AI Automation ROI Calculator (India)

We compute the value of human hours freed by automation, subtract running costs (LLM credits, hosting), add other quantifiable savings (errors avoided, faster cycle), and compare cumulative net savings against the one-time setup cost. Payback period = implementation months + setup cost / net monthly savings. Year-1 and year-3 ROI = cumulative net savings over that window divided by setup cost. The model assumes 176 working hours per month (22 days × 8 hours) to convert your fully-loaded monthly labour cost into an hourly rate.

For an India SMB, ₹50,000/month is a realistic fully-loaded cost (gross salary plus EPF, gratuity provision, insurance, equipment, and overhead) for a mid-skill operations or back-office role automating today. Senior engineers, accountants, or marketing leads will land closer to ₹1,50,000–₹3,00,000/month. Override the default to match your actual fully-loaded cost — the calculator is only as accurate as the inputs.

Strong yes = payback under 12 months — high-confidence build. Yes = payback 12–24 months — solid project, monitor carefully. Marginal = payback 24–36 months — pilot before full commitment, the assumptions need to be conservative. Reconsider = payback over 36 months or net monthly savings are zero or negative — either trim setup cost, automate a higher-value process, or push more value through other monthly savings (errors avoided, faster cycle time).

It is the share of those task-hours that an AI system can realistically take over end-to-end without a human in the loop. Most workflows land at 50–70%: AI handles the routine cases, humans handle exceptions and approvals. If you have not piloted yet, default to 60%. If you have piloted and measured task-completion rate, use that number. Setting this above 90% on a complex process is usually wishful thinking.

Indirectly — we assume you fold change management (training, documentation, rollout) into the one-time setup cost. If you are buying off-the-shelf automation it might be 10–20% of setup; if you are building custom and rolling out across geographies, it can be 30–50%. Bump setup cost accordingly. We do not model failed-pilot risk; the conservative approach is to run the calc twice with optimistic and pessimistic setup-cost assumptions.

For most AI automation business cases the payback is short enough (under 24 months) that NPV moves the answer by single-digit percent. Adding a discount rate makes the model harder to explain to stakeholders without changing the verdict. If you are comparing this against a multi-year capital project, take the year-3 cashflow into your standard NPV template at your firm's WACC. Discount-rate support is on the roadmap.