts and methods learned in the course to develop compelling AI business cases.
- Key Learning Objectives:
- • Interactive Role-Play: Participants work through real-world AI business value scenarios.
- • Job-Specific Case Development: Tailored AI business cases for Sales, Customer Success, IT, and Project Management.
- • Presentation of AI Business Value Cases: Participants develop and present AI value propositions to C-level decision-makers.
- • Real-Time Feedback from the Master Instructor: Insights on how to refine AI business value communication.
- • Reflection & Key Takeaways: Actionable next steps for applying AI business value principles in their roles.