According to our research, forward-thinking firms are driving the adoption of emerging tech.
Specifically, 87 per cent of business and technology professionals who have some knowledge of emerging technologies are experimenting with, piloting or implementing artificial intelligence.
The third most common use case for generative AI is software development.
Many are enthusiastic about the chances of writing code in natural language or using an autocompletion editor, or pair programmer, that helps directly write code quickly.
Financial services organisations like ANZ and Westpac have run internal experiments to prove that software coding can increase productivity between 42 per cent and 45 per cent.
However, there is much more that GenAI, as well as AI and machine learning, can collectively do in the world of software development and maintenance.
Forrester has named the area of AI-enabled assistants for software development Turing Bots, in honour of the British AI scientist Alan Turing. We consider Turing Bots to be a new exponential technology that will have short and long-term positive impacts in the financial services industry.
Turing Bots speed up the software development lifecycle
Turing Bots can support all phases of the software development lifecycle (SDLC), from the initial planning, analysis, and requirements phases, to design, coding, testing and delivery. There is a TuringBot type for every phase of the lifecycle.
Indeed, a rich eco-system of tools built by vendors is developing fast in the market. Well-known software and platform vendors like GitHub, Atlassian, Google, and AWS, together with start-ups and smaller players like Applitools, Coedium, Tabnine, as well as the well-known OpenAI, are all racing to build and infuse Turing Bots in current and future development tools.
More advanced Turing Bot approaches are using open-source large language models (LLMs) specialised in software as data, including Codex, Code Llama, and StarCoder. The technology is getting there, but are we ready for it? No.
As technology evolves faster and faster, we humans and enterprises struggle to keep up and change the way we work. Considering enterprise resistance to change, we believe that in less than five years, this technology will totally disrupt the way software, applications and products are built and maintained.
What about legacy?
When discussing legacy technology, let’s use ATM machines as an example. Interestingly, 95 per cent of ATM card swipes to withdraw cash run on old Cobol programmes. Cobol stands for common business oriented language, and is a computer programming language that has primarily been used in business, finance, and administrative systems since 2002.
It is estimated that more than 220bn lines of Cobol code are still used in production around the world.
Legacy applications process, run and manage customers’ policies for insurance products, and hold much of the data that is crucial in keeping business operations up and running. That data is also crucial for modern applications, but access to it through legacy applications is not easy.
