This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
Explore the Agentic AI Assessment Framework, crafted by ex-McKinsey and Big 4 consultants. Evaluate AI agents' performance across 6 critical capabilities. Agentic AI Assessment Framework is a 31-slide PPT PowerPoint presentation slide deck (PPTX) available for immediate download upon purchase.
Agentic workflows are rule-based, linear chains of prompts where each LLM step uses the previous output as input. They are predictable, structured, favor process consistency, and good for tasks needing strong domain knowledge, but they adapt poorly to unexpected inputs.
Autonomous agents, on the other hand, act like independent workers that receive a goal, plan and reason on their own, take actions, observe outcomes, and adjust using real-time feedback until task completion.
This deck provides a detailed overview of the Agentic AI assessment framework, a model to measure AI agents' performance across critical capabilities like how well an agent reasons, executes tasks, recalls knowledge, maintains reliability, integrates with systems, and understands human context.
These critical capabilities constitute the 6 phases of the AI Agent Assessment Framework:
1. Reasoning and Planning
2. Task Autonomy and Execution
3. Memory and Knowledge
4. Reliability and Safety
5. Integration and Interoperability
6. Social Understanding
The Agentic AI Assessment Framework gives organizations a structured lens to determine whether autonomous agents can operate safely and independently.
This PowerPoint presentation on the Agentic AI Assessment Framework also includes some slide templates for you to use in your own business presentations.
This PPT slide introduces the "Agentic AI – Agent Assessment Framework" for evaluating AI agents' maturity and performance across core dimensions: reasoning, execution, and interoperability. The framework consists of 6 sequential phases: "Reasoning and Planning," "Task Autonomy and Execution," "Memory and Knowledge," "Reliability and Safety," "Integration and Interoperability," and "Social Understanding," each representing a critical capability for AI agents. This structured assessment helps organizations identify capability gaps, prioritize investments, and determine AI readiness for deployment. A phased approach is essential for managing risk and ensuring AI systems meet operational expectations.
This PPT slide presents a framework for assessing AI agents' integration and interoperability capabilities. It identifies current maturity levels, limitations such as fragmented data formats and broad system permissions, which hinder efficient interaction and pose security risks. These limitations restrict AI agents from functioning seamlessly in complex digital environments. To improve connectivity, establishing common communication standards and interoperability frameworks, along with developing middleware solutions, is essential. Enhanced integration allows AI agents to transition from simple data retrieval to active contributions in enterprise workflows, supporting dynamic, scalable, and secure AI-enabled operations aligned with digital transformation goals.
This PPT slide compares 2 operational models: agentic workflows and autonomous agents. Agentic workflows are rule-based, predictable, and structured, involving multiple steps with specific triggers such as LLM call sequences and gate checks. They prioritize repeatability and clarity, but lack flexibility in changing conditions. In contrast, autonomous agents operate independently, receiving goals from humans and executing actions without constant oversight. They adapt to real-time feedback from their environment, making them more fluid and capable of handling complex tasks. The comparison highlights that agentic workflows are suitable for tasks with clear, repetitive steps, while autonomous agents excel in dynamic environments requiring flexibility and ongoing decision-making. The choice between these models depends on task complexity and variability.
Source: Best Practices in Artificial Intelligence, Agentic AI PowerPoint Slides: Agentic AI Assessment Framework PowerPoint (PPTX) Presentation Slide Deck, LearnPPT Consulting
This framework is developed by a team of former McKinsey and Big 4 consultants. The presentation follows the headline-body-bumper slide format used by global consulting firms.
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