WORKSHOP - How to Kickstart Your Enterprise AI Project
This interactive workshop will give you the knowledge and skill-set needed to validate and kickstart AI projects within your business.
Challenges in kickstarting an enterprise AI project
Many corporates understand how important it is to employ AI technologies into their businesses. However, many decision-makers have trouble knowing where to start. There are many reasons enterprises find it difficult to kickstart AI projects.
Lack of visibility into what AI can actually do
Misconception that all stakeholders need a deep understanding of AI technologies to initiate an AI project
Idea that the AI models need to be perfect from the get-go to achieve operational success
Misconception that there needs to be a large, innovative picture for the use of AI throughout the entire enterprise
Understand the biggest misconceptions about AI and how these misconceptions are holding you back from adopting deep tech into your enterprise. Learn why AI models don't need to be perfect for success, why a traditional waterfall project management style is not effective for AI projects, and why you don't need to have a deep understanding of AI technologies to deploy a successful project.
Understand what AI technologies can and cannot do, and how to determine if a business case can be made for these technologies. Learn from four examples of successful AI business designs and the four primary domains that need to be considered: Cost Reduction, Risk Prediction, Revenue Increase, and UX Enhancement. Learners will also take part in a Virtual Problem Setting brainstorm activitiy with peers.
Learn how to define what type of data will help your team reach their goals and how to properly manage this data to ensure it's used both effectively and efficiently by creating a Data Strategy Diagram. Learners will also learn from an in-depth case study on how one company created a data strategy that led to the successful deployment of their AI project.
Learn what to look for and what to be wary of when outsourcing AI model-production, and best practices for working in tandem with an AI vendor to ensure efficiency and transparency throughout the duration of your AI project timeline.