# Enterprise AI Canvas -- Integrating Artificial Intelligence into Business

**Authors:** U. Kerzel  
**arXiv:** [2009.11190](https://arxiv.org/abs/2009.11190)  
**Date:** 2020-09-18  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2009.11190v1/

## Key points

- AI and Machine Learning have the potential to revolutionize businesses and disrupt entire industry sectors
- Identifying use-cases where AI can create value and support or automate decision-making processes is a challenge
- Organizations need to undergo a transformation to effectively integrate AI-based systems into their workforce
- Redefining roles and responsibilities, as well as providing training and support for employees, is necessary for this transformation
- Technical aspects of machine learning models must be thoroughly discussed, including data sources, constraints, and evaluating data quality and predictions
- The Enterprise AI Canvas provides a framework for bringing together Data Scientists and business experts
- The canvas consists of two parts: one focusing on the business view and organizational aspects, and the other delving into technical details of the machine learning model and its data requirements
- Integrating AI into a digital enterprise requires careful consideration of various factors
- The Enterprise AI Canvas serves as a tool to facilitate discussions between stakeholders for successful integration and implementation of AI-based systems.

## Summary

Artificial Intelligence (AI) and Machine Learning have the potential to revolutionize businesses and disrupt entire industry sectors. However, integrating algorithmic decisions into companies comes with numerous challenges. One of these challenges is identifying use-cases where AI can create value and support or automate decision-making processes. Additionally, organizations need to undergo a transformation in order to effectively integrate AI-based systems into their workforce. This transformation involves redefining roles and responsibilities, as well as providing training and support for employees to adapt to the new technologies. Furthermore, the technical aspects of the underlying machine learning models must be thoroughly discussed. This includes determining where relevant data will come from, considering any constraints that may affect the model's performance, and evaluating the quality of both the data and predictions generated by the model. To address these challenges, the Enterprise AI Canvas provides a framework for bringing together Data Scientists and business experts. The canvas consists of two parts: part one focuses on the business view and organizational aspects, while part two delves into the technical details of the machine learning model and its data requirements. In conclusion, integrating AI into a digital enterprise requires careful consideration of various factors. The Enterprise AI Canvas serves as a tool to facilitate discussions between different stakeholders, enabling them to define all relevant aspects necessary for successful integration and implementation of AI-based systems.