Agentic AI ROI Calculator: Hiring FTEs vs Managed Services vs AI Agents

Why RevOps ROI Comparisons Usually Get It Wrong

When a VP Revenue or CRO sits down to evaluate RevOps investment options, they typically build a spreadsheet with three columns: hire an FTE (salary + benefits), engage an agency (monthly retainer), or buy a software tool (annual licence).

Table of Contents

1. Why RevOps ROI Comparisons Usually Get It Wrong
2. Option 1: Hiring RevOps FTEs — The True Cost
3. Option 2: Managed RevOps Services — What You're Actually Buying
4. Option 3: Agentic AI — The Full Investment Picture
5. TCO Comparison: 12, 24, and 36 Months
6. ROI by Company Size
7. The Hidden Costs Nobody Puts in the Spreadsheet
8. When Each Option Wins
9. How to Build Your Own Business Case
10. Frequently Asked Questions

This is the wrong comparison, and it consistently leads to bad decisions.

The problem is that the spreadsheet captures cost inputs but misses output quality, operational coverage, and the compounding value of getting RevOps right over time. A £65,000 RevOps Manager looks cheaper than a £96,000 managed services retainer on a spreadsheet. But the RevOps Manager works 8 hours a day, isn't available on weekends, takes 10 weeks to reach full productivity, and will likely leave within 18 months, triggering a recruitment cycle that costs £12,000–£20,000 and 3 months of degraded coverage.

The spreadsheet doesn't capture any of that.

This guide builds a genuine total cost of ownership (TCO) model across all three options, FTE, managed services, and agentic AI, over 12, 24, and 36 months. It uses real UK market numbers and accounts for the costs that typically don't make it into the initial comparison.

By the end, you'll have a framework you can adapt to your specific team size, ARR, and RevOps scope to make a properly informed decision.

Option 1: Hiring RevOps FTEs — The True Cost

The Salary Is Just the Start

The most common mistake when costing RevOps headcount is treating salary as a proxy for total cost. In practice, the fully loaded cost of a UK-based RevOps hire is consistently 40–65% above the advertised salary.

Here's the full picture for a RevOps Manager at the UK market midpoint:

£106,957 in Year 1. Not £65,000.

And that's before accounting for productivity ramp time.

The Productivity Ramp Problem

A new RevOps hire does not arrive at 100% productivity on day one. Based on consistent patterns across B2B SaaS companies, the typical ramp curve looks like this:

• Months 1–2: 25% productive (onboarding, process learning, system access)
• Months 3–4: 50% productive (independent execution begins)
• Months 5–6: 75% productive (handling most tasks without supervision)
• Month 7+: 100% productive (fully contributing)

This means you're paying full cost for roughly 6 months of sub-full productivity. The effective productivity cost in Year 1, when you account for ramp, is approximately:

Full year cost: £106,957. Actual productivity delivered (weighted average ~65% in Year 1): equivalent to £69,522 of full productivity

You're paying for a year, getting roughly two-thirds of the value.

The Attrition Reality

RevOps is a high-demand skill set with significant career mobility. Average tenure for RevOps professionals in UK B2B SaaS companies is currently 18–24 months.

That means on a 36-month horizon, you should plan for at least one full recruitment and ramp cycle. The cost of that replacement:

• Recruitment fee: £11,700
• Productivity loss during transition (3 months at 50% output): ~£13,250 equivalent
• Knowledge transfer cost (documentation gaps, tribal knowledge): £5,000–£10,000 estimated
• Total replacement cycle cost: £29,950–£34,950

Spread across a 36-month plan, attrition adds approximately £10,000–£11,650 per year to the true cost of the FTE model.

What One FTE Actually Covers

A single RevOps Manager working 40-hour workweeks has approximately 1,600–1,750 billable hours per year after meetings, admin, and non-project time.

Typical RevOps work volume for a £5M–£10M ARR B2B SaaS company (based on ARISE GTM client audits):

At the high end of volume, one FTE cannot cover all the required work. At the typical midpoint (~38 hours/week required), they're at capacity with no headroom for strategic projects or growth.

The result: strategic RevOps work process design and GTM architecture are permanently deprioritised because operational execution consumes all available capacity.

Option 2: Managed RevOps Services — What You're Actually Buying

How Agency Retainers Are Priced

Managed RevOps agencies typically structure retainers in one of three ways:

Fixed monthly retainer with a defined scope: £4,000–£15,000/month for a specified set of deliverables, usually a mix of strategic and operational work.

