Case 2 and Discussion 2

Strategic Advantage: Analytics and Economics

Assignment Overview

Economic Implications of Organizational Strategies

Most college students take at least one undergraduate economics class, which they often quickly forget. When the pandemic created a global economic event, the lessons of that class became more critical as businesses navigated uncertain circumstances. This case will allow you to expand what you learned in Tridents MBA Economics course.

Case 2 Resources

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Leadership: (2022)

Managing Operations: (2022)

Data Analytics: (2022)

Financial: (2022)

Marketing: (2022)

Ethics: (2022)

Case Assignment

Using Economics to Guide Strategy

The global economy will function differently in the foreseeable future due to the effects of pandemic disruptions, a war in Europe, and inflation. The term new normal is being used as organizations figure out how to leverage environmental analyses and develop strategies in uncertain times. As with all of the other strategies undertaken thus far in class, a multidisciplinary approach is necessary.

While not focusing on a single business or industry, research how strategic management is facilitating plans to support organizations in the post-COVID economy. Use quality research published within the last year. Articles from the library databases are a good choice. Library databases allow searching by date. In Google search, click Tools and enter the date range.

• Leadership: Look at the management planning function under economic uncertainty. (1 page).
• Managing Operations: Assess how operations can be scaled to support changing economic conditions (1 page).
• Data Analytics: The role of data analysis. (1 page).
• Financial: Examine accounting/finance practices that can be applied. (1 page).
• Marketing: Consider how marketers contribute. (1 page).
• Ethics: Include ethical concerns. (1 page).

Making Connections

• Explain how Strategic Management provides a foundation for the cross-functional teams to join forces to steer an organization in economic uncertainty. (1 page; research required)

No quotations are permitted in this paper. Since you are engaging in research, and . NOTE: Failure to use research with accompanying to support content will result in reduced scoring Level 2-Developing across the grading rubric. This is a professional paper, not a personal one based on feelings. It must be written in the third person. This means words like I, we, and you are not appropriate.

Assignment Expectations

Use the attached APA-formatted template () to create your submission.

• The template is set up in APA 7: double-spacing, font, margins, headings, page breaks, APA help links.

Your submission will include:

• Trident University Internationals cover page
• A paper with APA citations (2- to 3-sentence introduction, 7-page body, 2- to 3-sentence conclusion)
• The reference list page in APA format

Discussion:

Module 2 Discussion Week 1 Resources

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Week 1 Discussion Post

Using the readings and internet research, discuss the pros and cons of artificial intelligence as part of a data strategy. (Research Support Required)

This post should be 2 paragraphs (150-200 words). Since you are engaging in research, in the body of the post and . NOTE: Failure to use research with to support content will result in reduced scoring “Level 2-Developing” on the grading rubric.

Respond to: Review both student’s post and share your reactions and thoughts

Each reply should be one paragraph (or about 75 words) and must be substantive. Do not simply say “I agree” or “That is great.” Specify why and be detailed in your explanation. You may use research in your responses, but it is not required.

Amber Flynn posted Feb 1, 2026 5:08 PM

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Artificial Intelligence (AI) will rapidly transform data analysis and provide companies with unprecedented decision-making, forecasting, and work productivity. A director is empowered with artificial intelligence in order to process large volumes of structured and unstructured information, discover hidden forms, and accelerate practical realizations rather than conventional procedures (Harvard Business School Online, 2024). Hybrid acumen, which combines human beings’ discernment with AI skills, has emerged as a tactical method balancing automation with key reflections to help companies avoid overreliance on methods while enriching breakthroughs and awareness . Companies can improve risk assessment, forecast movement, and maximize supply distribution, all of which contributes to long-term tactical systematic planning by integrating automated reasoning into data methods.

However, the use of artificial intelligence in management plans is not without risk. Such moral issues as systematic partiality, data privacy difficulties, and the potential misuse of forecasting analysis may harm stakeholder confidence and lead to control difficulties (Headley, 2025). Establishments that fail to comply with AI supervision may suffer functional weaknesses, reputational damage, or a dearly-earned conformity misdemeanor . Hence, as artificial intelligence provides an essential calculated advantage, a director needs to apply moral systems, vulnerability monitoring, and human supervision to ensure the safety, long-term, and productive integration of AI into data-driven decision making.

References

Harvard Business School Online. (2024, August 14). 5 ethical considerations of AI in business.

Headley, J. (2025, April 28). AI risk management: Weighing the pros and cons of AI in your business. Warren Averett.

Albert Pagan posted Feb 1, 2026 7:07 PM

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Hi Class,

AI can be used as an enabler of data strategy, as it can help an organization better process and analyze data, and make decisions at a faster rate. If an organization has good quality data and proper governance, AI techniques can be applied to, for example, predictive analytics, fraud detection, or automation of repetitive processes, allowing leaders to recognize risks and opportunities that are not possible to find through standard analytical techniques. Data management processes can also be augmented with AI, e.g. in data classification or data quality monitoring. This, however, requires that data is in a suitable state for AI; according to Gartner (2025), a frequent reason why AI projects fail or fail to deliver intended results is due to a lack of consistent and well-structured data. In this sense, governance is an important foundation for proper AI use.

AI use also introduces new considerations for data strategy, as quality and bias issues with the data may result in inaccurate or unethical outcomes, while expanding use of AI may also raise privacy, security, and accountability risks. According to National Institute of Standards and Technology (2023), AI risks need to be accounted for at all phases of system lifecycle, and, according to Organisation for Economic Co-operation and Development (2024), transparency and explainability of the results need to be ensured. These factors also need to be addressed, or AI could in fact undermine rather than help establish trust.

References

Gartner. (2025, February 26). Lack of AI-ready data puts AI projects at risk.

National Institute of Standards and Technology. (2023). Artificial intelligence risk management framework (AI RMF 1.0) (NIST AI 100-1).

Organisation for Economic Co-operation and Development. (2024). AI, data governance and privacy.