With the research project “What can AI do for me?” a matching platform was launched that brings together companies with a need for AI applications with solution providers. The project by the Media University, GmbH, and Kenbun IT AG strengthens the networking of companies with the AI landscape.
“WhatCanAIDoForMe.com” is the name of the matching platform, which shows companies with unspecific AI projects suitable use cases and suggests suitable solution providers. The platform serves as a bridge between companies and AI solution providers. In this way, the innovative solutions of the AI landscape should be more strongly implied in companies to advance AI applications.
Businesses with AI needs can easily enter their requests directly on the platform. Suitable use cases, including the associated providers, will be suggested to you. As a bonus, a first estimated assessment of the value creation potential of their use case is given. Technically, the application is based on the AI platform Samantha from the software provider Things Thinking, which can analyse and compare texts on the level of meaning.
The introduction of the matching platform is preceded by a comprehensive study by the Institute for Applied Artificial Intelligence at the Stuttgart Media University on the possible applications and potential of AI in companies. Although AI is one of the most important technologies of the current time, most scientific studies have mainly examined the technological aspects of AI, but only a few of its effects on the value creation of companies.
The current state of research on the subject of AI certainly underlines positive effects concerning successful corporate management. So far, however, it has hardly been possible to draw any conclusions about the potential of specific use cases. For strategic decisions regarding the implementation of AI, however, corresponding insights at the application level are essential to use as the first indication of a possible return on investment that can be expected.
To solve the problem described, the “AI Value Creation” study identifies individual AI use cases, i.e. use cases in companies, and examines their potential for value creation. The aim is to provide companies with initial guidance in making strategic decisions regarding the implementation of AI applications. To this end, more than 40 qualitative expert interviews were conducted. In addition to experts from companies already using AI applications, the survey also included experts from AI solution providers and management consultancies.
The companies interviewed as part of the study belong to a wide variety of sectors, particularly manufacturing, wholesale and retail, the information, communication and media sector, and the finance and insurance sector. As part of the study, over 90 use cases were collected and systematised for the analysis. Most use cases were identified in production and supply chain, marketing and sales and customer service. In addition, some use case clusters were also used across functions.
The potential for the added value determined for the individual use case clusters is as varied as the areas of application for AI. Cost reductions are primarily expected in the production and supply chain areas, and optimization towards an efficient and uninterrupted production and logistics chain is sought. AI for process monitoring and quality control is said to have a high potential for cost reductions.
Predictive maintenance for the early detection of failures in production systems can prevent unplanned production downtimes and thus downtime costs. Accordingly, the study was able to identify the high cost-cutting potential here. For example, in agricultural production, computer vision can be used to determine the optimum fertiliser and crop protection requirements for each plant. This secures and increases the output quantity and saves resources. Increased harvest security and sustainability aspects, in turn, have a positive effect on the company’s value.
Increases in sales are primarily expected for use cases in marketing and sales. Areas of application are, for example, search engines integrated with shop systems and customer segmentation and personalization of offers. For companies, especially in the media industry, churn prediction, i.e. the determination of subscriber cancellation probabilities, also harbours significant sales potential. Customers with a high risk of cancellation can thus be identified and won back with appropriate retention measures.
In the long run, the customer lifetime value can also be improved. In addition, AI also offers the possibility of reducing costs in marketing and sales. An AI-driven pricing system, for example, can allow a company to adjust prices based on competitor demand and prices dynamically. Especially in e-commerce, when numerous product prices have to be updated, automation through AI can bring significant cost advantages.
But important processes can also be simplified across departments using AI applications, especially in repetitive processing tasks. Depending on the application, cost savings and increases in sales and company value can also be expected here. In addition to the operational factors mentioned, some experts stated that AI positively affects employee satisfaction. The simplification of routine activities achieved through AI applications enables employees to take on more demanding and creative tasks. This promotes the self-realisation and motivation of the employees in the workplace, which has a positive effect on the further development of the company.
The use of AI in companies thus also ensures competitive advantages. Companies that use AI successfully did say that they included the use of AI as a topic in their communication to improve their corporate image and increase their attractiveness from applicants’ perspectives. The use of AI can therefore also secure advantages for companies in recruiting highly qualified specialists.
A shortage of this highly qualified staff is currently a major challenge for companies. In addition to technological hurdles, it is also important to overcome possible negative attitudes of employees and management towards AI and to build trust in the technology. For AI applications to be used successfully in companies, they must be carefully and prudently planned. For example, the quality and the data infrastructure are key factors influencing and success factors. It is also important that employees and managers of the company show an open and positive attitude towards the topic. Anyone who sees AI as an opportunity positions the company in the direction of progress.
The “AI Value Creation” study shows the wide range of potential in the individual corporate areas and sectors and what obstacles companies still have to overcome for successful implementation. It is important to analyse these potential obstacles before using AI in your own company to transform the company into the future with the help of AI applications.
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