Article

Will AI replace software outsourcing companies?

June 20, 2024

FAQs

Stay updated with our tech articles – your go-to source for the latest insights, trends, and innovations in technology.

A: Some of the biggest challenges of using AI for software development include AI’s general limitations, which, in the context of software development include:

● Hallucinating responses,

● Inaccuracy, be it for code generation or review,

● The necessity of vast amounts of data (big data) for training purposes.

Nonetheless, AI can still be used - it requires a significant level of human supervision in order to make it viable. In due course, however, businesses and their software development teams need to assure that the inclusion of AI is helping them reduce turnaround times as well as cost, in order to justify using it further.
A: The best way to determine whether your offshore or nearshore software outsourcing team is using AI is to ask them. However, it is important to keep in mind that the tools used by any software development team (AI or otherwise) are simply the means to an end. In other words, high-quality, punctual outcomes that help your business meet expected KPIs are what ultimately matter.

Inversely, though, if you as a business leader or project manager observe that the addition of any new tools are costing more money, time and effort than previous working systems, this is a sign that your team may be working away from business objectives - and deliberations need to be followed in order to streamline operations.
A: No, AI doesn’t always perform better than humans and isn’t always recommended for certain software development tasks as a result, contrary to popular perception. AI presents significant limitations when it comes to fields of expertise that are more creative in nature, such as UI/UX design - as human sentiments such as empathy and the ability to sincerely resonate to users’ problems are required in order to deliver viable results.

However, AI can be valuable for tasks that experience a high volume of inbound data which require parsing and triaging, such as security alerts. Additionally, it can also significantly help streamline regression testing, as no test will be missed every time a new update is made to an application.

Can't find your answers?

Contact us