I. What Is Value for Costumer?

Before discussing how IA can create value for companies, we have to define what is “value”. The purpose of a business is to bring value to someone. Based on some research, according to Canhoto and Clear (2020), the value of something is defined by the utility it brings to its user. Moreover, according to Smith and Colgate (2007), there is no common agreement on the definition of user value. To address this unknown, they define a framework with 4 types of value.

• Functional value: A product (good or service) has desired characteristics and performs a desired function.
• Experiential value: Creating appropriate experiences, feelings, and emotions for the customer.
• Symbolic value: The customers attach or associate psychological meaning to a product.
• Cost value: Customers try to minimize the costs and other sacrifices that may be involved in the purchase, ownership, and use of a product.

Even if this vision of value is incomplete, it covers the vast majority of the forms of value for a customer.

This notion of “value” is to be distinguished from “added value”, which corresponds to the financial representation associated with a value contribution.

II. How Companies Create Value?

Furthermore, Smith and Colgate (2007) defined four value proposition channels for the company:

• Information: Value creation through activities associated with advertising, public relations and brand management (e.g. through packaging, labeling or instructions).
• Product: Value creation through activities associated with new product development, market research, research and development, and production.
• Interaction: Value creation through activities between customers and organizations or systems are created, or enhanced, by value-chain activities relating to recruitment and training, service quality, and operations.
• Ownership Transfer: Value creation by facilitating the customer’s experience with accounting (such as payment and billing), delivery (such as picking, packing, shipping, and product tracking), and transfer of ownership (such as contracts, copyright agreements, and titles).
• Environment: Value creation through activities associated with facilities management, interior design, and merchandising.

Looking at the scientific literature, multiple techniques for creating value are possible. However, from the way companies are presented in particular in the article by Ransbotham et al. (2017), it seems that the majority of companies focus on functional value creation.

III. AI Business Opportunity

1. Customer Knowledge

Artificial intelligence allows for a better understanding of customers. Understanding consumers is a real asset for companies, as it allows them to identify cosumers’ interest in the products or services offered and how the company can create items tailored to their needs.

For example, the company can achieve this by segmenting customers into different categories. On the one hand, classification makes it possible to attach a user to an already defined group. On the other hand, clustering makes it possible to create groupings of people that were not clearly defined beforehand. More concretely, companies can, for example, determine how to retain their customers by defining the next best actions or offers to make.

2. Improving and Personalizing User Experience

Artificial Intelligence can be used to improve the user experience by personalising it or making it easier to use. For example, it is possible with this technology to create a more personalised customer relationship through a chatbot.

In addition, the experience can be tailored to the user by suggesting content that they might potentially like. This solution based on a recommendation system is for example used by Netflix to propose films associated with the user's tastes. Thus, the great added value of this platform lies in the fact that it is easy to use in order to obtain content appropriate to the customer's expectations.

3. Process Optimization and Operational Efficiency

AI enables companies to perform process optimization. In concrete terms, tasks that were carried out manually by a user can be automated. For example, the use of OCR can retrieve the content of an image that no longer needs to be written manually.

Indirectly, Artificial Intelligence also makes it possible to increase the speed of information processing. A task that could take a human being minutes to complete can be done in seconds by a machine. In addition, the analysis done by the computer can be more accurate and consistent, as it gives the same attention to each task and can be used at any time.

4. Risk Reduction

It is possible with this technology to reduce the risk of an event occurring in the future. For example, it is possible to understand the life cycle of an object and predict when it will fail in order to solve a problem before it happens.

Alternatively, it can be used to reduce bank fraud to analyse whether a transaction is being used to fund terrorism or money laundering. Mitigating these risks can be complicated for humans, as it requires constant attention to thousands of near-instantaneous transactions, and only algorithms with a fine-grained and rapid understanding of the different variables can reduce these risks.

5. Complex Problem Solving

AI can be used to solve complex problems. Computers can take into account certain reasoning that is too difficult to be fully understood by humans. Because of the computing power that can be used, it is also possible to reduce a large amount of data to a few variables that can be interpreted more easily by humans.

In recent years, AI algorithms have improved to solve complex problems. Since 2015 and the development of Neural Networks, several projects have shown that this technology can beat human reasoning. For example, the company DeepMind with its AlphaFold project was able to prove that an AI can help to make major scientific advances in the field of health.

6. Access New Markets

Artificial Intelligence can be used to conquer a new market. Because of all the advantages and examples of use outlined above, this technology can give a company an advantage in expanding into a new business sector. According to Ransbotham et al. (2017), 75% of companies want to use AI to access new markets.

IV. Conclusion

These six themes may seem very similar in their response to different types of opportunities, as the underlying algorithms are sometimes very similar. To explain these similarities, it is possible to summarise them in four main families of needs:

• The need to describe: to explain a phenomenon by describing what is happening
• The need to understand: to explain why a phenomenon occurs
• The need to predict: to explain what phenomenon will happen in the future
• The need to control: To control a phenomenon by solving problems before they occur or by reducing the probability of their occurrence

There are a lot of way to create value for customer but we see that most of the interviewed companies use this technology for internal solutions.

Looking at the different research paper in this topic, they agree that AI can be used to reduce costs and access new markets. However, other themes such as customer knowledge or improving the experience are not clearly stated. For example, Ransbotham et al (2017) presents the reasons for adopting AI rather than the opportunities for its use. Comparing Smith and Colgate's (2007) research, AI helps to address the types of user values that are related to functional solutions and cost reductions. In addition, it also addresses the experiential need by improving interactions such as with the use of a chatbot or by adapting the shopping environment possible through user understanding.

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Canhoto, A. I., & Clear, F. (2020). Artificial intelligence and machine learning as business tools : A framework for diagnosing value destruction potential. Business Horizons, 63(2), 183‑193. https://doi.org/10.1016/j.bushor.2019.11.003

Ransbotham, S., Kiron, D., Gerbert, Ph., & Reeves, M. (2017). Reshaping Business With Artificial Intelligence : Closing the Gap Between Ambition and Action. MIT Sloan Mangement Review and The Boston Consulting Group, 59(1), 1‑17.

Smith, J. B., & Colgate, M. (2007). Customer Value Creation : A Practical Framework. Journal of Marketing Theory and Practice, 15(1), 7‑23. https://doi.org/10.2753/MTP1069-6679150101