“Just start with AI” is certainly a good credo at the beginning of the AI journey. However, if you want to go beyond prototype applications, have achieved initial AI successes and want to scale them, you should also take a strategic approach to large-scale AI implementation.
Read more in this blog post:
- Which influencing factors you should consider when investing in AI
- Which prerequisites enable a sustainably positive AI ROI
- How AI ROI can be measured and optimized in practice
- How KPIs and a personal exchange of experiences contribute to AI-first companies
What do companies expect from the use of AI?
An ROI example from customer service
The use of an AI chatbot in customer service can potentially realize all these expected benefits, as the following quantitative example illustrates: A medium-sized company with 100 employees has a service team with 5 FTEs. An AI chatbot is to be implemented for the automation of service requests, which:
- answer simple customer inquiries independently
- makes the internal knowledge database more searchable for service employees
The costs incurred amount to approx. 20,000 euros per year in the first year and approx. 17,000 euros in subsequent years. Employee costs in service without automation amount to approx. 300,000 euros per year. If 30% of service requests are automated, the company can save 1.5 FTEs or deploy them elsewhere and thus save 90,000 euros per year in service. This means that the AI implementation pays for itself in the first year.
An ROI example from internal knowledge management
The medium-sized company from the previous example also relies on AI for internal knowledge management in order to make processes more efficient. Although the return on investment (ROI) cannot be calculated as precisely as in customer service, a rough, quantitative estimate is still possible.
If all 100 employees save 10 minutes a day – at a very conservative estimate – by using an AI chatbot or CompanyGPT, for example through quick access to guidelines, processes, instructions or reusable text modules, this results in an annual productivity gain of around 3,600 hours. At an internal hourly rate of 40 euros, this corresponds to a value of around 145,000 euros, which can be used for other tasks.
At 15,000 per year, the costs for a second AI chatbot are already significantly lower than the initial implementation.
Consider AI scaling from the outset
The prioritization of use cases, meaningful ROI evaluations and the technical setup or use of a suitable AI platform are crucial for AI success. Companies that use different solutions for their AI automation not only pay more, but also need significantly more time to realign their processes. Kauz.ai’s aiSuite, on the other hand, provides you with best-in-class AI tools for data, chatbot and agent management on a single platform. This is constantly being expanded with new value-adding AI methods and simplifies and expands the possible uses of artificial intelligence in companies.
Creating the right set-up for all AI maturity levels
Companies that take artificial intelligence seriously as an economic growth driver often start with pilot projects and gradually expand them. By introducing central responsibility for AI – in the form of an AI manager, for example – interdisciplinary project groups can develop into sustainable professionalization. In this way, initial training courses in individual departments develop into a company-wide, everyday use of AI tools. The following overview of AI maturity levels helps to keep the possible organization of the future in mind, even at the beginning of the AI journey.
Take qualitative assessment criteria seriously
The introduction of artificial intelligence (AI) requires openness and a willingness to explore at every stage of organizational maturity. The exchange of experience between AI users within companies plays a central role in this – it promotes creativity, the ability to learn and continuous development in dealing with new technologies. A platform provider that not only provides new AI functions, but also communicates them transparently and regularly, makes a decisive contribution to establishing a continuous learning culture. In times of rapid technological developments, this ability to learn is a key competitive advantage.
AI transformation: ROI and other success factors
In this webinar, AI experts will provide insights into successful AI transformations. Learn more about AI use cases, their evaluation as well as organizational and technological setups for a successful AI implementation.
Westfalenhallen Group of Companies
Find out how the trade fair provider was able to automate recurring requests for different trade fair events.
ias Group
Find out how the integration of generative AI improves the health portal and optimizes the use of information by customers.
