Merge pull request #50825 from Orin-Thomas/orthomas-05Jun25-B

Terminology change at request of stakeholders

Author: v-ccolin

learn-pr/advocates/intro-ai-center-excellence/1-introduction-generative-ai-center-excellence.yml

@@ -1,9 +1,9 @@
 ### YamlMime:ModuleUnit
 uid: learn.introduction-generative-ai-center-excellence.introduction-generative-ai-center-excellence
-title: Introduction to the Generative AI Center of Excellence
+title: Introduction to the AI Center of Excellence
 metadata:
-  title: Introduction to the Generative AI Center of Excellence
-  description: Introduction to the Generative AI Center of Excellence
+  title: Introduction to the AI Center of Excellence
+  description: Introduction to the AI Center of Excellence
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas

learn-pr/advocates/intro-ai-center-excellence/2-how-center-excellence-assists-planning-adoption-generative-ai.yml

@@ -1,9 +1,9 @@
 ### YamlMime:ModuleUnit
 uid: learn.introduction-generative-ai-center-excellence.how-center-excellence-assists-planning-adoption-generative-ai
-title: How the Generative AI CoE assists in planning adoption of generative AI
+title: How the AI CoE assists in planning adoption of AI
 metadata:
-  title: How the Generative AI CoE assists in planning adoption of generative AI
-  description: Learn how the Generative AI CoE assists in planning adoption of generative AI.
+  title: How the AI CoE assists in planning adoption of AI
+  description: Learn how the AI CoE assists in planning adoption of AI.
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas

learn-pr/advocates/intro-ai-center-excellence/3-oversight-generative-ai-deployment-operations-governance.yml

@@ -1,9 +1,9 @@
 ### YamlMime:ModuleUnit
 uid: learn.introduction-generative-ai-center-excellence.oversight-generative-ai-deployment-operations-governance
-title: Oversight of generative AI deployment, operations, and governance.
+title: Oversight of AI deployment, operations, and governance.
 metadata:
-  title: Oversight of generative AI deployment, operations, and governance.
-  description: Understanding the generative AI CoE's role in oversight of generative AI deployment, operations, and governance.
+  title: Oversight of AI deployment, operations, and governance.
+  description: Understanding the AI CoE's role in oversight of AI deployment, operations, and governance.
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas

learn-pr/advocates/intro-ai-center-excellence/4-determining-organizational-roles-responsibilities.yml

@@ -3,7 +3,7 @@ uid: learn.introduction-generative-ai-center-excellence.determining-organization
 title: Determining organizational roles and responsibilities
 metadata:
   title: Determining organizational roles and responsibilities
-  description: Understand the roles and responsibilities of a Generative AI Center of Excellence.
+  description: Understand the roles and responsibilities of an AI Center of Excellence.
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas

learn-pr/advocates/intro-ai-center-excellence/5-skilling-your-organization.yml

@@ -3,7 +3,7 @@ uid: learn.introduction-generative-ai-center-excellence.skilling-your-organizati
 title: Skilling your organization
 metadata:
   title: Skilling your organization
-  description: Learn how the Generative AI CoE helps skilling your organization.
+  description: Learn how the AI CoE helps skilling your organization.
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas

