AI Agent ROI Calculator: 30 Days of Autonomous Work

Every sales leader gets the same question from finance in 2026: “Show me the math on this AI agent thing.” Most decks answer with a vibe. This guide gives you the actual five-number formula, runs it through realistic numbers for a 30-day window, and flags the four places the math quietly lies. By the end you’ll have a spreadsheet template you can rebuild in 15 minutes and defend in a budget meeting.

#TL;DR

The 30-day ROI of an AI sales agent comes down to five inputs:

1. Fully-loaded SDR cost / month (salary + benefits + commission + tooling + manager time)
2. SDR output volume (sourced contacts, sequences sent, meetings booked)
3. Agent operating cost / month (compute + LLM tokens + integrations)
4. Agent output volume (multiplier vs human baseline)
5. Quality discount (agent reply rate as a percentage of human reply rate)

Sample output for one US-based SDR replaced by a configured agent: roughly $7,000 net savings in month one, with the agent producing 2x to 4x the touch volume at 60% to 80% of the human reply rate. Use this calculator when you’re deciding between hiring SDR #4 and deploying an agent, not when you’re benchmarking AI as a category.

#Why ROI on AI sales agents is harder than it looks

Most “AI ROI” claims on the market round up. The honest numbers are still good, but you have to compare like-for-like and accept that the agent does some things worse than the human. The reason the math is hard is that you’re comparing a fixed-cost asset (the SDR) with a variable-cost asset (the agent), across two different output curves, with a quality gap in the middle.

The fixed-cost side looks clean on the surface. A US-based SDR runs $80,000 to $120,000 fully-loaded including base, on-target earnings, benefits, tooling, and ramp time, per the Bridge Group SDR Metrics Report (2023). Glassdoor’s 2024 SDR salary range, anchored on tens of thousands of self-reported salaries, puts US base alone at roughly $55,000 to $75,000 before the rest of the stack (Glassdoor SDR Salary, 2024).

The output side is where the lying starts. SDR teams routinely report “150 calls a day” or “500 emails a week” as productivity metrics. Those are activity metrics, not output metrics. The number that funds the business is meetings booked that turn into pipeline, and that number is roughly an order of magnitude smaller than activity counts suggest.

Reps spend only 28% of their week actively selling, with the rest absorbed by admin, research, and tool-switching, per Salesforce State of Sales (2024). That 72% is exactly the slice an agent can absorb. But absorbing it isn’t free, and the savings only materialize if you actually redeploy or right-size the human cost. A team that runs an agent and keeps every SDR seat got a coverage upgrade, not an ROI win.

#The 5 inputs you actually need

To compute 30-day ROI for an AI sales agent, you only need five numbers, and you should refuse to run the calculation if any of them is a guess. The five are: fully-loaded SDR cost per month, SDR output volume per month, agent operating cost per month, agent output volume per month, and the quality discount applied to agent output to make it like-for-like with the human baseline. Three of the five come from your finance and ops data. Two require a two-week pilot before you trust them. The formula collapses when teams skip the pilot and plug in vendor-claimed numbers.

#Fully-loaded SDR cost per month

Take base salary, add OTE commission at plan, add employer-side benefits (typically 25% to 35% of base in the US per Bureau of Labor Statistics ECEC, June 2024), add the per-seat cost of every tool that seat consumes (CRM seat, sequencer seat, dialer seat, data enrichment seat), and add a manager-time allocation. A manager running an 8-rep team at $180K spends roughly 10% of their week per rep, which is real money once you divide it back in.

For a fully-loaded US SDR at the midpoint of the Bridge Group range ($100K/year), monthly cost lands around $8,300. For a UK-based SDR you can roughly halve the OTE component but add UK employer National Insurance.

#Output volume per SDR

Pull the last three months from your CRM. Count meetings booked that the AE accepted, not raw activity. Industry medians for outbound SDRs cluster around 3 to 8 meetings booked per week per rep, which gives a monthly band of roughly 12 to 32 meetings. If your team is below that band, the agent ROI looks better. If you’re above it, your reps are probably top-quartile and the comparison gets harder.

Capture the inputs too: sourced contacts per month, sequences started, total touches sent, reply rate, meeting-acceptance rate. You need these to compute the quality discount later.

#Agent operating cost per month

For a configured agent stack, this is a small number. The main cost components are: a per-instance subscription (server plus orchestration), LLM inference billed by tokens through a gateway like OpenRouter, third-party integration costs (LinkedIn relay, enrichment API, email send domain), and a small amount of operator time to review escalations.

For a typical B2B SaaS deployment running one agent at moderate volume, expect total monthly operating cost in the low hundreds to low thousands of dollars, depending on token consumption and message volume. The number swings most on LLM choice. Routing complex reasoning to a frontier model and simple classification to a cheaper model can change the bill by 3x to 5x for the same workload.

#Agent output volume

This is the input most teams overestimate. The honest framing: a configured agent can process 2x to 5x the touch volume of a human SDR for cold top-of-funnel work, because it doesn’t context-switch, doesn’t take PTO, and runs on a 24-hour clock. The multiplier shrinks for tasks that require relationship memory or live judgment.

