Applying Agile is a mindset change rather than a process change as compared to traditional methods. Some of the typical challenges faced by teams in the Industry while practicing Agile are:

• Limited experience with agile
• Slowing down of work due to limited access to Product Owner
• Incomplete\less detailed user stories leading to high onshore dependency
• Struggle to keep momentum with continuous churn of agile events through active participation and to maintain quality of artifacts (backlog, burndown, impediment list, retrospective action log)

These challenges manifold when delivery teams within the Industry are practicing distributed agile at scale. In the last couple of years within the IT industry we are seeing the infusion of Artificial Intelligence (AI). The question which come up is, Can AI help to address some of the above challenges?

At Accenture, we have introduced virtual Agile agent that resides in our intelligent automation platform, Accenture myWizard®; The virtual agent uses set of AI technologies to collaborate with their human co-workers to help address above mentioned challenges. It monitors numerous aspects of Agile development projects—consisting of requirements, releases, metrics and resources—alerting the team of any potential issues and providing possible solutions.


Outline/Structure of the Talk

The outline of the session will be:

05 Minutes | State of Agile and practical challenges
During first 5 minutes, we will set the context by referring to VersionOne's state of Agile report as well as learnings from Accenture’s own experience of delivering distributed Agile projects. We will emphasise on how these challenges manifold when delivery teams are practicing distributed Agile at scale.

10 Minutes | What is Artificial Intelligence (AI)?
We will dedicate this slot to provide brief introduction to AI, how AI in today’s world is capable of sensing, comprehending and acting to create intuitive interactions and extend the capabilities of what either human or machine can do on their own. This will be followed by introduction to different types of popular AI techniques and how we are already deployed them in current IT landscape. We will share some of the examples of AI Machine Learning in Service management, application development, testing and quality assurance where manual tasks are being automated with good amount of success.

05 Minutes | AI for Agile: Automation Opportunities through Time & Motion Study
We will share details around the Time & Motion study (value stream mapping) that was carried out with the Accenture’s Agile teams to understand the challenges faced by them. We will detail out the value stream mapping technique and the outcome of interview process which was carried out with the Scrum masters and Agile team members. This technique helped us to understand AI opportunities within the Agile teams thereby to either address fully or partially the challenges they were facing during the Scrum ceremonies or while managing expectations during delivery.

10 Minutes | Introducing the Virtual Scrum Master
With the background of our Time & Motion study, we will now introduce the Virtual Scrum Master which came into the existence to leverage opportunities within the Agile team’s ways of working. Will talk about how the Virtual Scrum Master uses historical information (structured information like user story feed, semi structured information like server logs and unstructured data like speech to text of conversations) and provides recommendations, self healing opportunities, analytical insights, predictions, guided assistance to various Scrum ceremonies. We also throw insights on evolution of Virtual Scrum Master from performing automation of manual steps to becoming virtual member of the team. We will reference the functional design diagram of Virtual Scrum Master to explain the working of the Virtual Scrum Master and the key capabilities that it is performing today.

05 Minutes | Challenges in Adopting the Virtual Scrum Master
While the concept sounds great, the adoption of the virtual Scrum Master hasn’t been easy. There are tough questions around going against one of core values of Agile – Individuals and interactions over processes and tools! The perception is that we are trying to build AI agents with the hidden agenda of taking over the Scrum Master role in near future. We will talk about these challenges by classifying them into three broad level categories – people, process & technology.

05 Minutes | Where do we stand today?
We will share some insights with the participants on which of the above mentioned challenges are still a work in progress and how we were able to overcome others.

05 Minutes | Conclusion - Welcome the new digital co- worker
We would like to conclude the session by calling out how our fellow Agile SMEs can actively take part shaping up use of AI for Agile in today’s age is of human empowerment. It’s about us designing technology that conforms itself to people, putting us firmly in control of our own fate. How participants can collaborate with artificial intelligence (AI) and machines to do our jobs better going forward by embracing new digital co-worker!

Learning Outcome

We will like to share on how Agile agent has helped teams on the following aspects of Agile product development:

  • Identify and automate repetitive Agile tasks.
  • Gain insights to effectively drive Agile ceremonies, and create quality deliverables
  • Use historical information to predict the future and take corrective measures when needed.
  • Analyze patterns/relations/co-relations of historical and transactional project data to diagnose root causes
  • Drive standardization of Agile practices while scaling in a distributed fashion

But then it’s not been hunky dory all the time, we are facing some tough questions from the Agile teams about taking risk of going against one of core value of Agile – Individuals and Interactions Over processes and tools! Are we trying to build AI agents which will take over Scrum Master jobs?

We will like to talk about our perspective on this. We believe that AI in Agile will not replace the collaboration between and within the teams but augment it to the next level where Scrum Master and Machine work together to achieve continuous improvement.

In this session, we will share a case study where we have implemented the virtual Scrum Master to gain efficiency within a distributed Agile team.

Target Audience

Change Enablers, Scrum Masters, Product Owners

Prerequisites for Attendees

The attendee should know about what is Agile and should have the experience of Distributed Agile. If the attendees know the basics of AI, that will be helpful however not mandatory. Session is also for those who is Interested to know how AI can positively influence Agile in coming days.


schedule Submitted 4 years ago