learn-pr/advocates/intro-ai-center-excellence/6-knowledge-check.yml

@@ -3,7 +3,7 @@ uid: learn.introduction-generative-ai-center-excellence.knowledge-check
 title: Knowledge Check
 metadata:
   title: Knowledge Check
-  description: Validate your understanding of the Generative AI Center of Excellence.
+  description: Validate your understanding of the AI Center of Excellence.
   ms.date: 04/05/2025
   author: Orin-Thomas
   ms.author: orthomas
@@ -12,18 +12,18 @@ durationInMinutes: 3
 content: Choose the best response for each question.
 quiz:
   questions:
-    - content: "What is a primary responsibility of a Generative AI Center of Excellence?"
+    - content: "What is a primary responsibility of an AI Center of Excellence?"
       choices:
         - content: "Developing custom LLM models for all organizational needs."
           isCorrect: false
-          explanation: "While the CoE may provide guidance on AI development, developing custom LLMs isn't a primary responsibility. A generative AI CoE can focus on execution responsibilities like developing models or serve as a guiding body."
-        - content: "Aligning generative AI initiatives with organizational and business priorities."
+          explanation: "While the CoE may provide guidance on AI development, developing custom LLMs isn't a primary responsibility. an AI CoE can focus on execution responsibilities like developing models or serve as a guiding body."
+        - content: "Aligning AI initiatives with organizational and business priorities."
           isCorrect: true
-          explanation: "One of the key responsibilities of an AI CoE, is aligning generative AI initiatives with organizational and business priorities."
+          explanation: "One of the key responsibilities of an AI CoE, is aligning AI initiatives with organizational and business priorities."
         - content: "Replacing existing security teams with AI specialists."
           isCorrect: false
           explanation: "The CoE should work 'in close and constant collaboration' with security teams rather than replacing them."
-    - content: "Which of the following best describes how a generative AI CoE approaches cost management?"
+    - content: "Which of the following best describes how an AI CoE approaches cost management?"
       choices:
         - content: "By focusing exclusively on using open-source models to minimize expenses."
           isCorrect: false
@@ -34,14 +34,14 @@ quiz:
         - content: "By centralizing all AI development to avoid departmental duplication."
           isCorrect: false
           explanation: "Execution is often decentralized, especially in larger organizations."
-    - content: "Which role designs and optimizes inputs for generative AI models to guide their behavior?"
+    - content: "Which role designs and optimizes inputs for AI models to guide their behavior?"
       choices:
         - content: "AI Agent Engineer"
           isCorrect: false
           explanation: "AI Agent Engineers develop 'autonomous AI systems that can perceive, reason, and act to achieve specific goals' rather than focusing on prompt design."
-        - content: "Generative AI Operations"
+        - content: "AI Operations"
           isCorrect: false
           explanation: "Operations are responsible for 'deploying, managing, monitoring, backup, and recovery of AI workloads' rather than prompt design."
         - content: "Prompt Engineer"
           isCorrect: true
-          explanation: "Prompt engineers 'design and optimizes inputs for generative AI models to guide their behavior and produce accurate, desired outputs.'"
+          explanation: "Prompt engineers 'design and optimizes inputs for AI models to guide their behavior and produce accurate, desired outputs.'"

learn-pr/advocates/intro-ai-center-excellence/includes/1-introduction-generative-ai-center-excellence.md

@@ -1,32 +1,32 @@
-A generative AI CoE is a collection of people and resources that help an organization adopt generative AI. It helps define an organization's strategy, determining and establishing an organization's best practices for generative AI, and acts as an organization's generative AI adoption knowledge and skilling hub.
+An AI CoE is a collection of people and resources that help an organization adopt AI. It helps define an organization's strategy, determining and establishing an organization's best practices for AI, and acts as an organization's AI adoption knowledge and skilling hub.
 
-## What are the functions of a generative AI CoE?
+## What are the functions of an AI CoE?
 
-A generative AI CoE typically focuses on setting direction, defining strategies, providing support, establishing metrics, and monitoring the impact of generative AI initiatives. A generative AI CoE provides an organization with a central location and set of people that have the knowledge, skills, and capabilities to effectively leverage AI. When properly implemented, a generative AI CoE holds the authority and influence within an organization needed to drive adoption of generative AI solutions. 
+An AI CoE typically focuses on setting direction, defining strategies, providing support, establishing metrics, and monitoring the impact of AI initiatives. An AI CoE provides an organization with a central location and set of people that have the knowledge, skills, and capabilities to effectively leverage AI. When properly implemented, an AI CoE holds the authority and influence within an organization needed to drive adoption of AI solutions. 
 
-A generative AI CoE assists an organization with:
+An AI CoE assists an organization with:
 
-- Determining business use cases for generative AI applications.
-- Organizational generative AI readiness and driving adoption.
-- Developing generative AI skilling resources.
-- Identifying roles required for generative AI adoption and success.
-- Ensuring that generative AI workloads are governed responsibly and are compliant.
-- Ensuring that generative AI workloads meet operations and security best practices.
+- Determining business use cases for AI applications.
+- Organizational AI readiness and driving adoption.
+- Developing AI skilling resources.
+- Identifying roles required for AI adoption and success.
+- Ensuring that AI workloads are governed responsibly and are compliant.
+- Ensuring that AI workloads meet operations and security best practices.
 
