SalesQuants

Agent vs. Calculators

Should your next pipeline dollar go to an AI agent — or a human? Run both motions through the same funnel with your own numbers. Results update instantly, and your scenarios save on this device.

Workload economicsComing soon

Agent vs. RevOps Analyst

Automation vs. analyst hours on the same RevOps workload. In review — not yet released.

Planning models only — not forecasts. Replace every default with your own validated operating data before making a hiring or technology decision.

First-year economics

Should your next pipeline dollar go to an SDR—or an agent?

Compare both motions on the same funnel. Use your own costs, meeting volume, conversion rates, and deal economics. The result updates instantly.

Human SDR motion

SDR

SDR seats

Base salary per SDR

$

Fully loaded multiplier

×

Benefits, payroll taxes, equipment, management

Annual tools per SDR

$

Qualified meetings / month / SDR

Ramp time

months

Agent motion

Agent

Annual platform cost

$

One-time setup cost

$

Human oversight

hrs/wk

Oversight hourly cost

$

Qualified meetings / month

Ramp time

months

Shared funnel economics

YOUR FUNNEL

Meeting-to-opportunity rate

%

Opportunity win rate

%

Average contract value

$

Gross margin

%

Model verdict

The agent leads on first-year net value.

That advantage depends on meeting quality holding up at your entered conversion rates.

+$0 advantage

Agent first-year ROI 0%

Payback: —

Agent net value$0

SDR net value$0

Agent year-one cost$0setup + platform + oversight

SDR year-one cost$0loaded pay + tools

Agent cost / meeting$0productive first-year meetings

SDR cost / meeting$0productive first-year meetings

Agent gross profit$0from modeled closed revenue

SDR gross profit$0from modeled closed revenue

How the model works

Both options run through the same meeting → opportunity → closed-won funnel. Gross profit equals closed revenue × gross margin. Net value equals gross profit minus first-year cost.

Ramp is modeled at 50% productivity during the ramp period, then full productivity after it.

What the math does not capture

Brand risk, deliverability, compliance, and data quality
Conversation quality, territory nuance, and relationship-building
Downstream AE capacity and implementation change management

Planning model only—not a forecast. Replace every default with your own validated operating data before making a hiring or technology decision.

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The model guide, honest benchmarks, and new calculators as we build them. We model, we don't market.

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Sales capacity model

Where does an AI agent create more value?

Compare two honest cases: helping reps convert recovered time into pipeline, or turning automated work into usable team capacity. Adjust every assumption — the result updates instantly.

Sales team

Sales reps

reps

Quota-carrying headcount

Loaded cost / rep

$

Salary, benefits and overhead

Annual quota / rep

$

At 100% attainment

Current attainment

%

Team average

Gross margin

%

Applied to incremental revenue

Work the agent can change

Workweek

hrs

Total hours per rep

Automatable work

hrs

Admin, research, prep, follow-up

Agent automation

%

Share of that work handled

Productivity capture

%

Recovered time that becomes selling

Rep adoption

%

Team share using it consistently

Investment

Agent cost / rep / year

$

Software and usage

One-time rollout cost

$

Integration, enablement, governance

Model signal

Assist the team first

The modeled gross-profit lift is stronger than the value of capacity alone. Pilot the workflow before treating time saved as revenue.

+$0net value advantage

Assist the reps

Convert recovered time into revenue

Stronger case

Year-one net value$0

Incremental revenue: $0
Gross-profit lift: $0
Year-one ROI: —
Payback: —

Automate the work

Use time saved as deployable capacity

Second case

Year-one net value$0

Capacity unlocked: —
Capacity value: $0
Year-one ROI: —
Payback: —

Annual recurring cost$0

Year-one investment$0

Hours returned / year0

Pilot guardrails

Start with 2 reps for 60–90 daysChoose one repeatable workflow, not a broad “AI transformation.”
Require 9.0 hours returned per rep each weekMeasure completed work and usable time, not prompts or logins.
Prove at least $164K in annualized revenue liftThat is the break-even lift at your margin and year-one investment.

