Role of Artificial Intelligence (AI) in Enriching Firms Strategic Management Capability

Artificial Intelligence (AI) technologies which use complex computer systems and machine learning are emerging as powerful tools that enhance the capabilities of human intelligence to help in solving complex business problems and making effective strategic decisions where human intelligence has limitations. AI is not a business strategy but can be regarded as a functional strategy or a subset of a firm’s digital strategy (functional) that can support a firm’s business, functional, and corporate strategy to create additional value for the firm. As a functional strategy, it can enhance the decision-making capabilities of all three types of strategy and improve resource productivity and cost efficiency.

In the 21^st century, technological forces are reshaping the business environment in which Artificial Intelligence (AI) technologies are transforming all aspects of businesses, including commerce, production, and social interaction.  The combination of existing knowledge from electrical engineering and computer science created a new knowledge area known as “Artificial Intelligence (AI),” which, when further combines with decision-making principles, can help businesses make intelligent decisions. By combining the components and knowledge from these areas such as algorithms, big data, transducers, sensors, and AI, creates external intelligence—not present in the firm’s workers but outside the firm’s boundaries in the virtual economies’ algorithms and intelligence machines. AI tools are used to support business operations in optimizing workflow and enhancing productivity. The benefits of AI can be achieved through automating repetitive tasks, generating information, big data processing, and predicting future performance based on data analysis.

A more creative form of AI is Generative AI (GenAI) which descends from AI and can generate original content, such as text, audio, video, images, and software codes in response to a demand or request. It depends on more advanced forms of machine learning models known as deep learning models, such as large language models (LLMs). GenAI offers several benefits, including productivity improvement, enhanced efficiency and creativity, and can improve the decision-making capability of an organization.

Here are some important areas of strategic management in which AI technologies, such as GenAI, including large language models (LLMs) can help in enriching firms’ strategic management capability:

Scenario Analysis or Scenario Planning

In developing strategic plans and managing strategic change, it becomes imperative to explicitly address and understand the strategic implications of uncertainty in more detail. Scenario analysis or scenario planning is a powerful tool for systematically identifying and analyzing the sources of uncertainty facing an industry or a firm and converting them into useful scenarios. A scenario is a firm’s consistent view of how the future might unfold in light of current trends and uncertainties in the firm’s external environment. Scenario planning is also called contingency scenario planning (CSP). However, CSP is explicitly used to address rapid or sudden changes in the firm’s external environment.

The environmental uncertainties that exist in the firm’s external environment pose a threat to strategic managers because it constrains their ability to develop strategic plans and make strategic decisions to keep the firm in equilibrium with the external environment. For example, increased globalization creates additional markets, which increase the number of strategic factors and complexity for the firm in making decisions.

Scenario analysis or scenario planning can identify threats and opportunities, evaluate current strategies, generate new alternative strategies, build consensus, and develop flexible thinking. We can further evaluate the generated strategies under different scenarios to identify the most robust strategies. Historically, governments, businesses, and the military have used scenarios for a long time as a powerful tool to mitigate the consequences of uncertainty. However, because of the increased intensity of uncertainty in the business environment in the past two decades, the effectiveness of scenarios has been reduced. Traditional tools available for scenario analysis fall short in identifying trends and external strategic factors, are time-consuming, and limit the number of scenarios they can handle.

However, new AI technology-based tools, such as GenAI, can overcome the challenges faced by traditional CSP or scenario planning. It is expected that generative AI can substantially improve a firm’s capability to perform CSP much faster and at a lower cost than conventional methods. To further improve the effectiveness of CSP, firms can use advanced generative tools such as large language models (LLMs) which can help in identifying and generating innovative ideas for scenarios, evaluating and combining scenarios, and formulating scenarios based on trends.

