Most pitches for AIOps sound like a magician on stage. The lights dim, the voice gets dramatic, and then comes the reveal: “AI will fix everything.”
Except it doesn’t.
Technology has never worked that way. It does not create miracles by itself.
It creates leverage.And leverage only matters when it moves the financial needle.
I’ve seen this pattern across every portfolio I’ve led. The organisations that gained real ROI from AIOps didn’t fall for the magic show. They focused on seven very grounded levers. Each one with a direct line to EBITDA.
Let’s walk through them.
1. Fewer L1/L2 tickets.
These tickets are the background noise of operations. They drain focus and morale. When automation takes out 30–50% of that noise, the difference is not theoretical. It’s felt in the breathing space teams suddenly have.
2. Halved MTTR.
Mean Time to Resolve sounds like an engineering metric, but I see it as a human one. A customer waiting for a service to return is measuring patience, not time. Halving MTTR is halving their frustration. And happier customers stay longer.
3. SLA compliance.
Moving from 88% to 97% compliance looks like nine percentage points. In reality, it’s the line between penalties and renewals. Between shaky trust and solid confidence. EBITDA improves not just by avoiding fines but by keeping the business you already have.
4. Redeploying 15–25% of ops capacity.
This is the quiet win. When automation takes over repetitive monitoring and remediation, people are freed up. Not to do nothing, but to do the things they never had time for. Process improvements. Customer projects. System upgrades. Growth initiatives. The kind of work that moves a company forward.
5. Tooling consolidation.
Most IT stacks look like cluttered toolboxes — three hammers, two wrenches, and a screwdriver that no one remembers buying. AIOps consolidates functions, reduces licenses, simplifies contracts. It is not glamorous, but every rupee saved here flows directly to the bottom line.
6. Predictive maintenance.
This is where the story turns proactive. Instead of fixing after the break, you prevent the break. Downtime doesn’t just reduce — it disappears into near-misses that never happened. That is real resilience.
7. Cloud cost optimisation.
Cloud costs creep. Slowly, silently, and always upward. AIOps puts guardrails here — workload forecasting, scaling policies, smarter allocation. Even single-digit percentage savings on cloud spend can add up to meaningful EBITDA lift.
When you line them up like this, something becomes clear. None of these levers is “magical.” They are all practical. Each has a number you can track and a financial story you can tell.
That is why AIOps matters. Not because it is futuristic, but because it is immediate. The board doesn’t want to hear about AI. They want to hear about EBITDA.
AIOps only works when we translate technology into that language.
So when I hear the pitches, I no longer ask: “What does your AI do?”
I ask: “Which lever does it move?”
And then, the real question for you: Which of these levers, if pulled today, would change the story of your organisation tomorrow?
C
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