AI led Software Engineering

“Software is eating the world” – Andreessen Horowitz, HP (2011)

“Software is eating the world, but AI is going to eat the software” – Jensen Huang, Nvidia CEO (2017)

Background

Last decade has seen lot of disruptions in the industry placing unforeseen challenges on CIOs. Rate of business change has increased exponentially with much shorter time to market. The intensely competitive market ensures that chances of failure are almost nil. CIOs are expected to partner business, and at times leads, the delivery of digital transformation. The existing IT landscape of a company needs to be rationalized and modernized to be able to achieve the expected business velocity. To meet this challenge, over last decade, IT has responded with new culture, new methodologies, processes, modern tooling, technologies and architectures. Traditional boundary lines separating different specializations such as between Infrastructure Management and Application or between Development and Operations are now fallen. It is a norm now to expect a single, small team to have all the diverse skill sets required to deliver the business change.

These disruptions have placed an unprecedented demand on the team’s productivity and learning curve. There are many strategies being adopted to meet these challenges, e.g. leveraging RPA, AI, digitalizing the business processes etc. In this discussion we will focus on AI-enabled tools which are becoming popular to assist and augment project managers, requirement analysts, designers, developers, testers and support engineers in their daily tasks. These tools employ variety of AI technologies, including NLP, machine learning, deep learning etc to intelligently automate or assist decision making on behalf of team members. AI is now transforming the software engineering space and we need to take note and make decisions best suited to us. This series of article discusses the happenings in the AI led software engineering space, benefits it brings, use cases and the investments Sopra Steria is making in this new area to benefit its clients. The insights presented here are much wider in scope that just standard AI-Ops tools and cover the entire IT project lifecycle, starting from requirements to post production operations.

Benefits of AI led Software engineering Transformation 

AI is transforming software engineering and helping organizations deliver IT at the speed of business. More specifically, if any of the below challenges sound familiar, then you will be benefited by adopting AI led software engineering.

HR Challenges

We need our brightest people to be working on initiatives closer to business and not in lower value tasks, which can be “outsourced” to AI. This also keeps the employee happy as they get to be engaged in impactful activities rather than just “keeping the lights on”. Given the talent shortage and the time and effort it takes to ramp them up on business, keeping employees motivated by utilizing them in business focused activities is a high priority.

Productivity & Quality

Let’s face it, while humans beat algorithms in wisdom and creativity, reverse is true for speed and consistency. It is difficult to beat a well-trained AI for say predicting a defect and fixing things proactively so that it does not occur or semantic analysis of millions of line of code to determine security vulnerabilities. AI is good in discerning patterns and leveraging them to solve problems while humans can be in over-all control, assisted and augmented by AI.

Time to market

AI is essentially the newest team-mate who is so versatile that it can share workload of all the roles applicable to a project, except the fact that this special “team member” does only certain kind of work, excels at it but needs humans to provide him guidance. 

Business Value

Business KPI’s can be better tracked and managed by pooling in and correlating relevant data from various sources to help get a view of metrics important for business. This can lead to data driven collaboration and decision-making. Proactive IT operations can improve the satisfaction level of end customers.

Change Management

AI adoption introduces transformative changes to project processes thus requiring careful change management especially in operations area. Proper planning, encompassing people, processes and technology, is required for doing the restructuring needed to introduce the change.

Green development: AI can lead to capacity optimizations and incidence preventions etc which in turn helps make the green metrics better in a big way.

There are whole range of use cases for leveraging AI in various activities in the project or operations. At Sopra Steria, our role is to give you a perspective of this new trend so that you can make the best decision for the tangible results for yourself. In the subsequent articles we will talk about the AI use cases, both matures ones and ones in experimental phase, applicable to project for all its lifecycle stages. We will also talk about how, at Sopra Steria, we have invested in building IPs for implementing some of these use cases and helping our clients with it.

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AI led Software Engineering Use Cases: Application to Project Management activities