Anchor on touches sent and contacts researched per day, then convert to meetings booked using the next input. Skip the temptation to claim a 10x multiplier. Vendor decks claim it. Real deployments don’t deliver it consistently.

#Quality discount (reply rate vs human baseline)

The discount is the silent killer of optimistic ROI decks. Set agent reply rate as a percentage of your trailing-90-day human SDR reply rate. A well-tuned agent on warm personalization typically lands at 60% to 80% of human reply rate. A poorly-tuned agent (generic templates, no real personalization) lands at 20% to 40% and produces a spam reputation problem at the same time.

Apply the discount to agent touch volume to get a quality-adjusted output number. This is the number that goes into the formula. Without the discount, you’ll book a savings number that doesn’t survive contact with your sales-ops dashboard in week three.

#The 30-day formula, worked through with realistic numbers

Here is the formula, then a worked example. Variables first.

Net savings (30d) = SDR_cost - Agent_cost
                    + (Agent_meetings_qadj - SDR_meetings) * Meeting_value

Where:

• SDR_cost = fully-loaded monthly cost of the human SDR
• Agent_cost = monthly operating cost of the agent (subscription + tokens + integrations + operator time)
• SDR_meetings = meetings booked by the SDR in 30 days
• Agent_meetings_qadj = agent touches * meeting-conversion rate * quality discount
• Meeting_value = your average pipeline value per accepted SDR meeting

Worked example, midpoint US B2B SaaS, replacing one SDR with one configured agent:

• SDR_cost = $8,300 (fully-loaded, $100K/year)
• Agent_cost = $1,200 ($200 plan + ~$700 tokens + ~$200 integrations + ~$100 operator review)
• SDR_meetings = 20 (5/week, midpoint of the Bridge Group band)
• Agent_touches = 6,000 (3x human volume on cold outbound)
• Meeting_conversion = 0.4% (touches to accepted meeting on cold outbound)
• Quality_discount = 0.70 (agent at 70% of human reply rate)
• Agent_meetings_qadj = 6,000 * 0.004 * 0.70 = ~17
• Meeting_value = $2,000 (pipeline per accepted meeting, conservative)

Plug in:

Net savings = (8,300 - 1,200) + (17 - 20) * 2,000
            = 7,100 + (-6,000)
            = $1,100 net savings in month 1

That’s the honest answer for pure replacement in month one: a small positive, not a windfall. The windfall shows up in two scenarios, both of which the formula handles cleanly.

Scenario A: augmentation. Keep the SDR, deploy the agent alongside for cold prospecting. SDR meetings stay at 20, agent adds 17 more. Marginal monthly cost is $1,200. Marginal pipeline added is 17 * $2,000 = $34,000. Marginal ROI is roughly 28x in month 1.

Scenario B: replacement at scale. Replace SDRs 3 and 4 (the ones you would have hired next quarter) with two agent runs. You avoid $16,600 of fully-loaded monthly cost. Agent cost is $2,400. Quality-adjusted meetings are roughly 34. The savings are real and they recur every month.

The point of the formula isn’t to produce a single number. It’s to make the assumptions explicit so finance and sales argue about the right variables.

#Where the math lies (4 traps to avoid)

The formula is straightforward. The mistakes aren’t. Here are the four traps that turn a defensible ROI deck into a six-week credibility loss.

Trap 1: quality discount underestimated. The single most common ROI inflation. Teams plug in a 90% quality discount because the demo agent wrote one good email. Real production quality on cold outbound from a freshly-configured agent typically lands between 40% and 70% of human baseline for the first month, climbs into the 70% to 80% band after iteration, and stays there. Run a two-week pilot, measure actual reply rate, use the measured number. Anything else is fiction.

Trap 2: manager-time savings overstated. “We’ll save the manager 10 hours a week” is a number that rarely shows up on the cost line because managers don’t get cheaper, they just absorb other work. Count manager-time savings only when it directly replaces a backfill or a contractor invoice. Otherwise it’s coverage upside, not P&L savings.

Trap 3: tool-stack double-count. If you deactivate the SDR’s sequencer seat when you replace the SDR, you save that tool cost. If you keep the sequencer because the agent uses a different stack, you don’t. Half the ROI decks count the sequencer savings without checking whether the contract auto-renews per seat or per workspace. Read the contracts.

Trap 4: augmentation vs replacement confusion. The formula gives different answers for “replace one SDR” and “add an agent next to the SDR.” Both are valid plays. Conflating them gets you to a number that looks like replacement savings plus augmentation pipeline, which double-counts the value. Run the formula twice with explicit scenarios. Label which is which.

#A spreadsheet template you can copy

You can rebuild the calculator in a fresh Google Sheets tab in 15 minutes. Five tabs total, each isolated so you can adjust assumptions without breaking the formula.

Tab 1: Inputs. One column for variable name, one for value, one for source. Variables: SDR base salary, OTE, benefits %, tool stack per seat, manager-time allocation, agent plan cost, average tokens per task, token price per million, integration costs, operator-review hours, agent touch volume per day, meeting-conversion rate, quality discount, average pipeline per meeting.