-## Tailoring a generative AI CoE to your organization's needs
+## Tailoring an AI CoE to your organization's needs
 
-When designing and implementing a generative AI CoE, consider the following questions:
+When designing and implementing an AI CoE, consider the following questions:
 
-- Should the generative AI CoE concentrate on technical and operational aspects, on strategy and business alignment, or adopt an integrated approach?
+- Should the AI CoE concentrate on technical and operational aspects, on strategy and business alignment, or adopt an integrated approach?
 - Should the CoE focus on execution responsibilities like developing LLM models or serve as a guiding body, setting principles and frameworks?
-- Should the organization create an independent team associated with the CoE or can the necessary generative AI expertise be embedded within existing teams?
+- Should the organization create an independent team associated with the CoE or can the necessary AI expertise be embedded within existing teams?
 - Should the CoE operate as a centralized entity, a decentralized network, or a hybrid model?
 - Which staff should be part of the CoE to ensure its effectiveness?
 - Should the CoE primarily serve internal teams, support external clients, or focus on partners and ecosystem collaboration?
 - If the CoE is internally focused, does it also deliver AI services to the market as part of the organization's business model, or is it strictly enabled for internal AI adoption?
 
-Choosing the right organizational model depends on several factors. A CoE will always require some level of centralization to support governance, best practices, and alignment across all generative AI initiatives. However, execution is often decentralized, especially in larger organizations or industries where AI adoption varies across departments.
+Choosing the right organizational model depends on several factors. A CoE will always require some level of centralization to support governance, best practices, and alignment across all AI initiatives. However, execution is often decentralized, especially in larger organizations or industries where AI adoption varies across departments.
 
 Organizations needing greater control, compliance, and standardization might prefer a centralized model. In contrast, more distributed organizations, where business units operate independently, may opt for a hybrid approach, with the CoE providing strategic oversight while allowing departmental or regional execution.
 
-Small and medium enterprises may choose to start small and then scale. This allows those enterprises to focus on specific use cases where generative AI can immediately add business value. Small and medium enterprises may even partner with consultants to implement a virtual generative AI CoE if expertise isn't available within the organization itself.
+Small and medium enterprises may choose to start small and then scale. This allows those enterprises to focus on specific use cases where AI can immediately add business value. Small and medium enterprises may even partner with consultants to implement a virtual AI CoE if expertise isn't available within the organization itself.

learn-pr/advocates/intro-ai-center-excellence/includes/2-how-center-excellence-assists-planning-adoption-generative-ai.md

@@ -1,30 +1,30 @@
-IT projects suffer from many risks including scope creep, missing completion deadlines, and the project exceeding allocated budget. Projects that are planned out and which include best practices from the beginning are more likely to achieve their goals, be deployed within the projected timeframe, and remain within projected costs than those projects that take a more exploratory approach. A properly constituted generative AI CoE helps an organization minimize the chance that generative AI projects are unsuccessful and that the projects meet organizational aspirations.
+IT projects suffer from many risks including scope creep, missing completion deadlines, and the project exceeding allocated budget. Projects that are planned out and which include best practices from the beginning are more likely to achieve their goals, be deployed within the projected timeframe, and remain within projected costs than those projects that take a more exploratory approach. A properly constituted AI CoE helps an organization minimize the chance that AI projects are unsuccessful and that the projects meet organizational aspirations.
 
-A generative AI CoE can influence all of an organization's generative AI projects with the aim of all of those projects being successful and driving value for the business.
+an AI CoE can influence all of an organization's AI projects with the aim of all of those projects being successful and driving value for the business.
 
