As the use of embedded AI leads to a reduction in costs by early detection of possible failure risks in products, introduces innovative features and simplifies processes in user interaction, the technology must be under consideration in the future for a new product generation for the purpose of new business models or competition-relevant USPs.
Often, it is the lack of competencies within the company or the scarcely available resources for technology implementation that stand out as central obstacles to the rollout of technologies such as embedded AI. However, this starts with product developers or managers lacking guidance and experience on the technology opportunities and potential, as well as the product development cycle with embedded AI.
Therefore, we have created a guide for all product managers, R&D managers and interested parties to help identify the potential of AI for your product. It should help to identify which embedded AI technology can provide which added value for you:
The AITAD team will be happy to support you in the further development, conceptual design and implementation. Simply use our contact form for this purpose.
1: IDG 2019, on-premise & IDG study 2020 "Machine Learning".