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. How Companies Create Value by Using AI ?

Since the technical and the financial value associated to AI is a topic with a lot of article about it, I will mainly focus on the other indirect benefits. To get some insight, I interviewed multiple Chief Technical Officer and Chief Data Officer of companies that are using IA.

1. Transforming Corporate Image

This technology helps transform the company’s brand image. Most of the people interviewed think that this is a very important characteristic to develop and maintain. The use of advanced technology demonstrates the ability to innovate and people can see them as leaders in their field.

For some, this transformation takes the form of their willingness to share their code in open source, for others it is through communications made on the media. According to some participants, the media such as TV channels, radios or newspapers are interested in reporting these innovations made by companies because they capture the interest of the public.

2. Improving Marketing

Artificial intelligence creates value in marketing by making it easier to acquire new deals. This technology is a marketing asset because it provides solutions to complex problems and people are willing to work with those who master their business. Today, AI has become a new selection argument during tenders because the use of this technology often results in a better service.

By training sales people on the benefits of using AI, it can help to interest customers by addressing their needs that would not have been taken into account by other solutions. Furthermore, sometimes in certain industries, the use of these technological advances has become a necessity, as all competing companies already offer them.

3. Increasing Attractivity

This transformation of the company’s image and the technological breakthrough help attract different types of profiles. Some people working in the startup world explain that the integration of AI in their companies helps attract investors. In addition, the ambition of companies to undertake complex projects attracts the attention of data scientists. Due to the current shortage of profiles, it is sometimes difficult to recruit them.

Several Chief Data Officers explained that for profiles such as Data Scientists, Data Engineer or Data Analyst, technical challenges are among the main criteria for choosing their job. Moreover, once they have been hired, the challenge is to keep them within the company, as they are highly coveted profiles. The impression of being in an innovative company and responding to complex societal problems can partly play a role in the decision not to leave.

4. Changing Corporate Culture

Artificial Intelligence allows companies to transform their corporate culture. More precisely, the implementation of innovation projects demystifies the use and applications of Big Data and AI. On the one hand, for many people, these technologies are a kind of magic solution to all problems. On the other hand, these technologies are so abstract that people don’t see the use case to solve their business problem.

Understanding these areas allows for an increase in employee skills, which is indirectly a long-term investment for the realization of new projects. In addition, the completion of a project in one part of the business can spark interest in similar use in other parts of the company. Several Chief Data Officers explained that these practices are common across their different business units. Finally, by understanding the value of these technologies, business leaders increase their willingness to invest in new projects.

5. Creating Reflexion

Because of their complex stakes, the integration of artificial intelligence within companies can generate new thoughts. Because of the technical or economic advantages linked to the use of this technology, new marketing strategies can be envisaged. Furthermore, it can for example lead to discussions about the ethics of handling user data. These reflections are more and more common with the evolution of laws such as the GDPR in Europe.

Even if the ethical limits of AI and data processing are often debated, there is a big ecological issue related to this technology. To train the different models, it requires a lot of data and a lot of computing power. Many countries do not yet have a large proportion of green energy, so AI is indirectly mostly a very polluting mechanism. In this regard, the use of these technologies creates new reflections on the values of companies and their objectives

IV. Conclusion

As explained, all these other forms of value have an indirect effect on companies. However, for some, projects remain at the idea stage and never materialize. For others, AI results lack comprehensibility and they prefer to use naive algorithms. This discrepancy between ambition and reality raises questions for many about the use of these technologies in companies for political rather than functional purposes. Nevertheless, for many, because of the significant investment involved in these projects, its use is more about meeting a real technical need than an image need.

The various research papers reviewed give little attention to other forms of value of AI. As explained by Smith and Colgate (2007), companies more generally generate several types of value. However, this research paper focuses mainly on the different channels of value provision for the user, in contrast to this analysis showing rather the beneficial impact for the company. However, this does not mean that there is no value provision for the user.

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