AI in Software Development: Embracing Innovation While Preserving the Human Touch

It is no secret that AI is changing the game in every industry. Within the film industry, there is debate about using AI to write scripts, render actors, and more. Within the education system, there is turmoil over students using tools like ChatGPT to write essays or complete homework assignments.

AI is no longer science fiction; usable AI has arrived, and we are in a golden period when the industry is embracing and adapting various AI tools and processes. Gartner predicts that by 2025, the market for artificial intelligence (AI) software will reach almost $134.8 billion.

Within the tech space, the recent announcements about Devin AI and Microsoft's AutoDev have triggered more debate over what generative AI means for the future of programmers and coding. Some in the industry think AI could replace programmers, making coding so accessible that we no longer need to prioritize coding skills. 

While it is true that AI will revolutionize the way we code, as it will with many other skills, it is essential to evaluate how skilled programmers who have taken the time to learn the nuances of coding, considering the oversight and intricacies that come with that knowledge, can utilize AI to enhance rather than replace them.

It is important to note that generative AI is in the early stages of its lifecycle; it will only get more sophisticated as time goes on, and our relationship with it will continue to evolve as these newer innovations develop. 

In early 2023, ConcertIDC conducted a SWOT analysis. We sought feedback from every part of the company, from board members to QA engineers to senior tech leads. Every analysis listed Al as a potential threat to our company. 

As we have analyzed how we deal with this threat, adaptability was another strength mentioned in every survey. Viewing AI as a threat, especially as it relates to software development, is incredibly limiting. ConcertIDC's SWOT analysis emphasized that software developers must adapt. A threat is only a threat if you refuse to confront it. 

Embracing AI and all it can offer our customers and employees is crucial to moving forward. Finding ways to integrate AI into your everyday practices enables you to learn it and utilize it with skill and efficiency. 

At ConcertIDC, we have an AI governance Team and an AI strategy Team. Together, these teams are responsible for knowing the AI landscape, the best tools available, and the safety level of those tools for our customers. We are committed to reviewing the AI landscape on every project with every client and using the AI tools that are available. With recent advancements in the industry, concerns about AI technology's ethical and responsible use have also begun to surface. 

What once was a threat is now a strength and an opportunity. Utilizing the tools available to navigate the nuances of AI concerns like privacy, emotional capability, scale, etc., is imperative in maneuvering through the tech landscape seamlessly. 

AI tools are abundant from Microsoft, AWS, and trusted open-source tools.

We have trained AI Cloud engineers (for both Azure and AWS) skilled at building scenario-specific or Applied AI Services for various business use cases. We also have engineers specializing in cognitive services such as computer vision, decision-making models such as anomaly detectors, classification models, and language and speech models.

For customers who are on-prem due to security reasons, we have expertise in creating solutions using Ollama to host their AI solution in-house. We have also adapted and embraced AI in our software development lifecycle. For instance, our developers use GitHub Copilot to develop faster solutions and reuse code, while our Business Analysts use ChatGPT to research Domains.

Software engineers depend on certainty. Since its introduction, software has been built on logic, with inputs determining outputs. Al turns all of that on its head. With Al, the answers aren't exact. It uses models to learn and then replicate behavior. Traditional software is precise, while Al is flexible. We get the best of both by implementing Al into our software development practices.

Al is a massive help with code development, maintenance, and testing. While not every part of the SDLC will benefit from Al, there is a huge lift in other areas, and Al can potentially take days off from development. 

We see Al's best-in-class use in automating repetitive tasks, speeding up the development life cycle, reducing maintenance costs, and improving software reliability and predictive analysis. With all these gains, one thing remains the same: the human element must be maintained. 

Despite the adoption of Al into software development, all indications are that real humans, such as software engineers, will be creating software in the foreseeable future. We must adapt and prepare to work with innovations shaping the future.