My name is Lynn and I am a final year student, majoring in Finance. Recently I received sponsorship from QUT Business school to attend the exciting ‘Something Digital’ event hosted at Brisbane Convention and Exhibition Centre on 24 October. I was looking forward to hearing stories and opinions from people in the new emerging industry about how artificial intelligence will change future business models in its way. The event was really amazing combined with many different areas including human innovation, digital marketing, and data science, etc. Interesting and insightful speeches were given by experts in the industry. As a finance student, I am more interested in the masterclass in a green stage which is ‘five tips for choosing your first organizational AI project.’ The workshop really attracts me, not only inspiring but also insightful. The company aims to provide the most precise data and analytics in the market for improving business efficiencies and making insightful decisions with historical, current, and residual values.
First, Thuy identified two main reasons of organizations fail to complete an AI project based on their past experience: either the chosen AI project is too broad and generic or unable to capture the why for them. The aim of taking AI project is to demonstrate to the stakeholder that you are able to get to point A with current data, but with more data, you can get to point B, C, etc., which then unlocks the next level of value.
Another key idea from Blackbook.ai is separating noises from both information (qualitative) and data (quantitative) side which may subjectively and generalised in the decision making the process. This is critical for them to provide precise and accurate predictions and advice to fuel business transitions based on real-time raw data. In a time era when the internet and technology developed is so well established, it is not hard in regards to reading and collecting news, the task remained would identify the key drivers for your problem based on analysing the real trend from real data, which again reveals the importance of quantitative analysis.
He also pointed out the fact that the artificial intelligence technology is not magic, it’s still based on data and math, combined with historical trend analyzing from the past and mathematical algorithm used in predicting modeling. At the end of the day, it’s still about solving problems people are facing. The masterclass is designed to be interactive, people from different industries all facing different problems in daily work ranging from marketing channels, financial models optimisations, etc. I was so amazed about how this technology could be applied in the various modern business environment which is pretty advanced. One question put up by a group was how could potential solution provided by AI to solve and improve delivery efficiency for a company. The answer given by the CEO was to find out your variability in raw materials stock and identify which are the ones always being in stock, improve the wastage, define the characteristics and driver for your case. The more accurate data you have based on past outcomes, the more robust and explainable for your model to capture the ‘why’ for your puzzles.
Moral and ethical considerations that the development of technology has brought were discussed at the end of the conference, which is unavoidable in my opinion. This open-ended question triggered more interesting discussions and ideas for people at the after-party and led to a very meaningful ending for the conference.