Time-and-materials against a monthly bank: £5,000–£20,000/month of consultant time at blended rates of £125–£250/hour.

Project-based with ongoing support: A fixed implementation fee (£8,000–£25,000) followed by a smaller ongoing retainer (£2,000–£6,000/month) for maintenance and optimisation.

For a mid-market B2B SaaS company at £5M–£10M ARR, a realistic managed RevOps engagement looks like this:

On paper, this looks comparable to a fully loaded FTE. But the comparison breaks down on coverage.

The Coverage Gap

40–60 consultant hours per month sounds like a lot. It isn't.

At the RevOps work volume table above (38 hours/week average requirement = ~165 hours/month), a managed retainer providing 50 hours/month covers approximately 30% of the operational work required.

The rest falls back on your internal team — typically a generalist ops person, the Head of Sales Operations, or the CRO themselves.

What the agency covers well:

• Strategic projects (CRM architecture, attribution modelling, process redesign)
• Periodic deliverables (quarterly audits, reporting framework builds)
• High-skill execution (complex workflow development, integration setup)

What the agency struggles to cover:

• Daily operational execution (data hygiene runs, lead routing reviews, routine field updates)
• 24/7 availability (inbound leads don't arrive during agency business hours)
• Volume work (bulk data operations, campaign launches, ongoing CRM hygiene)

This is the core tension in managed RevOps: you're paying premium rates for a service that's architecturally unable to cover continuous operational work.

The Escalation Risk

Agency relationships carry an escalation risk that rarely appears in the initial cost model. When a consultant leaves the engagement, when scope expands beyond the retainer, or when a time-sensitive project creates work overrun, costs rise quickly.

Based on typical engagement economics:

• Consultant turnover affects 30–40% of multi-year agency engagements
• Scope creep adds an average of 15–20% to annual retainer costs
• Emergency escalations (system issues, data emergencies, urgent campaign builds) add £500–£3,000 per incident

Conservative escalation budget for a 36-month engagement: £15,000–£25,000 additional.

Option 3: Agentic AI — The Full Investment Picture

The ARISE GTM Cost Structure

Agentic AI for RevOps has two distinct cost phases: initial deployment and ongoing operation. Understanding both is essential for an honest TCO model.

Phase 1: Agentic GTM Blueprint (Months 1–2)

Before agents are deployed, a structured scoping and architecture phase maps your current RevOps operations, identifies the highest-ROI agent opportunities, designs the agent architecture, and builds the MCP connectivity infrastructure.

Phase 2: Ongoing Agent Operation (Month 3+)

Once deployed, agents operate continuously with human oversight and monthly optimisation support.

For a full five-agent system (adding GTM Strategy and Lifecycle agents in months 4–6):

What the Investment Buys in Operational Coverage

Unlike the FTE (1,600–1,750 hours/year) or managed retainer (600 hours/year), a three-agent agentic system provides:

• RevOps Agent: 24/7 operation, processing every lead, every data change, every routing decision. Equivalent workload coverage: 2,500–3,500 hours/year of operational execution.
• BI Agent: Continuous pipeline monitoring, automated weekly reporting, and real-time anomaly detection. Equivalent: 600–800 hours/year of analytical work.
• Human oversight included in package: 4–6 hours/month of expert governance, optimisation, and escalation handling.

Total operational coverage equivalent: 3,100–4,300 hours/year, more than twice what a single FTE can provide, at higher consistency and with 24/7 availability.

TCO Comparison: 12, 24, and 36 Months

This is the comparison that matters. Using the cost structures above for a £5M–£10M ARR B2B SaaS company requiring mid-to-high volume RevOps coverage.

12-Month TCO

At 12 months, the costs are roughly equivalent. The difference is entirely in what you get for the money.

24-Month TCO

At 24 months, agentic AI is cost-comparable to both alternatives while delivering more than twice the operational coverage. The compounding benefit of an improving agent (routing accuracy increases, hygiene loops get smarter) starts to show in output quality metrics.

36-Month TCO

At 36 months, the full five-agent agentic system is the highest absolute cost, but it's delivering 3.5x more operational coverage than the FTE model and 7x more than managed services, while improving continuously.

