Artificial Intelligence rules the news: technology developing at such a rapid pace we’ve never experienced before. And as a bonus, that technology has a very customer-friendly entry point; it’s actually quite amazing that anyone can use AI without the intervention of a data scientist. What does this mean for developers and IT professionals?
The rise of ChatGPT – never before has a new technology had millions of users within a week – is unprecedented. From students to CEOs, try finding someone who isn’t eager to find out the possibilities. Now there’s a platform where developers and users can immediately start experimenting. The next big question: how can we create value with AI?
Existing paradigms
Translating AI to the Gartner hype cycle, AI is now riding the crest of the wave; everything seems fantastic, audiences are running with it. But if we follow the hype cycle – and we will -, setbacks will follow. Roughly speaking, the current form of AI is only six months old.
So the public and also developers are adopting AI at lightning speed, but this is happening from existing paradigms. Users are now mainly looking for ways to accelerate current reality. Real productivity improvement, however, will only be achieved when we can let go of our way of thinking and start thinking differently about how we work, how we deal with customers and how we organize the chain. Then the real acceleration will follow.
To make the first steps, co-pilots are now being developed; support programs in the AI field that help users make certain tasks easier. Think of a co-pilot to easily create presentations, or functions in Word that make drafting contracts much simpler.
Microsoft, for example, is also developing co-pilots for Power BI, so that people who don’t understand business intelligence can simply ask questions to the system. These tools are coming, and developers can also create them themselves.
Ethics is a priority
The deployment of AI, of course, is already generating plenty of discussion. The discussion about data follows next. Data governance and security obviously need to be in order before you turn people loose on deep AI systems. For example, Microsoft is developing Fabric, a new platform that manages all data in one place. That way, data is better protected and easier to access,
There has also been a huge acceleration in the cloud. This has been going on for years, of course, but leaps and bounds are now being made. Developers are moving away from separate products and are now offering platforms. It makes it easier for people to collaborate and access all the data sources in the company.
This makes work easier, without paying attention to every bit or byte. Workers don’t want to think about which database that one piece of data is in, or which api is available. We’re moving toward one integrated whole, which allows us to get results faster.
Discussions about Ai are almost always about ethics. So shouldn’t you hire developers with ethics in the portfolio? The answer is yes. You have to be able to make clear how you handle data; how do you make sure your models are not biased? How do you make sure people are not biased? Ethics have to be a priority. You have to be able to explain the reasons why someone gets a mortgage from the bank and someone else doesn’t.
Digital sameness lurks
Another issue that companies need to watch out for is distinctiveness. Are your people able to use technology better and smarter than the competition? That’s where your competitive edge lies. After all, everyone has access to the same technology – that’s where the danger of digital sameness arises; everyone develops the same kind of solutions, thus creating uniformity in the market.
How are you going to develop that distinctiveness? This revolution allows you to ask targeted questions. If you learn to ask the questions just a little differently and better, you will be ahead. That means adjusting your natural language. And that’s tough, because that’s how we’ve communicated for thousands of years. Prompting, the technique used to ask AI systems the right questions, is therefore on the rise. Any developer who wants to use AI for work will have to learn these skills.
It is a glimpse into the future, but it’s the very near future. Developments are moving fast, probably much faster than we think now. We will continue to keep you informed!
