A strategic positioning on generative AI sets the basis to derive valuable use cases and required capabilities. We have developed a framework that supports you in laying the foundation towards your generative AI strategy. Key questions comprise:
The potential applications of generative AI are diverse and span across the entire value chain. Next to identifying potential fields of application and use cases, it is also important to manage the portfolio and set the right focus. We guide you in identifying and selecting the most valuable and feasible generative AI use cases. We bring in our deep domain- and industry expertise and have developed multiple use cases to practically showcase generative AI use cases.
A successful implementation of generative AI use cases requires the right technical and organisational basis. A unified AI platform builds upon a data platform to integrate cognitive and generative AI services like Azure Open AI or Copilot into your enterprise. We support you in assessing, designing and implementing a suitable platform for your business. Next to the technical foundation, it is crucial to design an organisational operating model that drives use case creation holistically. We also help design and set up the right operating model to organise and streamline AI activities within your enterprise.
A successful digital transformation starts with a successful people transformation and change in mindset. An organisation’s skill level and the adoption of new tools, technologies and working methods depend highly on an organisation’s workforce’s overall culture & skills, not the peak talents. Therefore, it is crucial to emphasise people’s ability to integrate generative AI successfully into a company’s daily business. We have developed a proven three-step approach to create awareness, engage and upskill employees, gradually increase usage, and sustainably embed learning and mindset in the daily business.
However, generative AI also poses a variety of new risks in terms of AI security. With the use of generative AI, it must be ensured that regulatory and compliance requirements are adhered to, especially concerning copyright and intellectual property, ethics & responsibility, and data protection. Our best practices enable effective implementation of relevant AI governance requirements.
GenAI has the potential to improve efficiency, effectiveness, and automation in manufacturing. How can GenAI eliminate errors, facilitate faster decision-making, provide data-driven recommendations, and automate processes in the manufacturing sector? Find out why companies should start their transformation today and how they can gradually expand their use cases based on value potential and data integration effort.
Director, Data & Analytics, Operations Transformation, 鶹Ƶ Germany
Tel: +49 151 15535019
