The Use of Artificial Intelligence to Improve Strategic Management Practices in Organizations

Artificial Intelligence (AI) has had revolutionary disruptions in almost every industry and is set to trigger revolutionary changes in the notion of strategic management. AI’s digital change, which is driven mostly by data, can assist in optimising organisations. Indeed, the application of AI in various aspects of business management entails significant opportunities. However, it is also stated that AI brings challenges in adoption, particularly in the early stages of AI deployment. This requires a study on how AI technology is likely to influence the strategic management of organisations so as to establish if its use will improve strategic management practices with a view to improving productivity and performance. This essay aims to discuss the role of strategic management enhancement through the examination of AI support for decision-making.

The Concept of Strategic Management

Strategic management can be defined as the process whereby organisations acquire and use appropriate strategies in the pursuit of their goals and objectives (Miller). Strategic management usually involves those in the organisation's management team who are expected to come up with decisions that would help achieve the management goals and objectives of the given organisation. It involves decision-making processes like rational action and environmental scans, which are generally performed by management. With increasing levels of uncertainty in the conduct of business operations due to technological advancement, there is a need to improve strategic management practices. Particularly, strategic decision-making calls for this high level of managerial cognition that may not be easily attained given the burgeoning complexities and uncertainties in the business environment (Keding 105). The amount of information that is required to be processed by strategic decision-makers is staggering, but these decision-makers are not machines. However, it is also important to look at the opportunities that technological developments have opened up to enhance strategic management practices. Since it is a more efficient knowledge source, AI can address the challenges associated with the decision-making process in the context of digital transformation.

Understanding Artificial Intelligence

AI stands for artificial intelligence, a technology that aims to imitate human intelligence with computers. Some of the human intelligence that AI tries to mimic includes judgment, sight, logic, and solving (Keding 92). It is worth noting that AI models can mimic human intelligence, and this capability can assist in overcoming some cognitive constraints that strategic decision-makers may possess. Simulated human intelligence enables AI to interpret data, learn from it, and use the insights to accomplish tasks using three critical aspects of AI: analytics, predictive AI, and machine learning (Keding 92). The importance of these aspects lies in the fact that AI is capable of addressing tasks that are relevant to human intelligence, including business ones. Remarkably, the algorithms being applied to AI models provide this technology with the capability of self-learning via machine learning. This integration makes AI more competent in tackling tasks that humans can do while attending to other issues like data overdoses.

The Impact AI Can Have On Strategic Management

With these varied functionalities of AI, there is little doubt that AI has the potential to significantly contribute to strategic management. AI models have been revealed to have better knowledge for strategic decision-making due to some attributes like algorithms (Keding 92). Applying algorithms in decision-making occurs on several occasions based on linking various problem variables applicable to big data analysis. Big data is a massive pool of information that has the potential to improve decision-making if realized. Whereas big data as a knowledge source is difficult for humans to realise due to the limitations of cognitive abilities, AI has several significant advantages. Big data can be analysed using AI, and it is also capable of learning from it.

AI can play the part of a crucial support in various sections of strategic management, for example, in the analysis of the market segment. For instance, AI can use performance data, resulting in trends and patterns that help improve an organisation’s marketing strategies (Jobanputra et al. ). It is remarkable that the identification of such trends and patterns is based on big data analysis in real time, which may increase the speed and efficiency of the decision-making process, which is a key factor in strategic management. Large amounts of information that AI processes allow organisations to make precise and pertinent decisions, focusing on the most important information, which can be overlooked when using other strategic management approaches. Consequently, the application of AI in the processes of strategic decision-making brings about an enhancement of strategic management in an organisation.

Limitations of AI

However, with the prospects of AI in strategic management, it is important to note that AI is only mechanistic in the sense that it operates based on input and output processing. AI, being a deterministic model derived solely from data, does not involve decision-making attributes like ethics and values. AI is also capable of mimicking intelligence through rationality, which is derived from data, and therefore it cannot always select the correct choice within an environment (Keding 92). This is because AI models depend on the information fed to them to learn; therefore, businesses must feed these models accurate data. These shortcomings do not mean that AI cannot support the efforts of strategic decision-makers in their endeavours. However, AI has the potential to enhance the quality of decisions within an organisation by performing and enhancing specific cognitive limitations inherent in strategic managers in a world that is becoming increasingly complex and unpredictable. For instance, AI can point the decision-makers to the data that is exactly right by employing an algorithmic approach. However, criticism has been raised on algorithmic decision-making, especially when assumed strategic choices remain random and creative (Keding 92). This concern does not take into account how AI can study from data collected beforehand. The strengths and weaknesses of AI support the idea that it should be used as a supplement, but not a replacement, in strategic management.

Ethical and Legal Challenges of AI Use

However, with the adoption of AI, several ethical issues come up that cannot be disregarded. One of the most important issues is that AI can be biased. Bias can be in the form of deliberate control of the data that is fed to the AI models or by providing discriminant data (Zuiderveen, 1972). Thus, when AI models are trained with a biased dataset, the likelihood is high that the models themselves will be biased. There are examples of bias in AI that have appeared, including discrimination using discriminant characteristics like racism. If the data that was used in the AI training process is labelled and defined discriminatively, it will be discriminative as well. This remains the case even for the data from the sample that is used to train the artificial intelligence model. Thus, misuse of artificial intelligence can have severe consequences.

Privacy is the other major concern that organisations that wish to venture into the use of artificial intelligence must consider. What is particularly concerning about AI is that it poses unprecedented risks when it comes to the protection of an individual’s data. Privacy violations can take place at any step of the AI cycle, including data collection, processing, storage, and disseminating results (Liu et al. 5). This becomes a threat, especially for shared AI models that are openly used because large-scale collection and analysis of data are possible. Also, due to AI’s enhanced features and high machine learning capabilities, it can gather user data on its own without their permission. Hence, organisations are under ethical pressure to make sure that the use of AI in their operations is ethical and legal.

In conclusion, AI has various advantages in organisations' strategic decisions. Strategic management practices can be advanced through the use of AI because it makes decision-making processes more efficient and accurate. However, most of the limitations of AI have a workaround. AI could be used by organisations to support the work of management teams in strategic management rather than replace them. However, the use of AI is associated with ethical and legal issues that organisations should consider in order to ensure that their use of AI is legal.