Tab 2: SDR cost. Pulls from Inputs and computes fully-loaded monthly cost per SDR. Formula stack: base/12 + OTE/12 + (base * benefits%)/12 + tools per month + (manager salary/12 * allocation %).

Tab 3: Agent cost. Pulls from Inputs and computes monthly agent cost. Formula stack: plan + (daily tasks * avg tokens * price per million / 1,000,000 * 30) + integrations + (operator hours * loaded hourly rate).

Tab 4: Output and quality. Computes quality-adjusted meetings per month for both SDR and agent. Formula stack: SDR meetings = direct input from CRM. Agent meetings = daily touches * 30 * conversion rate * quality discount.

Tab 5: 30-day result. The two-line summary: net savings (cost side) and net pipeline (output side). One row per scenario: pure replacement, augmentation, and the “next hire avoided” scenario. Color the cells green when the scenario clears your hurdle rate and red when it doesn’t. Done.

Keep every input cell sourced. If you can’t cite the source for a number, color the cell yellow and treat the scenario as not yet decision-grade.

#What Tasmela’s customers see in month 1

We’re going to be specific where we can be and honest where we can’t. Tasmela provisions a dedicated AI agent per customer that handles top-of-funnel sales work across the channels your team already uses (LinkedIn via a compliant relay, Gmail or Workspace, Slack escalations, calendars). The 14-day trial exists specifically so you can plug your own numbers into the formula above before committing.

What we won’t do is invent customer-level outcomes. The DO NOT CLAIM list on our side is real: no fake testimonials, no fictional case study numbers. What we can tell you is what the published industry benchmarks say about deployments structured this way.

In similar B2B SaaS deployments, published industry benchmarks show first-month outcomes clustering in three patterns. For pure replacement of one cold-outbound SDR, expect small positive savings ($1K to $5K) at midpoint US salaries. For augmentation alongside an existing 4-to-8-rep SDR team, expect 20% to 40% pipeline coverage uplift, with the cost line dominated by token spend not subscription. For “next hire avoided” scenarios (the budget you would have spent on SDR #N+1), expect the agent cost to land at 10% to 20% of the avoided headcount cost, monthly, recurring.

These ranges assume the data layer is clean, the quality discount is measured (not assumed), and there is a human-in-the-loop checkpoint on named accounts. Skip those preconditions and the ROI compresses fast. For the underlying architecture this calculator is sized against, the AI agent stack for B2B sales pillar walks through the five-layer reference design in detail.

If you want to pressure-test the calculator against our pricing tiers, the /tarifs page lists what is included at each plan including AI credits, which is the cost line that swings the formula the most.

#FAQ

#How long should I run a pilot before trusting the ROI number?

Two weeks is the minimum to get a defensible quality discount. One week is enough volume to set up the agent but not enough cycles to measure reply rate stability. Four weeks is ideal if your sales cycle includes a follow-up sequence. The number that takes longest to stabilize is meeting-acceptance rate, because it depends on whether the booked meetings actually convert in pipeline review.

#Should I replace my SDR or augment them?

If you have a coverage gap and your SDR is hitting quota, augment. The agent absorbs cold top-of-funnel and frees the SDR for warm follow-up and live calls. If you have an open SDR seat you were about to hire for, replace the hire with an agent and re-run the formula after 30 days. If you have an underperforming SDR who isn’t clearing quota, fix the SDR or change the role design before deploying an agent. An agent on top of a broken motion just makes the broken motion faster.

#What if my AE meetings don’t convert at the same rate as SDR-sourced meetings?

You need a second conversion rate in the formula: agent-sourced meeting to opportunity. If that rate is lower than SDR-sourced meeting to opportunity, apply a second quality discount at the pipeline stage. A meeting that the AE rejects in week three is not a meeting that funds the business. Track the cohort separately for the first 90 days.

#Does the ROI math change for enterprise vs SMB sales?

Yes. Enterprise sales has lower meeting volume, higher pipeline value per meeting, and stricter human-in-the-loop requirements on named accounts. The cost side of the formula stays similar but the output side compresses on volume and stretches on value per meeting. Run the formula with your actual ACV and meeting-conversion rates. SMB deployments typically show faster month-one payback. Enterprise deployments show larger absolute pipeline impact but slower attribution.

#What is the single biggest variable to nail before I run the formula?

The quality discount. Everything else is finance arithmetic with documented inputs. The quality discount is the only variable that requires a real pilot to measure honestly. Teams that skip the pilot and use a vendor-supplied 90% discount produce ROI decks that don’t survive a quarterly review. Two weeks of measurement is cheap insurance against a six-month credibility problem.

#Read next

• The AI Agent Stack for B2B Sales in 2026 (Pillar Guide) - the five-layer architecture this calculator is sized against.
• Automate B2B Lead Generation with an AI Agent (2026 Guide) - the layer-1 and layer-3 deep dive on the prospecting side of the equation.
• How to Give an AI Agent Access to LinkedIn (Complete 2026 Guide) - the action-layer setup for the channel that swings agent reply rates most.
• ChatGPT vs AI Agent: What’s the Difference? - the conceptual primer if your finance team still calls everything “ChatGPT.”