How the model works

Assist case: baseline revenue × automatable share of the workweek × agent automation × productivity capture × adoption. Gross margin converts the revenue lift to gross profit.

Capacity case: rep count × automatable share × agent automation × adoption. That FTE-equivalent capacity is valued at loaded rep cost.

ROI: (benefit − recurring cost − rollout cost) ÷ (recurring cost + rollout cost).

This is a decision model, not a forecast. The two cases are alternative value lenses and should not be added together. Capacity only becomes savings when hiring is avoided, workload is redeployed, or headcount changes. Revenue lift assumes recovered time produces at the team’s current rate.

Planning model only—not a forecast. Replace every default with your own validated operating data before making a hiring or technology decision.

Get the Agent vs. playbook in your inbox

The model guide, honest benchmarks, and new calculators as we build them. We model, we don't market.

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The amplification case

Same team. More pipeline. What does AI add to every rep?

Skip the replacement debate. Keep your reps, hand them AI, and model what happens to volume, replies, meetings, and pipeline. The result updates instantly.

Your team today

TODAY

Reps / SDRs

Outbound touches / rep / month

Emails, calls, social touches — all channels

Reply rate

%

Replies that become meetings

%

Meeting-to-opportunity rate

%

Opportunity win rate

%

Average contract value

$

Gross margin

%

AI amplification levers

AI LEVERS

More outreach volume

%

AI drafting, sequencing, and list-building put more at-bats in play

Higher reply rate

%

Personalization and account intelligence make each touch land better

More replies become meetings

%

Instant follow-up and better targeting — no reply waits, none drops

Realization rate

%

The honesty dial: share of the theoretical uplift you actually capture after adoption and deliverability limits

AI cost

COST

AI cost per rep

$/mo

Licenses, usage, and data for one amplified rep

Annual platform / implementation

$

Team-level platform, integrations, and rollout

Amplification verdict

Same team. 51% more meetings.

Nobody was replaced. Every rep just produces like one and a half reps — the gain is output, not headcount savings.

+51% meetings per rep

Net gain per rep, year one $0

Team net gain: —

Meetings / rep / month — amplified0

Meetings / rep / month — today0

Meetings lift+0%after the realization discount

Revenue per rep — amplified$0from $0 today

Incremental pipeline / rep+$0new opportunities × ACV, per year

Equivalent team size0 repsoutput of the amplified team, in today's reps

AI ROI, year one0%net gain ÷ AI cost

Payback—on year-one AI spend

How the model works

Your baseline funnel runs touches → replies → meetings → opportunities → closed-won, per rep, per year. Each AI lever lifts its own stage of that funnel, discounted by the realization rate, and the stages compound — more touches, each converting better, is how the meeting count multiplies.

Net gain equals incremental gross profit across the team minus year-one AI cost (per-rep seats plus the platform fee). Nobody leaves the model: the output is more pipeline from the same headcount.

What the math does not capture

Deliverability ceilings — inboxes punish raw volume; that is what the realization dial is for
AE capacity: 51% more meetings needs someone to take them
Data quality, territory saturation, and conversation quality
Rep adoption — an uplift nobody uses realizes at 0%

Planning model only—not a forecast. Replace every default with your own validated operating data, and make vendors defend the uplift percentages they promise against your realization rate.

Get the Agent vs. playbook in your inbox

The model guide, honest benchmarks, and new calculators as we build them. We model, we don't market.

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Agent vs. Calculators

Agent vs. SDR

Agent vs. Rep

Amplified Rep

Agent vs. RevOps Analyst

Should your next pipeline dollar go to an SDR—or an agent?

Human SDR motion

Agent motion

Shared funnel economics

Power your outbound with Instantly

Get the Agent vs. playbook in your inbox

Saved scenarios

Where does an AI agent create more value?

Sales team

Work the agent can change

Investment

Get the Agent vs. playbook in your inbox

Saved scenarios

Same team. More pipeline. What does AI add to every rep?

Your team today

AI amplification levers

AI cost

Get the Agent vs. playbook in your inbox

Saved scenarios