How Generative AI Will Transform Software Development Workflows

Artificial intelligence is advancing at an exponential rate. Many leaders are scrambling to embrace this software revolution by integrating with AI-enabled plug-ins or incorporating AI-powered technology into their own enterprise platforms. 

Some leaders are concerned about the potentially significant impact of AI on human roles and have signed an open letter calling for a pause on the development of generative AI. One thing is clear: We are in the midst of a pivotal shift in software development and workflows across all industries. 

For developers, the emergence of generative AI’s language learning model will revolutionize code creation and become one of the most important tools for developers. Below are some of the ways that generative AI will benefit developers, improve security measures and lead to digital transformation. 

How Generative AI Will Benefit Developers 

As AI becomes more integrated into development tools and workflows, it will increase development speed, efficiency, creativity and accuracy. AI will become second-nature to developers and their processes throughout the software development life cycle (SDLC), as it continues to become embedded and incorporated within the tools and workflows that developers use daily. Additionally, AI can automate tasks, playing a valuable role in addressing the ongoing challenges of talent shortages in organizations and quality control. 

Code production and code editing are two areas in which AI automation has truly benefited developers. Automatically generated code from AI is much like some of the writing we have seen from ChatGPT. It’s useful, speedily produced and requires human oversight to check the end results. Still, AI produced code cuts down on development time and helps reduce the potential for human error. AI assistance in code editing programs increases the speed with which we find and correct errors, a true asset in shortening the software development life cycle.

Due to recent bouts of tech layoffs and general economic uncertainty in the tech world, many development teams are facing significant pressure. What used to be handled by large teams in the past has now been condensed to a few highly skilled workers who are responsible for managing the workload of the entire team. This can sometimes result in tasks being deprioritized and developer burnout as engineers work extra hours to compensate for the reduced team size. Whether it’s editing code or automating administrative tasks such as testing, monitoring and checking for updates, AI can alleviate some of that pressure and free developers up to focus on more creative tasks.

AI tools that automate tasks will also help smaller developer teams scale their operations and compete with enterprises. Streamlining repetitive tasks will free their developers up to focus on more unique and differentiating solutions. 

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How Generative AI Will Improve Cybersecurity Measures

Cybersecurity AI is an area that will ultimately strengthen the internal processes within organizations. Incorporating security measures into the software development life-cycle (SDLC) is a crucial part of software development. However, many developers and cybersecurity professionals often struggle to shift left and focus on security early in the process. 

Once AI has been trained properly on security measures, it can help companies ensure compliance as the code is being written, resulting in stronger applications from the outset. As security becomes more integrated within the SDLC, developers will have more time to focus on the creative aspects of app ideation. 

Additionally, talent shortages can lead to an overwhelming workload and increase the potential for exposing vulnerabilities, which could result in a security breach. Generative AI and automation provide developers with confidence that their internal security systems are consistently being monitored for suspicious activity. 

In particular, generative AI can be used to create customized security models. These models can be trained on large data sets of historical security data to identify patterns and anomalies that may be indicative of a potential threat. Automation can then be used to implement these models in real-time, allowing for rapid detection and response to security threats. With this in place, vulnerability management won’t fall through the cracks. 

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4 Ways Generative AI Will Shape Software Development

DevOps will continue to evolve along with AI by becoming more mature and integrated into existing tools. For example, developers currently utilize IntelliCode, which is an AI-powered tool that recommends auto-completions during programming based on project analysis. 

Below are some more software development changes generative AI will create: 

1. Increase the Use of Low-Code Solutions. 

By taking advantage of mature software development kits (SDKs) and libraries like LEADTOOLS, developers and organizations will be able to integrate the eyes of AI into their applications. Other low-code tools and platforms such as Microsoft Power Apps and Google App Maker will also benefit from AI. 

Even less experienced developers will be able to quickly and efficiently build products and solutions with very powerful features, without requiring the extensive coding expertise and experience that would be needed otherwise. Additionally, this eliminates the need to hire more developers to maintain their products since that work can be offloaded to the SDK partner. 

2. Integrated AI Will STreamline Cybersecurity Efforts

The rise of remote work and digital transformation exposes more security vulnerabilities, as nefarious bad actors are also using generative AI to write malicious code. AI could be used to monitor network traffic and identify suspicious patterns or behaviors that could indicate a security breach. Most security companies are already working on AI and machine learning solutions to detect and prevent these threats.

3. Accelerate Digital Transformations and Improve Remote Work 

COVID-19 forced many organizations to rapidly adopt digital technologies and accelerate their capabilities by five-to-10 years. This acceleration will continue as more developers embrace the remote or hybrid lifestyle, and businesses will be required to adapt and stay competitive in the software market. 

Automating tedious and repetitive tasks will free up employees working remotely to focus on more complex and high-value work. Doing so will improve overall efficiency and productivity. AI-powered virtual assistants that manage schedules and prioritize tasks may also enhance the remote work experience.

4. AI Tools Will Become More Effective Through Developer Use

As AI solutions become more integrated into everyday processes and workflows, users will accelerate the growth of the algorithms with more data and feedback. Data sets will expand with consistent feedback and contribute to the maturity of this technology. Even the most incremental updates will seem monumental as this technology continues to evolve. 

As developers discover the benefits of incorporating generative AI into their workflows, their roles will likely shift. New technologies like this should be embraced, rather than feared. 

While every new technology needs regulation and refinement, AI is the next logical step in software development. From smaller companies being able to scale their products and compete with larger enterprises to the average developer streamlining their workflows, the opportunities for growth with AI are exponential. AI is simply another powerful tool in the developer’s toolbox and will increasingly become integrated into the core foundations of software development.