Reading the latest news on AI development, one could easily believe that AI is a technological panacea. At Advanced, we recognise the need to implement this exciting new technology in a responsible way, responding to the needs of our customers. We are still in the early days of AI, with new understanding and new possibilities arising every day. This is why we are taking steps to experiment, explore and refine, learning what AI is capable of, and what value we can bring to our customers.
Problem to solution
When taking a journey of exploration, it’s important to define the goal we are looking for. As we study the art of the possible with GenAI, we must do so through a carefully curated lens. At Advanced our starting point is always to ask, “What is the problem that our customer has?”. By starting with the customer, we can truly understand what will make work better for them.
Our approach, therefore, is one of research and careful experimentation. We are exploring what we can achieve through creative minds and emerging technologies like AI. We are learning where to use AI to add value to the software that provide our customers.
If we want to maintain our success, and if AI is to be a part of that success, we have to think seriously about the difference that it can make to our practices. As a revolutionary new technology, it’s easy to try and turn AI’s hand to every problem, but sustainable success requires a measured approach. The starting point has been looking at how AI is developed and what it is designed to achieve.
We’ve talked about AI and the sub-set Machine Learning and over the last year we’ve seen amazing advancements in the space: ChatGPT, MidJourney, Firefly to name a few. These solutions have shown us what’s possible so far in chatbots, text generation and text-to-image creation.
We are understanding how AI can work as a copilot. This doesn’t mean taking over responsibilities but responding to the needs of people in the workplace and automating repetitive tasks. When we need rapid responses that aren’t reliant on human expertise and insight, then AI can come into its own. This is a basis for the experiments we are currently carrying out, testing where these kinds of capabilities can be applied in the world of work.
Predicting the trajectory of rapidly evolving technology is a fool’s game. We’ve seen that time and time again in the poorly aged articles of yesteryear. What we can do, is examine where we are now and use that to support realistic aspirations; we can say what we hope to achieve with AI.
At Advanced, we are customer inspired. We want to provide solutions that our customers can rely on for success, making their processes simpler and more user-friendly. It’s important to us to respond to our customers’ needs, and use our understanding of their sector constructively.
In recent months, we have released both our Annual Business Trends Report and our Sector Trends Reports. Through these, we have seen both the excitement and trepidation expressed across the world of work. We have seen both ends of the scale, with strong plans to adopt AI in the Legal sector, contrasted with more worried attitudes in Education.
When 90% of Legal firms are already keen to use AI in their practice, it’s important that we listen to their needs and provide the solutions that can solve their problems. And when a fifth of manufacturers are already using AI, we need to explore how we can integrate it into simplified and straightforward workflows. On the other hand, we need to be mindful and understanding of sectors like Education which are more concerned.
When education providers are concerned about machine learning undercutting the need for student learning, we need to work with them, not against them. We need to make the effort to experiment with how AI can still be a useful tool for them, so they don’t miss out on its capabilities. It’s only through testing and exploring that we can find the solutions that will make a difference for educators.
We’re always learning more about AI, and we want you to join us on this exciting journey. Learn more about the journey of Machine Learning in our blog here. Or explore the field of Natural Language Processing that powers chatbots here. You can also look out for new content discovering new insights about AI on our blog here.