The correct question at 36 months isn't "which is cheapest?" It's "which produces the highest revenue impact?"

ROI by Company Size

The ROI case for agentic AI strengthens as ARR and RevOps complexity increase. Here's how the numbers shift across company sizes.

£2M–£5M ARR

Typical RevOps profile: 1 part-time ops resource, 500–1,500 inbound leads/month, HubSpot implementation under 18 months old.

Best fit: Single-agent deployment (RevOps Agent only). Blueprint + one agent at approximately £6,500/month ongoing.

At this ARR, the ROI case is good but not immediate. Year 2 is where it becomes compelling.

£5M–£10M ARR

Typical RevOps profile: 1–2 dedicated RevOps resources, 1,500–4,000 inbound leads/month, complex multi-stage lifecycle.

Best fit: Three-agent deployment (RevOps + BI + Lifecycle). Blueprint + three agents at approximately £9,400/month ongoing.

This is the highest-ROI band. Enough complexity to benefit from multiple agents, enough volume for the efficiency gains to compound quickly.

£10M–£20M ARR

Typical RevOps profile: 3–5 RevOps team members, 4,000–10,000+ leads/month, multi-product or multi-segment GTM.

Best fit: Full five-agent system. Blueprint + five agents at approximately £14,400–£15,400/month ongoing.

At £10M+ ARR, the ROI case is compelling enough that the decision is less about whether to deploy and more about deployment sequence and governance.

The Hidden Costs Nobody Puts in the Spreadsheet

Beyond the direct cost comparisons, there are five categories of cost that consistently get missed, and that consistently change the outcome of the analysis.

1. The Cost of Slow Lead Response

The data on lead response time is unambiguous. Leads contacted within 5 minutes of submission are 100x more likely to convert than those contacted after 30 minutes (Harvard Business Review, widely replicated). Most B2B SaaS companies at £5M–£15M ARR are responding to leads in 2–6 hours.

At 2,000 inbound leads per month with a 3% conversion rate and £15,000 average contract value, improving response time from 4 hours to 15 minutes can produce a measurable uplift in conversion:

Estimated revenue impact at 20% conversion improvement: £180,000/year

Human routing systems, whether FTE or agency, cannot reliably achieve a sub-15-minute response at scale. Agents can.

2. The Cost of Data Degradation

CRM data quality degrades at approximately 20–25% per year without active hygiene (contact details become outdated, companies change, and email addresses bounce). A CRM with 10,000 contacts loses 2,000–2,500 usable records annually without intervention.

The downstream cost of poor data quality across lead scoring, campaign targeting, pipeline forecasting, and sales prioritisation is difficult to quantify precisely but consistently estimated at 10–15% of potential revenue in affected processes.

For a £7.5M ARR company with 30% of revenue flowing through marketing-influenced leads: potentially £225,000–£337,500 in annual revenue impact from data quality alone.

FTE and agency models address this periodically. Agents address it continuously.

3. The Cost of Inconsistent Execution

When humans execute RevOps processes, performance varies by day of week, workload, and individual. The lead routing accuracy variance between best-day and worst-day performance in human-executed systems is typically 15–20 percentage points.

At 2,000 leads/month with 15% routing inaccuracy versus 3% agent inaccuracy, the delta is 240 misrouted leads per month. At even a 10% recovery rate on misdirected leads and £15,000 ACV: £432,000/year in recoverable pipeline.

4. The Opportunity Cost of Strategic Capacity

Perhaps the most significant hidden cost is what your RevOps team cannot do when they're buried in execution work.

A RevOps Manager spending 70% of their time on operational execution has 30%, roughly 5–6 hours per week, for strategic work. In an agentic model, they have 70–80% for strategic work.

Over a year, that's the difference between 260 hours of strategic RevOps work and 1,040 hours. What does 780 additional hours of strategic capacity produce? Better process architecture, faster GTM improvements, higher-quality stakeholder relationships, and the insights that drive the most valuable operational changes.

This is genuinely difficult to put a number on, but it's likely the largest single value driver in the decision.

5. The Cost of Delayed Competitive Intelligence

Companies running quarterly manual competitive research miss an average of 6–8 significant competitor moves per quarter. Each missed move that reaches a sales call without a prepared response costs an estimated 0.5–2% of the deal conversion rate on affected opportunities.

