AI-based software development relies on effective change management

The adoption of AI-powered software development has created a monumental shift in the way today’s companies drive innovation. In a short period of time, progressive enterprises around the world have realized that artificial intelligence is not only here to stay, but has the power to completely transform their development processes for the better.

In fact, recent research shows that AI pair programming tools are already helping developers code up to 55% faster. The advantages don’t end there. Nearly three-quarters (74%) of developers in the same study said they felt less frustrated when coding with AI tools and were able to focus on more fulfilling work. This enables them to reduce hassle and increase productivity – so much so that it is estimated that the productivity benefits provided by AI developer tools could increase global GDP by over $1.5 trillion by 2030.

While it’s now an established fact that effective AI integration can quickly lead to faster development cycles and keep developers moving, it’s worth remembering that integrating new tools or procedures into your business environment often requires change management. Despite the pace of AI development and its transformative impact on enterprises, the reality is that change management and a focus on implementation are needed to truly realize the benefits.

The use of AI coding tools may be virtually ubiquitous in the developer community – a recent study found that 92% of developers now use them both on and off the job – but the reality is that there is still much work to be done to ensure enterprises positioned to take advantage of the benefits of innovation that AI-based software can provide.

The bottom line is that while enterprises are increasingly accepting the growing need to incorporate AI tools into the development process, they still face obstacles in designing the optimal conditions for developers to thrive in the AI era.

Initially, these obstacles focused on a lack of understanding of technology and awareness of the appropriate tools for each situation. However, we are in a new phase of understanding and widespread acceptance of the role that artificial intelligence can play in accelerating the development process and accelerating innovation. Awareness is no longer a problem.

Instead, a new challenge has come to the fore: whether companies are sufficiently prepared to properly integrate AI coding tools and manage such a monumental change in the software development process and the associated developer experience.

Chris Reddington

Senior Developer Support Manager at GitHub.

AI accelerates development processes, not replaces them

Such is the transformative potential of AI that any enterprise leader could be forgiven for assuming that AI-based software development will effectively replace existing software development processes. However, this is not the case. Instead, AI coding tools accelerate existing systems rather than replacing them. AI tools understand the context of the project they are working on, which means they can help identify bugs, generate relevant code snippets, help write tests, and even provide documentation, all of which can save significant amounts of development time. Enterprise integration should instead focus on onboarding and deployment methods that enable development teams to realize benefits as quickly as possible with minimal disruption.

However, it is too simplistic to assume that adopting AI coding is simply a matter of tools. Buying access to the latest technologies and providing them to teams will not foster a positive culture of AI-based software development. Tools alone cannot create a progressive culture around their effective use and understanding of their impact.

This is partly because by investing in AI coding tools, enterprises not only buy productivity, but also provide a better experience for developers. “Productivity” is a restrictive term, and the impact of AI tools should never be judged by the sheer amount of code developers can produce. Similarly, too often productivity is synonymous with saving time in the enterprise context. This isn’t an unfair association, but it doesn’t tell the whole story. Saving time doesn’t stop there. Instead, enterprises should consider what happy and fulfilled developers can do in their free time by integrating AI into their workflows.

Leveraging AI-powered software development

By implementing AI coding tools, companies go beyond prioritizing productivity and go deeper by transforming developer satisfaction. Companies need to understand that they will only unlock AI coding capabilities if they implement the tools as part of a broader strategy of prioritizing supporting developers so they can focus on what’s important. Enabling them to spend less of their day on repetitive tasks and more of their day solving problems and tackling challenges as a whole can only accelerate innovation and ultimately increase developer satisfaction.

Increasing developer satisfaction levels can also help enterprises attract and retain top talent. Access to the latest and greatest tools has a tangible impact on how developers think about their work. For example, research shows that 70% of developers believe that using AI coding tools will give them an advantage at work, with the greatest benefit being upskilling, followed by increased productivity. In my experience, developers tend to have a hunger for knowledge and training, as evidenced by the findings that developers rank learning new skills (43%) and receiving feedback from end users (39%) as the two main factors that have a positive impact on their working day. Providing them with the best possible tools to develop and learn can help increase talent acquisition and retention.

The use of AI-based software development is more of a cultural change than a technological change. However, influencing this change and creating an organizational environment where AI-powered software can thrive doesn’t have to be overly complicated. As with any new technology, success begins with building a solid foundation, driven from the top and supported by every level of the enterprise.

Leaders must create and adopt a long-term strategy that elevates the development process and refines it over time to deliver the desired results. A change like AI coding requires leaders to create forums where teams can share best practices and learn from each other. For example, creating internal communities or centers of excellence is an effective way to accelerate change, allowing teams to share success stories or learning moments if they didn’t initially get the response they wanted. This enables development teams to share knowledge, for example on how to adapt prompts to work with AI tools to achieve the desired result.

Artificial Intelligence is the definition of a disruptive technology, so organizations need to change their mindset beyond simply equipping and hoping for the best. With top-down support, internal support networks within developer communities, and a progressive vision of how AI will change the way software is developed at every stage, leaders and developers are much better equipped to leverage the benefits and ensure they don’t miss out on the biggest opportunity for innovation. business in living memory.

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