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The Case for Automation in Software Development

Robotic Process Automation (RPA) has made great strides in the enterprise world over the past few years. According to Gartner’s most recent study on the topic, the RPA software market grew 63% in 2018 alone and was expected to reach global revenues of $1.3 billion by the end of last year. The rapid growth of automation is not only prompting significant media buzz around its promising capabilities, but also raising concerns about its long-term impact on overall employment.

Robotic Process Automation (RPA) has made great strides in the enterprise world over the past few years. According to Gartner’s most recent study on the topic,  90% of robotic process automation (RPA) vendors will offer generative-AI-assisted automation by 2025. The rapid growth of automation (and here the case of automation in software development) is not only prompting significant media buzz around its promising capabilities, but also raising concerns about its long-term impact on overall employment.


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AI in the workplace: productivity gains and fears of trust

Surely, companies are increasingly relying on virtual employees — from chatbots to AI-powered personal assistants — to increase productivity and lessen the burden imposed on staff by time-consuming and repetitive tasks better left to machine learning algorithms. However, as it tends to be the case with artificial intelligence, there exists a generalised mistrust of synthetic agents and their overblown potential to replace humans.

As we have mentioned in the past, we should look at new technological developments from a more practical perspective rather than from a position of worry. Automation and artificial intelligence are tools that we can leverage to enhance the quality and speed of our work.

Embedded in the DevOps DNA

This is particularly true in a discipline like software engineering, which requires the full power of human ingenuity while also encompassing a series of tasks that burn through a lot of time and resources. Not surprisingly, automation is deeply ingrained within agile development methodologies and represents a big part of the day-to-day in DevOps.

In their effort to optimise software production pipelines, DevOps engineers take advantage of various automation tools that allow for faster, more robust development – although how much automation should exactly be involved in the process remains a cause of debate.

In any case, benefits of automation in software development are too great to ignore: speed, more resources and increased quality and security.   

Increased resource availability

Firstly, the continuous improvement and delivery (CI/CD) paradigm is an intensive process that involves many steps and requires increased collaboration between teams. Accordingly, automation has a great role to play to help with code testing, the updating of repositories and the integration of various software components.

Moreover, automation offers a possible solution for understaffed teams of developers. Skill and personnel shortages are a prevailing issue for the industry. Development teams can greatly benefit from eager bots and other automation tools tackling all those lower-level, time-consuming tasks.                                

Maintaining quality and app security together with speed

Given today’s accelerated and competitive product lifecycle and the need for companies to adapt to ever-changing markets, speed is key in the delivery of software solutions. However, it is hard to achieve optimum levels of speeds while preserving code integrity and ensuring security across your universe of solutions.  

Automation not only helps ensure the production of robust and quality code with fewer resources — it also leads to greater security standards by allowing developers to continuously monitor for vulnerabilities while maintaining the focus on higher-level aspects of software creation.

In fact, a recent report by Ponemon Institute and IBM revealed that organizations without security automation experienced in 2019 breach costs that were 95% higher than those companies with fully-deployed automation ($5.16 million average total cost of a breach without automation vs. $2.65 million for fully-deployed automation).


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Conclusion

This data underscores the ongoing significance of security automation in the contemporary cybersecurity landscape. As organizations grapple with evolving cyber threats and vulnerabilities, the adoption of automated security measures emerges as a key strategy for not only enhancing overall cybersecurity posture but also for minimizing the financial impact associated with data breaches. Therefore, as we progress into 2023, these insights serve as a compelling reminder for businesses to prioritize and invest in advanced security automation solutions to safeguard their digital assets and maintain resilience in the face of evolving cyber risks.

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