Agile Software Development is Driving AI and ML Innovation

Learn how Agile software development is driving AI and ML innovation

Artificial intelligence (AI) and machine learning (ML) are now widely used in businesses across virtually every industry, and the rapid pace of adoption shows no signs of slowing: McKinsey research suggests that AI could enable the automation of up to 70% of business activities between now and 2030.

According to Damian Winczewski, Head of Agile at STX Next, an Agile approach's agility and customer-centricity may drive technical innovation, laying the groundwork for the continuous development of new AI and ML applications.

According to STX Next, agile software development will define the future of AI and machine intelligence.

"For a long time, agile methodologies have been a driving force in software development." This strategy, noted for its adaptability, flexibility, and customer-centricity, is well aligned with the concepts behind AI and ML, especially considering the rapid growth of these technologies. Agile techniques, such as Scrum, have a cyclical evolution that is well suited to the dynamic nature of AI and ML initiatives.

Incorporating Agile into AI and ML projects has various advantages, including rapid adaptability to the ever-changing digital landscape, risk minimization, budgetary restraint, and improved project quality and client satisfaction. Agile approaches have had to adapt to new issues as distributed teams and the remote work revolution have grown in popularity. To retain agility and productivity, Agile teams must use virtual stand-up meetings, collaborative online tools, and asynchronous communication techniques.

Aside from remote work issues, Agile approaches are expanding to integrate sustainability and ethical development practices as more firms see the necessity of responsible AI and ML development. Agile frameworks are being modified to include ethical concerns in the development process, ensuring that AI and machine learning systems are created with fairness, transparency, and accountability in mind.

Agile approaches will stay at the vanguard of innovation as the software development landscape evolves, allowing teams to adapt to changing conditions and give value to consumers. "Whether it's in the exciting and transformative world of AI and ML, or in addressing the challenges of remote work and ethical development, Agile is poised to shape the future of software development in exciting and transformative ways," Wisniewski said.