Digital transformation in controlling

Digital transformation and artificial intelligence in controlling - status quo and challenges

• Current trends, technological innovations and developments relating to digitalization and AI.
• Impact of AI and new technologies on companies in terms of agility, complexity and competitiveness.
• Digital business models, products and services and the role of AI in their implementation.
• Practical examples of successful AI applications such as predictive analytics, machine learning, robotic process automation (RPA) and intelligent assistants.

Influence of AI and digitalization on corporate management / controlling

• Potential and possible applications of big data analytics, AI-supported forecasts and automated decision support.
• Process automation and increased efficiency in controlling through intelligent robotic approaches.
• Practical introduction and application of relevant tools for AI, data science and machine learning in day-to-day controlling.
• Impact on the role, self-image and organization of the: controller as a data-driven business partner.

Challenges and opportunities of AI for controllers

• Dealing with ever shorter technology cycles and the dynamics of digital innovations.
• Design of agile and data-oriented corporate management.
• Quality assurance, evaluation and effective use of data and AI results.
• Positioning controllers as strategic consultants in management through value-adding, AI-based analyses.

Starting points for a successful AI and digitalization strategy

• Evaluation and further development of the digital and AI maturity level in the company.
• Identification of relevant AI use cases along the entire controlling value chain.
• Integration of AI strategies into operational business processes for sustainable value enhancement.
• Prioritization and implementation of digital solutions using open source and commercial tools.
• Creation and practical implementation of an analytics and AI roadmap.