3 Agile Software Development Practices to Create AI Applications

AI developers are more reliant on Agile methodologies to create the best applications.

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Artificial intelligence technology is becoming more important with each passing day. Companies in every industry from finance to manufacturing to hospitality are investing in AI to improve their business models. Companies around the world are projected to spend nearly $1.6 trillion on AI by 2030, as they discover the countless benefits it offers.

Software developers are taking advantage of the sudden booming market for AI. They are creating a number of AI applications that are specialized to serve a number of different purposes.

Agile technology has been a very important part of the software development process. AI has helped create SCRUM teams to improve Agile development, but the same technology has in turn helped create new AI applications as well.

If you are an AI software developer, you are going to want to understand the best practices for using Agile to streamline the process. Keep reading to learn more.

Guidelines on Using Agile to Create AI Applications

Agile software development combines flexibility with speed. It’s about delivering projects and bringing apps to life to provide customers with quick but consistent results. Development teams might focus on one project or app at a time. However, these groups do it with a heavy emphasis on collaboration, cross-functional skill sets, and customer-centric mindsets.

The versatility and flexibility of Agile practices make them ideal for creating AI applications. Carlo Appugliese of IBM has a great guide on creating great AI projects with Agile. Appugliese says the launch of an Agile team is the first initial sprint needed to create a great AI application.

However, using Agile to create an AI project won’t be easy. You need to assemble the right team and make sure the right processes are in place.

As a leader of an agile development team, your job is to reinforce and facilitate their work. The unique structure and approach your group uses to get things done also demands a distinctive leadership methodology. You won’t be able to create quality AI programs without

This article outlines three ways to effectively support an agile team.

1. Implement Your Chosen Agile Methodology With Intention

By definition, an agile software development team uses an agile development methodology to define and shape its workflows. You can choose between the Lean, Kanban, and Scrum approach, among others. One of the most popular agile methodologies is Scrum, and for good reason. It breaks down the group’s tasks into sprints, letting them focus on completing chunks of a project at a time.

Thinking about the nature of a sprint from a runner’s perspective demonstrates why the Scrum approach can be so effective. A runner covers a short distance with incredible speed and energy. A software development team does the same by working in sprints under Scrum. They focus on designing and bringing one product feature to life. Then it’s on to the next one. This is how most AI applications are born. They require a number of AI features to work optimally, so they must be carefully honed.

Leaders can ensure sprints are well organized and go as planned by efficiently separating and allocating tasks. You can start with a list of your product’s priorities and see where your backlog exists. AI applications are very sophisticated these days, so you need to identify them carefully.

Then you can make a separate list of assignments that consist of unfinished tasks from your backlog. Use the list to plan out what your team will tackle during their next sprint. As you check off each priority one at a time, be sure to communicate your expectations and timelines when creating the next big AI application.   

2. Build Up Trust and Camaraderie

Agile groups work at a fast pace. But one thing that doesn’t move at the speed of light is trust. It takes a bit of time and trial and error to build team members’ faith and confidence in each other. They have to get to know one another, each member’s work ethic, and what each excels at.  

Simultaneously, trust starts with leadership. A Gallup survey found that only one in three employees have faith in their leaders. Dishonesty, a lack of interaction, finger pointing, and refusal to own up to mistakes can negatively influence how your team perceives you.

When team members can’t put stock in what you say and do, they’re less likely to follow your direction. Productivity takes a nosedive, and animosity can spread like wildfire. It’s not just you the team doesn’t trust; it’s each other.

Simple, open, and frequent communication can go a long way toward preventing a toxic culture. Something as easy as daily stand-up meetings builds in face time and encourages the group to interact. Each team member says what they’ve accomplished, the tasks they’re currently working on, and whether they need help.

As their leader, your job is to demonstrate open communication and coordinate the collaborative process. When someone in the group needs help, match them with the appropriate resources. These include others on the team with the experience and expertise to help their colleagues overcome their obstacles.

3. Cross-Train Employees

Because everyone on the team brings something different to the table, group members can learn from each other. Cross-training and pair programming help employees build and expand their knowledge. This strategy also prevents information silos and ensures projects keep moving while someone is out of the office.

In some teams, cross-training and knowledge sharing are formalized. Employees are paired as backups to each other. They learn the other team member’s responsibilities by working side by side and exchanging information.

When one person is out sick or on vacation, their backup assumes responsibility for their tasks. While the backup may not get to everything, they handle the most urgent requests and priorities. This way, nothing critical falls through the cracks.

Less formal cross-training might involve digital resources, including collaborative knowledge bases. Employees contribute to these resources as they stumble upon questions that impede workflows and the solutions that resolve them. Or team members might come to you, expressing interest in learning more about a technique or subject area. You could then pair employees with others who are already skilled and knowledgeable in those methods and subjects.

Either way, you’ll support flexibility within your team’s skill set. Plus, you’ll be providing employees with learning opportunities. One of the top things software developers look for and value in an employer is professional development. When you invest in them, they’re more likely to stay committed to each project and the organization.

Remaining Agile While Developing AI Applications

There’s a saying that a team is only as strong as its weakest link. Your goal is not to be that link! Without solid leadership, a team of software developers is essentially a bunch of individuals trying to accomplish uncoordinated tasks. This is especially true when developing AI applications, due to their complexity.

To be successful, the group needs you to provide an overall direction and a method for getting there. Along the way, honest, frequent communication combined with knowledge sharing is essential to the collaboration agile teams are built upon. You also have to have a system for testing your AI software before releasing it to market. Incorporating these approaches into your leadership style can help your team become more adaptable and efficient.

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