AI in Professional Fields: Where Are We Currently At? And how is the Landscape Changing?

An interesting quote in this article: “OpenAI have launched a simple tool for creating ChatGPT-powered apps – similar to the initial battle for supremacy between iOS and Android.” 

AI is becoming more prominent in all professional fields. Bill Nelson, head of NASA, believes that AI is the new space race and that there are useful lessons to be learned by comparing where we are now with the competition between the US and Russia for supremacy in space in the 1960s that led to the moon landings. He cites the international cooperation in legal concerns that led to the UN Outer Space Treaty of 1967.  

When I wrote my first attempt at an AI governance framework a few weeks ago, I was conscious that we are in unchartered territory, and many of the norms for how AI will be applied do not exist yet.  

The potential fight for supremacy between OpenAI (the lab that developed ChatGPT) and Microsoft, Meta, Alphabet and new companies just getting started, including Builder.AI with their no-code app builder offering, will be a choice. 

AI in Professional Fields – Change and Transformation   

As AI changes, becomes more advanced and grows, it is being used more and more in different professional fields.   

In the future, there will be many apps and different approaches that use AI in professional fields.  

I can’t speak for everyone, but; 

• As a change professional, the use of AI in various roles makes me think that many of the change initiatives I will be involved in over the next few years will include the creation of new ways of working using benefits from these apps. 
• As a transformation professional, I think I will have to be in a position to help organisations decide which way to jump in terms of their AI approach. 

How is AI changing the way you work? Is it something you are being involved in using regularly? Do you have a prediction for how your job role will change?  

Staying Current with the Latest AI Ideas 

Another thing we can all guarantee is that staying current with the latest innovations in the AI world will be essential. For example, how many of these latest ideas are you aware of and have an opinion about (to be honest, I didn’t tick many, which inspires me to learn more): 

• Benefits and constraints of traditional AI versus generative AI – for example, recognising that traditional AI is good at extracting data and removing data entry from existing processes, whilst generative AI can use data to create answers for customers, including reports and presentations. 
• No-code development – puts the power of how to use AI into the hands-on customers as well as our in-house tech teams. 
• Data collection methods – understanding all the different approaches and having a view on which is best for your purpose is important. Considerations about what data to use and where to source it shifts from an IT decision to a business decision. Are you prepared to decide between reinforcement learning from human feedback (RLHF) from off-the-shelf data sets? 
• Traceability of data – connected to data collection, we now have to create processes that ensure we know and can explain to others where data has originated. This is not a new requirement, but the speed of AI development means that the importance of traceability is greater than ever. 
• Vector databases – stores data as a mathematical representation, which changes the type of data that can be retrieved from a database from an exact record to the “most useful/relevant” answer 

I hope this gives you a few ideas about AI in professional fields, and for more information, don’t forget to revisit this page every week for more thoughts.