# On-Prem AI ROI Calculator: Payback and 3-Year Return

> Source: https://netray.co/tools/on-prem-ai-roi-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Turn hours saved per employee into annual net benefit, payback months, and 3-year ROI for an on-prem AI investment.

## Category

on-prem-ai

## Tool

**Kind:** calculator

**Inputs:**

#### Employees using the AI system

**Key:** knowledge_workers

**Type:** number

**Default:** 200

**Min:** 10

**Max:** 10000

**Step:** 10

**Unit:** people

**Help:** Engineers, planners, quality, finance, and support staff with access.

#### Hours saved per user per week

**Key:** hours_saved_per_week

**Type:** slider

**Default:** 3

**Min:** 0.5

**Max:** 10

**Step:** 0.5

**Unit:** hrs/wk

**Help:** Measured pilots typically show 2-5 hours on drafting, search, and summarization.

#### Average fully loaded hourly cost

**Key:** avg_hourly_cost

**Type:** number

**Default:** 55

**Min:** 20

**Max:** 200

**Step:** 5

**Unit:** $/hr

**Help:** Salary plus benefits and overhead divided by ~2,000 annual hours.

#### Realistic adoption rate

**Key:** adoption_rate

**Type:** slider

**Default:** 60

**Min:** 20

**Max:** 95

**Step:** 5

**Unit:** %

**Help:** Share of licensed users who actively use the system weekly by month 6.

#### Implementation investment

**Key:** implementation_cost

**Type:** number

**Default:** 250000

**Min:** 25000

**Max:** 2000000

**Step:** 25000

**Unit:** $

**Help:** Hardware, deployment services, integration, and training - one-time.

#### Annual run cost

**Key:** annual_run_cost

**Type:** number

**Default:** 90000

**Min:** 10000

**Max:** 1000000

**Step:** 10000

**Unit:** $/yr

**Help:** Power, support, model refreshes, and operations staffing per year.

**Outputs:**

#### Annual hours saved

**Key:** annual_hours_saved

**Expr:** round(knowledge_workers * hours_saved_per_week * 48 * adoption_rate / 100)

**Format:** hours

**Description:** Active users times weekly savings across 48 working weeks.

#### Annual labor value captured

**Key:** annual_labor_value

**Expr:** round(annual_hours_saved * avg_hourly_cost * 0.5)

**Format:** currency

**Description:** Hours valued at loaded cost with a conservative 50% value-capture factor.

#### Annual net benefit

**Key:** annual_net_benefit

**Expr:** annual_labor_value - annual_run_cost

**Format:** currency

**Description:** Captured value minus yearly operating costs.

#### Payback period

**Key:** payback_months

**Expr:** round(implementation_cost / max(annual_net_benefit / 12, 1) * 10) / 10

**Format:** months

**Description:** Months for net benefit to repay the implementation investment.

**Primary:** true

#### 3-year ROI

**Key:** three_year_roi_pct

**Expr:** round((annual_net_benefit * 3 - implementation_cost) / implementation_cost * 100)

**Format:** percent

**Description:** Net 3-year return as a percentage of the implementation investment.

**Primary:** true

**Disclaimer:** Estimates only. Real ROI depends on measured adoption and time savings in your environment; the 50% value-capture factor is a conservative planning assumption, not a guarantee.

## Content

**Intro:** This calculator builds the financial case for an on-prem AI investment, converting hours saved per employee into annual net benefit, a payback period in months, and a three-year ROI percentage - the three numbers every CFO asks for. It is designed for manufacturers evaluating self-hosted AI assistants, RAG over technical documentation, and workflow automation. The model is deliberately conservative: it discounts adoption below 100%, applies a 50% value-capture factor to saved hours, and subtracts full run costs, so the output survives finance scrutiny rather than collapsing under it.

**Sections:**

#### How the ROI model works

**Body:** Annual hours saved multiplies your user count by weekly hours saved, 48 working weeks, and your realistic adoption rate - because licensed seats never equal active users. Those hours are valued at fully loaded hourly cost, then cut in half by a value-capture factor: saved time does not convert one-for-one into output, since some of it dissolves into slack, and honest models say so. Net benefit subtracts annual run costs, payback divides the one-time implementation investment by monthly net benefit, and three-year ROI expresses cumulative net return against that investment. At the defaults - 200 users, 3 hours a week, 60% adoption - the model shows roughly $385K annual net benefit, an 8-month payback, and about 360% three-year ROI.

#### Benchmarks for defensible inputs

**Body:** The most contested input in any review meeting is hours saved, so anchor it in measured evidence rather than vendor claims. Published enterprise copilot studies and Netray's own pilot measurements cluster in consistent ranges by task type.

**Bullets:**

- Document drafting and correspondence: 30-50% time reduction on affected tasks
- Technical information search and retrieval: 2-4 hours per engineer per week
- Meeting, report, and record summarization: 1-2 hours per user per week
- Realistic month-6 adoption with active change management: 50-70% of seats

#### Reading your results like a CFO will

**Body:** Payback under 12 months clears almost any capital committee; 12-24 months is fundable with a credible measurement plan; beyond 24 months, rescope to fewer users with higher-value workflows rather than pushing optimistic inputs. Expect two challenges in review. First, 'those hours are not real dollars' - which the 50% capture factor already concedes; offer to run a measured 90-day pilot converting the assumption into observed data. Second, 'adoption will disappoint' - which is a self-fulfilling prophecy without funded training and champions, so put change management inside the implementation budget rather than treating it as optional.

#### How Netray turns the projection into measured ROI

**Body:** Netray implements on-prem AI with the measurement discipline this model assumes: baseline time studies before rollout, instrumented usage tracking, and quarterly value reporting your finance team can audit. We scope implementations to hit sub-12-month payback by starting with the highest-density workflows - typically engineering document search, quality record summarization, and ERP-adjacent drafting for SyteLine and LN environments - then expanding on evidence. The business case you build here becomes the baseline we measure the deployment against.

**Cta:** Build your ROI case, then let Netray design a measured pilot that turns the projection into audited numbers.

**Faq:**

#### Why does the calculator halve the value of saved hours?

**Answer:** Because saved time converts to business value imperfectly - some becomes higher output, some becomes better-quality work, and some dissolves into ordinary slack. Claiming 100% conversion is the fastest way to lose a finance audience. The 50% factor is a defensible middle ground consistent with how productivity-tool business cases are typically underwritten; if your pilot measures actual throughput gains, replace the assumption with your data.

#### What belongs in implementation cost versus annual run cost?

**Answer:** Implementation is one-time: GPU hardware and servers, deployment and integration services, data preparation, security review, and initial training - typically $150K-$400K for a mid-market on-prem deployment. Run cost recurs annually: power and cooling, hardware support contracts, model refresh and evaluation effort, and an operations staffing share, commonly $60K-$150K per year. Keeping them separate is what makes payback and ROI calculations meaningful.

#### How do I defend the hours-saved input to skeptical executives?

**Answer:** Do not defend an assumption - propose a measurement. Run a 60-90 day pilot with 20-30 users: baseline their time on target tasks first, instrument usage during the pilot, and survey plus re-measure at the end. Pilots in document-heavy manufacturing roles consistently land in the 2-5 hour weekly range, and a measured 2.5 hours from your own people beats a claimed 5 hours from any vendor benchmark in every executive conversation.

## Search terms

on-prem ai roi calculator, enterprise ai payback period, ai business case manufacturing, llm roi calculator, ai productivity savings calculator, ai investment return enterprise

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