Yes, AI is powerful, but you still need experts

I hate to write yet another blog about AI, but I think as we are all acclimatising and adjusting to the recent advancements we are learning more and more about the upsides, downsides and different dynamics to this new normal.

At NuForm we are excited about how AI can actually help our customers, and our service to those customers. We don’t look at it as a threat.

We are optimising internally with extensive R and D, working with several partners to leverage tools that can make us more efficient, and working proactively with our customers to ensure that we are doing all we can to maximise the benefits for them. The key thing is that we are doing this with context and looking to solve real business problems.

The past few months have taught me a few things, these may drastically change in the coming months, but at least for now - these are some of my observations -

- Like a lot of new shiny tech, and buzzy things, new tech is only as good as the people using it. Yes, the level of automation around things like design and dev, will have a huge impact and change the way we work. It will make it far quicker for people with less skill to do a lot really quickly and no question we will take advantage of that. Doing things faster ultimately means a lower cost and less time for our customers which is only a good thing. However, like we have seen with other advancements in the past you still need a good driver behind the wheel to really execute to the level required. A good example is low code development tools, they are great depending on what you want to do. Eventually you will reach a point where the level of complexity means you need a different approach. I look at AI in a similar way. Instructing for example AI to design or code something will work and create massive efficiencies, but I believe you will still need experts behind it, to really maximise the benefits in complex business critical environments.

- There are just some things that AI cant do. For example, how can AI do onsite research? How can AI really understand the business drivers being a digital product and then translate it in to a service? How can AI add empathy to the design process? I still feel that there will just be so many nuances in so many part of the development cycle where AI cannot replace skilled humans.

With that said - where do I think for now it will make the most gains?

- Prototyping - user story creation and this being translated in to wireframes and designs.
- Code generation - boilerplate code generation will hugely benefit.
- Testing and Bug fixing - faster, more reliable services to ensure mistakes don’t happen.
- Data analysis and Insights - faster more efficient ways to analyse and leverage large amounts of data.

If you want to learn more about how we using AI in our processes, give us a shout.