Will AI Replace Scrum Masters and Agile Coaches?

The Core Argument

Guided by host Sanjay Saini, Brij argued that AI is the equivalent of the late 90s computer revolution — it will eliminate some roles while creating others. He stated that AI will not entirely replace Agile Coaches or Scrum Masters, but will drastically expand their capacity. Sanjay added that currently, too many professionals waste massive LLM engines on trivial tasks like email writing. Together, they concluded that Agile practitioners must embrace AI for deep data querying, predictive sentiment analysis, and context engineering to avoid obsolescence.

“It is going to eat up the jobs, but it is going to create the jobs at the same time.” Brij K Jalan (04:08)

Detailed Answers

1. Could you share a brief overview of your professional background?

Brij began his career in the IT industry in 2002 during a recession. After taking on various short-term roles, he joined TCS in late 2003, where he has remained for over two decades. Over his 22-year tenure, he has moved through nearly every role in the software lifecycle, starting as a tester and developer before transitioning into project management. He eventually scaled the ladder to become an SPC and an offshore Agile Coach for the past eight years.

2. How do you view the general impact of AI on IT and software teams?

Brij compared the current AI boom to the computer revolution of the late 1990s. While AI will inevitably render some jobs obsolete, he argued it will generate entirely new roles simultaneously. Sanjay added that unlike early computers — which were strictly for tech professionals — AI spans all departments and non-tech roles equally. Survival depends entirely on adopting AI as a baseline productivity enhancer across the board.

3. How are you personally utilizing AI in your day-to-day workflow?

In his professional life, Brij relies on generative tools to slash the time spent on administrative tasks. Drafting a complex presentation now takes him under 90 minutes using templated AI inputs. Sanjay supplemented this by recommending purpose-built deck generation tools that produce rapid, high-quality presentation drafts from basic prompts, which speeds up the workflow even further.

4. How will AI specifically alter the roles of Agile Coaches and Scrum Masters?

Brij highlighted how AI drastically scales a coach's capacity. During massive SAFe PI planning events with multiple breakouts, an Agile Coach can now deploy AI agents to monitor all rooms simultaneously and flag friction. Sanjay validated this capacity expansion with a real-world HR use case: he is currently building a model that uses AI sentiment analysis to evaluate six months of employee survey data to predict future attrition, a predictive capability that is impossible at human speed.

5. What is the current level of AI adoption among development teams?

Adoption is currently polarized due to insecurity and unequal tool access. Brij shared a scenario where a team member used a cloud-based AI tool to generate a complex Jira query that completed 80% of the work instantly. Sanjay strongly noted that using massive LLM engines merely for trivial tasks, like writing standard emails, is a childish use of the technology and a massive waste of its true analytical potential.

“People are using massive LLMs for writing emails. That is a childish use of the technology.” Sanjay Saini (23:32)

6. How can organizations leverage AI for broad transformation and measuring ROI?

When leadership considers AI adoption, their singular focus is Return on Investment. Brij explained that executives want to know exactly how much cost can be eliminated before committing to expensive licenses. The industry is currently in a state of confusion, overwhelmed by daily product announcements. Ultimately, organizations realize they need a hybrid approach of human intelligence and AI, but are actively trying to find the right balance.

7. What specific upskilling steps should Agile practitioners take right now?

Brij advised that the first skill anyone must learn is prompt engineering. However, Sanjay expanded on this, observing that the industry is rapidly moving beyond simple prompts into context engineering and agent configuration. Practitioners must learn how to provide rich data context to AI models. Brij also recommended completing fundamental AI certifications from major cloud providers to understand token mechanics.

Brij starts practitioners at prompt engineering; Sanjay's point is that the bar has already moved to context engineering and agent configuration. Closing exactly that gap is what our Artificial Intelligence training program is built to do.

8. Is AI governance a viable future career path for Agile practitioners?

Yes. Just as test managers transitioned into Scrum Master roles during the Agile boom of the 2010s, Brij predicted that current Scrum Masters will transition into AI governance and AI security roles. For practitioners feeling threatened by generative tools, shifting their career focus toward establishing ethical guardrails and operational governance for these very tools is a highly secure and lucrative next step.