AI-Enabled Software Delivery: Rethinking Team Roles and Responsibilities

AI software delivery is upon us, as the train of new AI-related information is unrelenting.

SaaS companies, in particular, are at the forefront of this revolution. Our senior techies and product folks must be prepared to embrace this change.

The days of manual planning and sifting through lines of code will soon be gone. It will happen sooner than we expect. We're already in an era where machines can optimize and create software. Are we, as an industry, ready for this transformation?

In this post, I will talk about my thoughts on the evolution of traditional software engineering team roles, the emergence of new ones, and some ideas for preparing your organization for the AI-driven software development process.

AI-Powered Software Delivery

By "AI software delivery", I'm talking specifically about integrating artificial intelligence into the software development process to optimize planning, coding, software testing, and deployment.

This fusion of AI and software engineering has the potential to revolutionize how we develop, deliver, and maintain software.

That should lead to faster development cycles, improved efficiency, and reduced costs.

For those that don’t adopt fast enough, it’s probably the kiss of death.

As leaders in our respective domains, we are the person responsible for staying ahead of the curve and ensuring that our software development teams are equipped to navigate this monumental shift.

The Transformation of Traditional Roles

We know we have to adapt.

I want to think about some of our most common roles, and how they could be impacted by AI.

My question is this: what’s the best way to harness the possibility of radical change driven by AI and keep everything on the rails?

1. Software Engineers. That covers everyone from your QA engineers to your front-end developers. Embracing AI isn’t optional for engineers. Knowing how to use AI to get the right answers fast, write code in the right contexts and automate repetitive tasks is imperative for your team to avoid falling victim to competition. Higher-level decision-making tasks need to be their everyday. Ultimately it’s entirely possible to supercharge engineering team performance.

   
   

2. Product Managers/Owners. Project managers included. Product innovation will become an AI collaboration task. You'll be left behind if you’re not using AI-powered tools to gain insights into customer needs and preferences, predict market trends, and make data-driven decisions.

   
   

3. DevOps Engineers. AI-powered tools will be a mainstay of DevOps operations. The gap between human-only and AI-assisted DevOps performance will be substantial. AI will support optimising almost every process, from CI/CD to security.

   
   

4. Team Leads/Tech Leads. Being strategic about AI will be the success differentiator for tech leads. Sure – their job will be to understand AI. It will also be to align and develop the AI use philosophy of the business both upstream and downstream and spot opportunities and risks (including legal developments). Perhaps most importantly, upskilling and reskilling people while instilling a culture of experimentation and innovation will be critical.

Just a taste. But what about leaders?

The era of senior technical and product managers monopolizing knowledge and decision-making is fading, and these roles have to evolve.

Mastery of AI technologies and seamless integration into the development process is now essential.

Senior product managers should embrace AI for informed decisions and previously inaccessible insights.

Consider a senior technical manager at a SaaS company who once spent hours reviewing code and identifying bottlenecks. AI-powered code analysis tools automated this process, allowing them to focus on strategic planning and team development. This transition from hands-on expert to a strategic leader, leveraging AI for efficiency and productivity, exemplifies the required shift.

Adaptability and embracing change are imperative in this AI-driven software delivery landscape. Senior managers adhering to outdated practices risk obsolescence.

Preparing Your Organisation for the Future

Adopting AI-powered software delivery is not just about implementing new technologies and reshuffling team roles—it's about cultivating a mindset of innovation and adaptability throughout your organization.

Here’s a quick checklist of the things that come to my mind…

• Culture is king. Experimentation and measured risk-taking won’t happen without support and endorsement from the top. That includes healthy conversation around AI adoption and AI implementation.

  
  

• Encourage safe adoption. Give your blessing – and clear guidelines – to your team to equip themselves with the skills they need to adopt AI effectively. Actively make that space, and get people talking about their learnings. Lead from the front.

  
  

• Encourage cross-function collaboration. Your software development team is probably at the sharp edge of AI adoption in your organization. But the benefits will extend a long way past your engineering team. Collaborate with other departments to ensure your other teams – such as marketing, sales, and CX – stay ahead of the curve.

Conclusion

AI is here to define team roles across the software industry. We must be prepared to adapt to this new reality, embrace the opportunities it presents, and navigate the challenges it brings.

When we get this right, we’ll tap into a competitive advantage that can fuel exponential growth and propel our organizations forward.

Also published here.