The rise of AI-informed testing – and what this means for the future of your business

Over the last five years, artificial intelligence (AI) has moved from being a niche interest into something found everywhere you look within the IT landscape. The pace of change and innovation has been dramatic and it’s a rare day when there isn’t a news story about what AI can do – or some new insight or innovation that has been supported by machine learning. And it’s no surprise that market leaders are paying close attention to this. For example, Capgemini’s World Quality Report (2020-21) found that 88% of organisations surveyed wanted to use AI in their quality assurance (QA) work.

Across tech stacks and tool chains, we see AI systems becoming more common. On one hand, this is being driven by the pace of change globally as businesses and organisations assess and redesign themselves, drawing on the lessons learned over the past few years. While on the other hand, there’s also the need to be competitive – if your rival is doing it and getting to market faster or with fewer defects, can you afford not to do the same?

Informing decisions with AI

The rapid rise of AI is also being driven by the need to control the process of change and the need to be able to make informed decisions amongst the deluge of data that sweeps through complex IT estates every day. The times when any one person could look at all stages of the application development and maintenance (ADM) cycle and see what was happening are gone. To make sense of all the data, we need tools to help us cut through the noise and enable us to focus on making these informed decisions.  
 
Tools such as these are already becoming mainstream – with the ability to manage the entire process starting with the business need and then shifting to supporting agile ways of working and building, assuring, testing, and delivering change quickly and securely. Smart systems, expert systems, and AI are brought together in best-in-class reporting tools, visualising the complex information in ways that humans can easily process and base decisions on.

In this respect, testing is using new smart tools as it moves away from being a separate stage on its own – becoming much more integrated within the entire delivery process. Working with development teams, testing can help build early checks for security and performance during code check ins, through to integrating the QA culture across all teams to bring together a quality-engineering-focused, mature, agile DevOps team.

Achieving continuous quality monitoring through Capgemini’s Quality Engineering with ADMnext

Smart monitoring of the process and live operations enable continuous quality monitoring and identification of defects or emerging issues before they become serious. This is where Capgemini’s Quality Engineering with ADMnext comes in. In developing this offering, we spent a lot of time making sure that monitoring and control are baked in from the start – and AI is playing a big role here. AI is crucial for supporting our decision making by helping us make sense of the volumes of data generated every day – enabling us to be in control and well-informed.

This helps beyond some of the traditional IT functions. Because we have the data and can track decisions, we can be more accountable for what we do and why. In turn, this supports corporate risk management. How? Because any system in which you can show you are in control of – with the right information to make the correct decisions – becomes easier to manage in terms of risk across the organisation. This is something that more and more organisations are recognising and it’s helping to drive the adoption of AI tools further.

If you can use intelligent analytics to manage both risk and change effectively, you have an IT bedrock that is resilient and helps the business be responsive to a rapidly changing world.

Down the line, as the processes are embedded into the organisation and we are able to test defects out of the system before they happen, zero-defect development and zero-touch testing will become more common. Firstly, however, they need to be built on the foundations of AI being deployed right now. 
 
To learn more about what Capgemini’s Quality Engineering with ADMnext can do for your business, visit us here.

 

Author