For a £7.5M ARR company with £4M in active pipeline, a 1% conversion improvement from better competitive intelligence represents £40,000 in recovered pipeline per quarter.

When Each Option Wins

The honest answer is that no single option is universally right. Here's when each model makes sense.

When Hiring an FTE Wins

• You're below £2M ARR, and a RevOps Agent wouldn't generate enough volume to justify the investment
• Your processes are undocumented, and you need a human to design them from scratch before automating
• You're building a RevOps function for the first time and need someone to manage stakeholders, build relationships with sales, and design the operating model
• Your GTM is changing rapidly (new market entry, product pivot, sales model change) and requires constant human judgment and adaptation
• You have an internal technical resource available to govern an agentic system and want to explore building in-house

When Managed Services Wins

• You need senior strategic RevOps expertise for a specific project (CRM migration, attribution redesign, territory modelling) that requires high-skill execution over a defined period
• You're between 0 and 12 months into your HubSpot implementation and need expert guidance to build it correctly before adding automation
• You have an internal RevOps person who needs expert backup on strategic projects but can handle operational execution themselves
• You want to test the ROI of better RevOps before committing to infrastructure investment
• Your operational volume is low (under 500 inbound leads/month), and a periodic-touch model is sufficient

When Agentic AI Wins

• You're at £3M+ ARR with 500+ inbound leads/month and growing
• Your CRM has 12+ months of history with reasonable data quality
• Your core RevOps processes are documented (or you're willing to document them as part of deployment)
• Operational consistency matters; you need the same standard of execution at 2 pm on Tuesday and 2 am on Sunday
• Your RevOps team is capacity-constrained and spending the majority of their time on execution rather than strategy
• You're planning to scale and want operational infrastructure that scales with you without linear headcount increases

How to Build Your Own Business Case

Use this five-step framework to build the ROI model for your specific situation.

Step 1: Quantify Your Current Manual RevOps Cost

Track your team's time across five categories for two weeks: CRM operations, reporting, lead management, campaign execution, and competitive research. Apply your loaded hourly rate (total annual comp ÷ 1,750 hours) to get a weekly operational cost.

Formula: Weekly manual hours × loaded hourly rate × 52 = Annual manual operations cost

Example: 35 hours/week × £55/hour × 52 = £100,100/year

Step 2: Calculate Your Lead Response Impact

Find your current average lead-to-response time. Estimate your monthly inbound lead volume and current lead-to-opportunity conversion rate. Use a conservative 15% conversion improvement assumption for sub-15-minute response versus your current average.

Formula: Monthly leads × conversion rate uplift × ACV × 12 = Annual revenue impact

Example: 2,000 leads × 0.5% uplift × £15,000 ACV × 12 = £1,800,000 potential (at scale, use 10–15% of this as a conservative estimate)

Step 3: Estimate Your Data Quality Cost

If your CRM has over 12 months of history without consistent hygiene, assume 15–20% of records have quality issues affecting scoring, routing, and campaign targeting. Estimate the downstream revenue impact at 5% of the marketing-influenced pipeline.

Step 4: Build the Three-Option Comparison

Use the cost structures in this article, adjusted for your team size and ARR band. Build 12, 24, and 36-month scenarios for each option. Include ramp costs, attrition provisions, and escalation buffers for FTE and agency options.

Step 5: Add the Strategic Capacity Value

Estimate the current strategic capacity of your RevOps team (hours per week on non-operational work). Calculate the uplift from moving to an agentic model (typically 2–3x more strategic hours). Assign a conservative value to that additional strategic capacity based on the GTM improvements it could enable.

The combination of operational cost savings, revenue impact from improved response times and data quality, and strategic capacity unlocked typically produces an ROI case that's compelling at £3M+ ARR and becomes increasingly powerful at £5M–£10M ARR.

Frequently Asked Questions

What is the ROI of agentic AI for RevOps compared to hiring an FTE?

Over a 12-month period, costs are comparable; a fully loaded RevOps FTE in the UK costs £95,000–£127,000 per year, while a three-agent agentic system (Blueprint + monthly operation) costs approximately £125,000 in Year 1.

The ROI difference comes from output: the agentic system provides 3,100+ hours of operational coverage at consistent quality versus 1,100 hours (ramp-adjusted) from a new hire, with 24/7 availability and continuously improving performance.

For most teams at £5M+ ARR, positive ROI versus the FTE model is typically demonstrated by month 9–12.

