Download the presentation slides below!
The SOAR Model advocates for a paradigm shift in how businesses interact with AI, moving away from treating it as a simple search engine towards leveraging it as a strategic advisor. The S.O.A.R. Model (Strategy, Operations, Analyst, Research) illustrates practical applications of an "AI Advisor" in driving revenue growth.
Main Themes
Reframing AI as a Strategic Advisor: The central theme is to move beyond the perception of AI as a mere information retrieval tool (like a "Google Search") and instead view it as a partner capable of challenging assumptions, suggesting improvements, and providing strategic insights. The document explicitly states, "Stop Treating AI as a Google Search" and encourages users to "See AI as an Advisor."
The S.O.A.R. Model for Practical AI Application: The document proposes the S.O.A.R. model as a structured approach to integrating an AI Advisor across different functional areas critical for revenue growth:
Strategy: Utilizing AI to evaluate and refine strategic plans, such as Go-To-Market (GTM) strategies.
Operations: Employing AI to optimize operational efficiency, particularly in sales processes like RFP responses.
Analyst: Leveraging AI to identify opportunities for revenue increase within existing constraints, such as limited budgets and headcount.
Research: Using AI to enhance research capabilities by integrating with various data sources and automating tasks.
The entire framework is oriented towards growing revenue. The examples and applications provided within each component of the S.O.A.R. model directly relate to improving sales effectiveness, expanding market share, and increasing revenue streams.
Conclusion
The SOAR effectively argues for a more strategic and integrated approach to utilizing AI within businesses, specifically focusing on driving revenue growth. By presenting the S.O.A.R. model, the document provides a practical framework for leveraging AI as an advisor in strategy, operations, analysis, and research. The emphasis on challenging assumptions, optimizing processes, and leveraging existing assets highlights the transformative potential of AI when viewed as more than just an information source. The advancements in AI agents further suggest a future where AI plays an even more active role in task completion and proactive support.
Share this post