In this data-driven century, we face new cutting-edge technology that is rapidly changing customer behavior such as the rise in e-commerce, contactless payment, and increased concerns about privacy. As a result, entrepreneurs need to find the best way to transform all business models, including IT landscapes whilst maintaining compliance with new regulations concerning data privacy. This has led many corporations to start initiatives to collect as much data as possible to understand their customer needs.
Information has now become a valuable asset. Innovation projects, often related to data science or Artificial Intelligence (AI), require many types of structured and unstructured data in order to gather meaningful insights that can be utilized to shape business strategies. However, gathering and understanding this data can be challenging due its unpredictable outcomes and requires enough time to validate the results in the real-world context.
There are many benefits of implementing data science and AI technology in various industries, but it requires a thorough understanding of how to manage an AI project end to end, from requirements gathering to implementation. Otherwise, time and resources spent could lead to ineffective outcomes.
This session will focus on guiding project managers on how they should prepare when they start a Data or AI project. What should be considered at the start of an AI project? What are the potential risks in gathering data? How can the project manager prepare their team to successfully execute?
Our speakers will shares details derived from data science and AI project management, with specific use cases. They will also explain the techniques project managers can use to successfully execute these types of projects.