The use of low-code/no-code platforms has seen significant uptick in the past couple of years. These tools are increasingly being used to develop and train AI/ML models and though they help in speeding up the process, there are significant downsides that enterprises need to be aware of. In the first of this two part series, we are joined by Brad Shimmin and Alex Harrowell as we seek to understand the platform and infrastructure implications of relying on low-code/no-code platforms for AI implementations.