How much does it cost to deploy agentic AI for RevOps?

The initial Blueprint phase (architecture, documentation, first agent configuration, MCP connectivity setup) costs £12,500 and takes 4–6 weeks.

Ongoing agent operation starts from approximately £6,500/month for a single-agent deployment, rising to £14,400–£15,400/month for a full five-agent system.

Total Year 1 cost for a three-agent deployment (the most common starting configuration for £5M–£10M ARR companies) is approximately £125,000.

At what ARR does agentic AI become cost-justified for RevOps?

Based on ARISE GTM client data, the ROI case becomes clearly positive at £3M+ ARR for single-agent deployments and most compelling at £5M–£15M ARR for three-to-five agent systems.

Below £2M ARR, the volume of inbound leads and operational complexity is often insufficient to generate the efficiency gains needed to justify the investment.

Above £20M ARR, the strategic impact of multiple agents operating as an integrated system typically produces the strongest ROI.

What are the hidden costs in RevOps ROI comparisons?

The five most commonly missed costs are: the revenue impact of slow lead response (leads contacted after 4+ hours convert at 50–70% lower rates than leads contacted in under 15 minutes), the downstream impact of data quality degradation (estimated at 10–15% of potential revenue in affected processes), the cost of execution inconsistency (routing errors, missed follow-ups, variable report quality), the opportunity cost of strategic capacity consumed by operational execution, and the revenue impact of delayed competitive intelligence reaching sales teams.

How does agentic AI ROI compare to managed RevOps services?

At 12 months, costs are roughly equivalent, and both typically fall in the £110,000–£125,000 range for mid-market B2B SaaS companies. The key difference is operational coverage: a managed services retainer at £8,000–£10,000/month provides 40–60 consultant hours, covering approximately 30% of total RevOps operational requirements. A three-agent agentic system at a comparable cost provides 3,100+ hours of operational coverage, running 24/7.

At 36 months, managed services tend to be slightly lower in absolute cost but produce significantly less operational throughput and no compound improvement in agent performance.

How do you calculate the ROI of faster lead response times?

Start with your current average lead-to-response time and monthly inbound lead volume. Apply the well-documented conversion rate improvement for faster response (leads contacted in under 5 minutes convert at materially higher rates than those contacted after 2+ hours).

Use a conservative 10–15% conversion rate uplift assumption for moving from 4+ hours average response to under 15 minutes. Multiply by monthly lead volume, your lead-to-opportunity conversion rate, and average contract value.

For a company receiving 2,000 inbound leads per month at 3% lead-to-opportunity conversion and £15,000 ACV, a 15% conversion improvement represents approximately £162,000 in additional annual pipeline.

What should I include in a 36-month RevOps TCO model?

A complete 36-month model should include: direct personnel or retainer costs (including employer NI, pension, and benefits for FTEs); recruitment and replacement costs (at least one full cycle for FTEs over 36 months); productivity ramp costs (6–10 months of sub-full output for new hires); escalation and overrun provisions (15–20% of base costs for agency models); operational coverage comparison (hours of work delivered at what quality level); compound improvement trajectory (how does performance change over 36 months?); and strategic capacity unlocked (what does your team do with time freed from execution work?). Most organisations underweight the last two factors, which are typically the most significant value drivers.

Is the ROI case for agentic AI different for PLG vs sales-led B2B SaaS companies?

Yes. For product-led growth (PLG) companies, the Lifecycle and BI agents typically generate the strongest initial ROI; the volume of product signups, activation events, and expansion signals requires continuous monitoring and sequencing that agents handle well.

For sales-led companies, the RevOps and GTM Strategy agents tend to dominate early ROI through lead routing, deal velocity improvement, and consistent methodology application.

Both models benefit from the Competitive Intelligence agent, though the use case in PLG skews more toward pricing and packaging intelligence versus traditional deal-level competitive responses in sales-led motions.

Ready to build your own ROI model? Take our 3-minute Agentic GTM Readiness Assessment to get a personalised ROI estimate based on your team size, ARR, and current RevOps maturity.

Take the Readiness Assessment →

Published by Paul Sullivan, February 2026. Paul is the founder of ARISE GTM, a HubSpot Platinum Partner specialising in agentic AI for B2B SaaS revenue teams, and author of Go-To-Market Uncovered (Wiley, 2025).