 ## Estimates of business value
 
-A strong reason for organizations to consider adopting a generative AI CoE is that the structured approach that a properly functioning generative AI CoE brings helps an organization reap the strongest benefits from generative AI adoption.
+A strong reason for organizations to consider adopting an AI CoE is that the structured approach that a properly functioning AI CoE brings helps an organization reap the strongest benefits from AI adoption.
 
 When implemented correctly, an AI center of excellence ensures the right people are involved at the right time. Key responsibilities of the AI CoE include: 
 
 - Aligning AI initiatives with organizational and business priorities. 
 - Measuring and communicating the impact of these initiatives. 
 - Promoting and overseeing leaders' alignment and commitment. 
-- Raising awareness and understanding of generative AI within the organization to drive adoption and build capabilities. 
-- Ensuring key business and technical decision-makers, and other stakeholders, are actively involved in generative AI initiatives. 
+- Raising awareness and understanding of AI within the organization to drive adoption and build capabilities. 
+- Ensuring key business and technical decision-makers, and other stakeholders, are actively involved in AI initiatives. 
 - Bridging the gap between technical and leadership to translate technical capabilities into business outcomes.
 
-![Diagram showing the process through which technical and domain experts can collaborate in generative AI lifecycle.](../media/technical-domain-expert-collaboration.png)
+![Diagram showing the process through which technical and domain experts can collaborate in AI lifecycle.](../media/technical-domain-expert-collaboration.png)
 
-A generative AI CoE is able to identify use cases and ensure the "organizational fit." Domain experts (from business or specific functions) play a crucial role in identifying relevant use cases, determining the necessary data, and evaluating the model's effectiveness, especially considering the unique challenges of generative AI like delusions or model variability. The CoE is able to ensure that use cases must align with the organization's overarching strategy and its ability to deliver on that strategy.
+An AI CoE is able to identify use cases and ensure the "organizational fit." Domain experts (from business or specific functions) play a crucial role in identifying relevant use cases, determining the necessary data, and evaluating the model's effectiveness, especially considering the unique challenges of AI like delusions or model variability. The CoE is able to ensure that use cases must align with the organization's overarching strategy and its ability to deliver on that strategy.
 
 ## Realistic estimates of outcomes
 
-A generative AI CoE can also ensure that an assessment is performed of how realistic the goals of a generative AI project are before a line of code has been deployed, rather than determining that the goals weren't realistic only after the project fails to meet expectations. Implementing generative AI in an organization requires a clear approach to measure its performance, adoption, and impact. 
+An AI CoE can also ensure that an assessment is performed of how realistic the goals of an AI project are before a line of code has been deployed, rather than determining that the goals weren't realistic only after the project fails to meet expectations. Implementing AI in an organization requires a clear approach to measure its performance, adoption, and impact. 
 
-Without actionable metrics, it's challenging to evaluate progress, identify improvement areas, or manage complexity. A solid strategy depends on well-defined metrics to assess performance and ensure initiatives provide value. A generative AI CoE can be responsible for tracking these metrics to ensure that organizational objectives are achieved.
+Without actionable metrics, it's challenging to evaluate progress, identify improvement areas, or manage complexity. A solid strategy depends on well-defined metrics to assess performance and ensure initiatives provide value. an AI CoE can be responsible for tracking these metrics to ensure that organizational objectives are achieved.
 
-Beyond business outcomes, it's crucial to track how effectively generative AI is being adopted within the organization. Metrics like user engagement, frequency of usage, and integration with existing workflows can reveal valuable insights into the user experience and identify areas for improvement. 
+Beyond business outcomes, it's crucial to track how effectively AI is being adopted within the organization. Metrics like user engagement, frequency of usage, and integration with existing workflows can reveal valuable insights into the user experience and identify areas for improvement. 
 
-Transparent performance metrics developed by a generative AI CoE based on organizational expectations also increase organizational confidence in AI by demonstrating its real-world impact. Establishing clear links between AI performance and business outcomes strengthens stakeholder trust and reduces adoption barriers in future generative AI projects.
+Transparent performance metrics developed by an AI CoE based on organizational expectations also increase organizational confidence in AI by demonstrating its real-world impact. Establishing clear links between AI performance and business outcomes strengthens stakeholder trust and reduces adoption barriers in future AI projects.