Artificial intelligence is changing software development in ways large and small. While many companies race to roll out AI-enabled features, the potential for AI goes beyond the feature level. Rather, AI will become the foundation for most—if not all—SaaS solutions. Machine learning and AI models will allow SaaS technologies to continually drive new efficiencies across a variety of business processes. AI should be seen as the foundation for a new way of development.
Software delivery will become a utility. The grunt work that exacted a high tax for incremental value will just happen, and the backlog of high-value additions and innovation will surge into production. Humans will not get replaced. Rather, you will see the greater potential of software developers unleashed.
From design to platform thinking
With AI at the core of platform (and SaaS) development, you’ll start to see “design thinking” evolve into “platform thinking.” Exploration and learning will be essential in a world of AI-powered technology. Rather than outcome-oriented, software design will become goal-oriented. Using AI, development teams will be able to:
- Rapidly build and deploy functional proofs of concept (POCs), not just design prototypes.
- Run A/B tests and multivariate tests with real end users.
- Identify and deploy fully tested applications based on real-time user evidence.
Because AI enables professionals of all skill sets to design, deliver, and improve both processes and technology, platform thinking will become ingrained across entire businesses. The end result will be empowering every employee in the enterprise to bring ideas to reality very rapidly.
As AI becomes an essential part of software development (and ultimately business processes), team structure and skill sets will need to evolve. The AI engine, which will appear in many forms (platform suggestions, companion bots, analytics and reporting), will become an active part of the software delivery team.
AI as an extension of software delivery
Although agile methodology has been praised as widely adopted, few businesses have truly achieved continuous delivery. With AI serving as an extension of your software delivery teams, true agile will be made possible. Intelligent automation will enable teams to deliver changes at a continuous flow.
What forms will this intelligent automation take? Design systems will be dynamically created and implemented as bots build underlying code. Self-built POCs will enable full feature testing from the outset. Built-in and evolving test automation will ensure quality and rapidly increase velocity.
How AI will affect software development roles
Companies will need to consider the role AI will play in platform engineering and be one step ahead. As this new way of development emerges, so will new job opportunities.
- The role of the business analyst will be elevated to drive business strategy. In all likelihood, AI will write individual user stories, requirements, and acceptance criteria. Rather than capturing criteria, business analysts will assess AI-generated ideas and drive business alignment to platform thinking. AI and technology will be a driving factor in business strategy, and business analysts will be the face of this arm of the strategy.
- Interaction design roles will outpace UI design roles. As visual AI rapidly evolves, demand for UI design to individually lay out pages and business process flows will decrease. Interaction designers will guide AI to design UI and UX through JavaScript design systems, graphical guidelines, and continuous user testing.
- Software architects will wield the power of AI. Even at the infancy of AI in software development, we’re already seeing the rapid emergence of platform engineering. Businesses are quickly moving away from point-SaaS solutions and consolidating on both custom-built and SaaS-enabled platforms such as Salesforce, ServiceNow, and Workday. Today, software architects are designing governance systems to guide code standards, development processes and more. In the future, they will power AI to build, enforce and evolve these systems on their behalf.
- Test architecture will emerge as a highly-paid, in-demand role. With autonomously built software, continuous testing will be critical. As the delivery lifecycle condenses, more testing will be needed than ever before. Automating user tests based on acceptance criteria will not be enough. Test architects will design, deploy, and maintain complex test architectures, end-to-end test new functionality, continually conduct exploratory testing, and execute ever-evolving regression suites.
Ultimately, with AI as the foundation of SaaS, the day-to-day work of software builders will fundamentally change. Continuous testing will be the deciding factor in a world of AI-driven software development and will determine which businesses thrive and which will fall behind in this new pace of work.
Sanjay Gidwani is COO of Copado.
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