Sanjay K Mohindroo
Discover how senior IT leaders can strategically decide where to start and stop with IT process automation to balance efficiency and human judgment.
The Boardroom Imperative
The conversation around IT process automation is no longer confined to back-office IT meetings or DevOps stand-ups. It’s moved into the boardroom.
Why? Automation now shapes competitive advantage, customer experience, and operational resilience in ways that directly influence market position and shareholder value.
For senior technology leaders — CIOs, CTOs, CDOs, and board-level stakeholders — the challenge isn’t simply “Should we automate?”. That’s already answered. The real challenge is twofold:
Where do we start — and how do we know when to stop?
Too much automation, applied without strategic boundaries, can create brittle systems, erode flexibility, and amplify risk. Too little automation, on the other hand, leads to sluggish operations, lost opportunities, and higher costs.
Over the past two decades, I’ve navigated both extremes — witnessing automation deliver astonishing business transformations and, in other cases, spiral into costly misadventures. This post distills those experiences into a narrative that invites discussion, challenges assumptions, and equips you with a mental map for leadership in this space.
From Server Rooms to Strategy Rooms
Automation isn’t just a cost-saver anymore; it’s a growth enabler.
In today’s digital transformation leadership landscape, automation influences:
- Speed to market — Faster deployments mean quicker revenue capture.
- Data-driven decision-making in IT — Automation ensures data flows are timely, accurate, and analytics-ready.
- Resilience — Automated recovery and failover keep services alive in a crisis.
- Security posture — Orchestrated security automation reduces incident response times from hours to minutes.
- Customer experience — From self-healing apps to personalized digital services, automation defines the brand interaction.
At a strategic level, automation is a lever for IT operating model evolution. But here’s the catch — boards now ask not just how automation will help, but how leaders will govern it. The governance piece is where most organisations stumble.
Automation can become a silent empire-builder, sprawling into areas where human judgement should still reign. The right approach demands balance — enough to create transformative efficiency, but not so much that it strips away flexibility and adaptability.
The Shifting Ground Beneath Us
Global trends tell a clear story:
- Gartner projects that by 2026, 70% of organisations will have implemented structured automation governance to avoid the “dark side” of over-automation.
- McKinsey’s 2024 report estimates that intelligent automation could unlock $3.3 trillion in annual value globally by 2030, but also warns of “automation debt” — the cost of poorly planned automation that must later be unwound.
- ISG data shows that automation-led transformation projects now yield an average ROI in 18–24 months, down from 30–36 months just five years ago.
In my experience, three macro-shifts are reshaping automation decisions:
1. From isolated scripts to enterprise orchestration — Leaders are moving beyond automating single processes to creating interconnected, cross-departmental automation ecosystems.
2. From reactive to predictive — AI and machine learning are enabling automation that not only reacts to events but anticipates them.
3. From tech-first to value-first — The conversation now starts with business outcomes, not technology features.
#DigitalTransformation #EmergingTechnologyStrategy #CIOPriorities
My Playbook in the Field
Over the years, I’ve distilled a few guiding principles that have saved me — and my teams — from expensive mistakes.
1. Start with “Why”, Not “How”
It’s tempting to begin with the tools, vendors, and shiny new platforms. But the starting point must always be business value. Every automation project should pass this test:
“If this automation disappears tomorrow, will it materially hurt our ability to deliver on our strategic goals?”
If the answer is “no,” you’re automating the wrong thing.
2. Treat Automation Like Architecture
You wouldn’t build a skyscraper without blueprints. Yet I’ve seen automation stacks evolve organically — one RPA bot here, one workflow there — until they resemble spaghetti code in real life. Leaders must think in terms of modular design and scalable governance from day one.
3. Know the Automation Comfort Zone
This is about recognising where automation should stop. Some processes thrive under automation; others require human discretion, ethical judgement, or nuanced contextual awareness. One example: automating customer complaint resolutions beyond a certain level can backfire, stripping away empathy from interactions.
Frameworks, Models, and Tools — Navigating the Spectrum
I use what I call the Automation Spectrum Framework with leadership teams:
Stage 1 — Stabilise
Focus on automating repetitive, low-risk, high-frequency tasks. Example: password resets, data entry, patch scheduling.
Stage 2 — Optimise
Move to more complex workflows that cross team boundaries. Example: incident triage, supply chain notifications, predictive maintenance triggers.
Stage 3 — Innovate
Here, automation enables new capabilities that didn’t exist before. Example: AI-driven service recommendations, autonomous incident resolution.
Stage 4 — Govern
Implement strong governance, metrics, and stop rules. Define thresholds where human intervention must re-enter.
Checklist for leaders to start tomorrow:
- Identify top 5 automation candidates with measurable business impact.
- Map risk exposure for each.
- Define clear ROI metrics (time saved, cost avoided, error reduction).
- Assign ownership for automation governance.
#ITOperatingModelEvolution #DataDrivenDecisionMaking
Lessons from the Field
Case 1: The Telecom Operator That Over-Automated
A leading telecom player rolled out aggressive automation in its customer service arm. While call resolution times dropped by 40%, customer churn increased by 12% within a year. The reason? Automation replaced too many human touchpoints, eroding trust and empathy.
Lesson: Always balance operational efficiency with customer experience.
Case 2: The Bank That Got It Right
A regional bank used automation for compliance reporting, freeing up analysts for investigative work. The project paid for itself in nine months and improved regulatory audit scores. Crucially, they had a clear “automation stop zone” — no AI-led decision-making in credit approvals without human review.
Lesson: Define automation boundaries upfront to protect brand trust.
The Road Ahead
Looking ahead, automation will become ambient — embedded into every layer of enterprise operations, often invisible until it fails. AI will make automation smarter, but it will also make governance harder.
For senior IT leaders, the competitive edge won’t come from who automates the most. It will come from who automates wisely.
If you take nothing else from this post, remember:
- Start with value — not tools.
- Architect for scale — not patchwork.
- Draw the line — where human intelligence matters most.
The most visionary CIOs, CTOs, and CDOs will be those who see automation as both a power tool and a responsibility.
Where do you see automation starting and stopping in your organisation? I invite you to share your thoughts — let’s make this a conversation worth having in every boardroom.