Measuring Firm’s Long-term Performance

The primary purpose of strategic management is to maximize the firm’s performance in the long-run, maximize the long-run profit, or maximize the enterprise value in the long-run. However, to improve or maximize performance, it is imperative to measure and control it. There is a saying if you cannot measure, you cannot control. To improve or maximize performance through strategic management’s performance management system, strategic goals are translated into performance targets, and then performance results are monitored, evaluated, and controlled against the targets. To become successful, performance targets must be clear and consistent with long-term goals and linked to the firm’s strategy. However, the typical strategic management model’s evaluation and control element uses a feedback control system that is not appropriate to measure and control long-term performance, because a feedback control system can only measure short-term performance successfully. Therefore, the performance targets should be measured and monitored over the short term only. The other problem in the performance management system is that disaggregating long-term goals into short-term performance targets and key performance indicators (KPIs) remains an enormous challenge. Moreover, integrating or rolling up the short-term targets does not meet the goals specified in the plan for several reasons. However, these anomalies can be corrected.

GenAI and LLMs data analytics capability: data analysis, processing, iterations (in feedback-tuning), mining, and predictive capability can successfully resolve long-term performance measurement issues.

Enriching Idea Generation, Focus, and Strategic Decisions Making

Making strategic decisions involves deciding on which issues to focus on. Without focus, things you want to do can be spread across many areas of activity. Focus provides direction for strategy and helps in targeting those areas where the return is maximum. Focus can also provide direction for idea generation in innovation, idea screening, project selection, and resource commitment and deployment.

Generative AI tools such as LLMs can help in identifying, generating, and evaluating new ideas and areas (arenas), generating alternative strategies, and enriching focus and organization’s strategic decision-making capability.

Risks and Challenges of Generative AI

GenAI offers enormous potential to create additional sources of value and profitability for firms in all industries. From the above discussion, we see that GenAI can become an indispensable tool in the future for strategic management. However, currently, it is still in its infancy stage and not fully commercialized, and therefore, presents considerable risks and challenges to users, developers, and society. It faces complex operational and external issues, such as hallucinations, inconsistent outputs, unwanted bias outputs, deepfakes, and threats to privacy, security, and intellectual property.

To mitigate the risks and challenges of hallucinations in GenAI, for example, firms should consider the use of GenAI as an external optional complementary resource that can augment the firm’s strategic decision-making capability. Because using GenAI involves high risks, subject matter experts should review the GenAI output for content reliability and accuracy and should not blindly implement the strategic decision outputs generated by GenAI.

References and Further Reading

1. Camilo Quiroz Vazquez and Michael Goodwin, What is Artificial Intelligence (AI) in Business? IMB (February 20, 2024).
2. Ashok N., Digital Strategy, Digital Marketing Strategy, and Tactics, A&N Strategy Consulting (September 15, 2016).
3. M. Grant, Contemporary Strategy Analysis (United Kingdom: John Wiley & Sons, Ltd., 2018), Chapters 2 and 15.
4. Cole Stryker and Mark Scapicchio, What is Generative AI? IBM (March 22, 2024).
5. Ashok N., Combining Scenarios and Real Options to Address Uncertainty in Strategy Formulation, A&N Strategy Consulting (April 17, 2022).
6. Daniel J. Finkenstadt et al., Contingency Scenario Planning using Generative AI, California Management Review (Jan 22, 2024).
7. L. Wheelen et al., Strategic Management & Business Policy (Malaysia: Pearson Education Ltd., 2018), Chapter 4.
8. Ashok N., Effective Performance Measures of Corporate Control, A&N Strategy Consulting (December 31, 2020).
9. Robert G. Cooper and Scott J. Edgett, Product Innovation and Technology Strategy (U. S: Product Development Institute Inc., 2009), Chapters 3 and 4.
10. Alexa Trachim, How LLMs for Data Analysis can Support Businesses? In Data Labs (April 16, 2024).
11. Daniel J. Finkenstadt et al., Use GenAI to Improve Scenario Planning, Harvard Business Review (November 30, 2023).
12. Mostafa Sayyadi and Luca Collina, How to Adapt to AI in Strategic Management, California Management Review (June 6, 2023).