Key components of a persuasive message
1. Based on your reading, what are the seven key components of a persuasive message? Provide a brief explanation for each component.
2. Explain the key components of the ADKAR model. How can this model be best utilized to complete a successful change within an organization? Identify types of organizational changes that are best suited for this model of change.
3. This is a Collaborative Learning Community (CLC) assignment.
The purpose of this assignment is to discuss the impact of AI in the workplace from the perspective of leader responsible for implementing change.
New technology, such as generative artificial intelligence (AI), is ever-present in the business realm and requires organizations to change frequently and in significant ways. Research an organization that recently implemented new technology. Also, refer to the Topic 8 Resources and additional research sources regarding current AI trends.
You are assigned as leaders in a task force at an organization of your group's choosing (i.e., either one where one of you are currently employed or one your group is interested in researching that meets with instructor approval) where your team is tasked to identify the potential uses for AI to improve productivity.
Using the "CLC – AI in the Workplace" template, in 1000-1250 words, address the following:
• Briefly describe your selected organization, including its industry and the market it serves.
• What are the benefits of implementing AI in this organization? Provide two examples of how it can be deployed to improve efficiencies and what new innovation opportunities could be pursued by redirecting resources from tasks that AI can now perform.
• What challenges may be encountered by the organization in implementing AI in the ways that you recommended? Explain what counteractions can be employed to address these challenges.
• Identify at least one internal and one external stakeholder who may be impacted by this potential change. What unintended consequences may occur that will impact one or more of these stakeholders?
• What ethical considerations may arise from the implementation of AI in the organization?
• Refer to Topic 8 Resources. From a Christian worldview perspective, how can the use of AI promote human dignity, stewardship, and/or human flourishing?
General Requirements
Sample Solution
1. Seven Key Components of a Persuasive Message:
- Credibility of the Source: The audience needs to believe the message sender is trustworthy and knowledgeable.
- Logical Appeal: Present clear arguments and evidence to support your claims.
- Emotional Appeal: Connect with the audience's emotions to evoke a desired response.
- Strong Opening: Grab the audience's attention and introduce the topic effectively.
- Clear Message: Clearly state your message and desired outcome.
- Strong Closing:
Full Answer Section
- Audience Awareness: Tailor the message to resonate with the audience's needs, interests, and values.
- ADKAR Model for Successful Change Management:
- Awareness: Ensure everyone understands the need for change and its potential benefits.
- Desire: Create a desire within employees to embrace the change.
- Knowledge: Equip employees with the knowledge and skills necessary for the change.
- Ability: Provide opportunities for employees to practice and develop the required skills.
- Reinforcement: Offer ongoing support and recognition to reinforce the desired behavior.
- Leadership: Champions the change, communicates the need (Awareness), and fosters a positive attitude (Desire).
- Training & Development: Provides the knowledge and skills for the change (Knowledge, Ability).
- Performance Management: Offers ongoing coaching, feedback, and recognition to sustain the change (Reinforcement).
- Implementing a new enterprise resource planning (ERP) system
- Shifting to a remote work model
- Upskilling employees for automation or digital transformation
- Improved Efficiency and Productivity:
- Example 1: Automated Data Entry: Deploying AI for data entry tasks can free up employee time for more complex analysis and creative work.
- Example 2: Predictive Maintenance: AI can analyze sensor data from equipment to predict maintenance needs, preventing costly downtime and optimizing resource allocation.
- Innovation Opportunities: By freeing up human resources from routine tasks, AI can enable organizations to pursue new innovations.
- Example 1: Product Development: AI can analyze market trends and customer data to identify opportunities for new products or services.
- Example 2: Research & Development: AI can expedite research processes by analyzing vast datasets and identifying promising avenues for scientific exploration.
- Cost: Implementing and maintaining AI systems can be expensive, requiring upfront investment and ongoing support.
- Job Displacement: Some tasks currently performed by humans might be automated by AI, raising concerns about job losses.
- Data Bias: AI algorithms can perpetuate biases within the data they are trained on, leading to discriminatory outcomes.
- Cost-Benefit Analysis: Thoroughly assess the cost of AI implementation against the potential benefits for a positive return on investment (ROI).
- Reskilling and Upskilling: Invest in retraining employees for new roles that complement AI capabilities rather than being replaced by them.
- Data Governance: Implement robust data governance practices to ensure data quality and mitigate algorithmic bias.
- Internal Stakeholder: Employees: The fear of job displacement could cause anxiety and resistance to change.
- Unintended Consequence: Decreased employee morale and reduced productivity.
- External Stakeholder: Customers: Concerns may arise regarding data privacy and the ethical implications of AI decision-making.
- Unintended Consequence: Loss of customer trust and potential brand reputation damage.
- Transparency and Explainability: AI algorithms should be designed in a way that allows for transparency and explanation of their decision-making processes.
- Data Privacy: Organizations should implement robust data security measures and adhere to data privacy regulations.
- Algorithmic Bias: Regularly audit AI systems for potential biases and take steps to mitigate them.