Developing AI use cases in business requires finding the right talent. There are several possible options, such as:
- Specializing in business experts – Indeed, hiring a data scientist is uk email list expensive for a small business. Therefore, we can train a business expert to become a data citizen.
- Hiring data scientists – If the company can afford it, this is certainly the best solution. Developing internal skills is an important long-term asset for companies.
- Consulting firms – Outsourcing resources is also possible. An intermediate step is to recruit a junior data scientist and seek advice from a consultant on the strategy to adopt.
Once this choice is made, there is only one important ingredient missing for the use of AI to be implemented on an enterprise scale.
Speaking the same language
For AI to be successfully used in business, it’s imperative that employees nepal phone number list for business growth and customer connection develop a common language. This is especially critical for smaller companies, which often lack the resources to hire a team of data scientists. This requires creating an environment that empowers employees to become more data-savvy .
This is where the concept of data literacy comes in . Literally, this means knowing how to read and write data. More concretely, it means knowing how to interpret data, but also how to communicate it. The idea is for employees to be aware of the importance of data, the possible applications, and the limitations of artificial intelligence.
Executive training focused on data management and enhancement
In the field of digital transformation, it is essential for executives to develop a solid understanding of data science concepts. One initiative that addresses this need is the Certificate of Advanced Studies (CAS) in Data Science & Management, developed jointly by HEC Lausanne and EPFL.
The CAS in Data Science & Management offers a unique program designed specifically for mobile list business executives. At the intersection of technology and management, it focuses on concepts such as:
- Enterprise Data Maturity Assessment
- Understanding and implementing an effective data strategy
- Data governance and quality management
- Proficiency in data visualization and dashboard design
- Discovering machine learning and the role of data scientists
To ensure a good understanding of the concepts taught, participants carry out a company project related to data management or enhancement.