Sample report · Workforce AI Exposure Audit

Where AI will change your workforce, and what to do about it

Harbourview Distribution Ltd

A role-by-role and task-by-task assessment of 94 people in 20 roles, with the capacity at stake, your organisation's readiness and a 12-month path forward.

Prepared by Ewort Atkinson, MBAWorkforce & TVET researcher · AI Proof Careers Hub

Sample report for a fictional organisation · 24 September 2026 · Prepared for the Harbourview executive team

Organisation AI Exposure Index
49.4/100
Moderate exposure

Headcount-weighted across 20 roles. 37.2% of people are in High-exposure roles.

Hours at stake
3,202per month · ≈18.5 FTE
High-exposure roles
35people · 37.2% of workforce
AI readiness
38/1008 leaders surveyed
Work AI can do or speed up
64%of mapped task hours
01 · Executive summary

What leadership needs to know

Harbourview is not facing an AI problem across the whole business. It is facing one in the office. Your warehouse, fleet and field teams do work that current AI barely touches. Your contact centre, finance and HR administration teams spend most of their week on exactly the templated, screen-based work AI tools now handle well.

Across the business that adds up to roughly 3,200 hours a month, the equivalent of about 18 full-time people, spent on work AI can absorb or speed up. That is not a case for cutting 18 jobs. It is capacity you are already paying for, and it can be moved into things your customers notice: faster issue resolution, proactive account care, tighter collections and better stock accuracy.

The risk is the gap between exposure and readiness. Readiness scored 38 out of 100, with no AI-use policy in place, so staff are likely already using public AI tools with customer data. The first 90 days should close that gap: set the rules, run one well-measured pilot in the contact centre, and train the people whose work is changing first.

Our recommendations

  1. Approve an AI-use policy and an approved-tools list within 30 days. It is the cheapest risk reduction available to you.
  2. Pilot AI reply drafting and order-status automation with one contact-centre team, measured against today's handling time and quality scores.
  3. Train the 35 staff in High-exposure roles first, and involve them in redesigning their roles so the change is done with them, not to them.
  4. Decide now where freed capacity goes (collections, retention calls, stock accuracy) so the time saved shows up in results, not idle time.
  • 37.2% of the workforce (35 people) work in High-exposure roles. Exposure is highest in Customer Service (index 72.5).
  • About 3,202 hours a month of current work, roughly 18.5 full-time equivalents, can be absorbed or accelerated by today's AI tools.
  • The single largest opportunity is process routine order status requests (Customer Service Representative, 12 people): about 332 hours a month.
  • Organisational AI readiness is 38/100. The weakest area is Governance & risk (20): no AI-use policy. Staff may already be pasting customer or company data into public AI tools.
  • Customer Service, Finance, Human Resources, Marketing sit in the Act now quadrant: highly exposed and not yet ready.
  • 44.7% (42 people) do hands-on, relationship or judgement-heavy work that current AI barely touches. That is a stable core to build around.
AI Exposure Index
49.4/100

Moderate exposure

Hours at stake
3,202/mo

≈18.5 full-time equivalents

People in High-exposure roles
35

37.2% of the workforce

AI readiness
38/100

8 leaders surveyed

02 · Where to act first

Exposure against readiness, by department

Each bubble is a department, sized by headcount. Highly exposed departments that aren't ready for AI (top left) need attention first.

ACT NOWACCELERATEBUILD FOUNDATIONSSUSTAIN 00252550507575100100 AI readiness → AI exposure → Operations 43Customer Service 24Sales 9Finance 8Human Resources 3Marketing 2IT 2Facilities 2Health & Safety 1

Act now

High exposure, low readiness. The work is changing and the team isn't set up for it yet.

Customer Service · Finance · Human Resources · Marketing

Accelerate

High exposure, good readiness. Ready to pilot AI in these workflows now.

IT

Build foundations

Lower exposure, low readiness. Less urgent, but basic AI skills and policy still apply.

Operations · Sales · Facilities · Health & Safety

Sustain

Lower exposure, good readiness. Keep skills current and share good practice.

No departments
03 · Department view

Exposure heatmap

Sorted by the hours of work AI can absorb or accelerate in each department.

DepartmentPeopleExposureHours at stake / moTask mixReadinessPriority
Customer Service2472.51,34423Act now
Operations4333.373827Build foundations
Finance871.351443Act now
Sales945.830640Build foundations
Human Resources360.711344Act now
Marketing258.08142Act now
IT252.05653Accelerate
Facilities228.02838*Build foundations
Health & Safety132.02338*Build foundations
AutomateAI-assistedHuman-led* No department response; organisation score used
04 · The work itself

Which tasks AI will change

Every task your teams listed was assessed individually. This is where the hours are.

22%Automate: AI can do most of it today, with a person checking
42%AI-assisted: faster and better with AI, still owned by a person
36%Human-led: presence, dexterity, trust or accountable judgement

Share of the task hours your teams described. Hours at stake assume the listed tasks fill 80% of the week and that AI absorbs 60% of “automate” task time and 25% of “AI-assisted” task time.

Ten biggest opportunities

  1. Process routine order status requests332hrs/moCustomer Service Representative · 12 people · Automate
  2. Answer standard customer emails using templates278hrs/moCustomer Service Representative · 12 people · Automate
  3. Look up stock availability in the system166hrs/moCall Centre Agent · 10 people · Automate
  4. Load and check goods against the manifest137hrs/moDelivery Driver · 18 people · AI-assisted
  5. Log call notes after each call125hrs/moCall Centre Agent · 10 people · Automate
  6. Take inbound phone orders from retailers121hrs/moCall Centre Agent · 10 people · AI-assisted
  7. Prepare weekly sales activity reports117hrs/moSales Representative · 8 people · Automate
  8. Follow scripts for returns and refunds104hrs/moCall Centre Agent · 10 people · AI-assisted
  9. Collect signatures and cash on delivery103hrs/moDelivery Driver · 18 people · AI-assisted
  10. Report vehicle faults to the fleet office103hrs/moDelivery Driver · 18 people · AI-assisted
05 · Readiness

Is the organisation ready to act?

From the AI Readiness Pulse completed by 8 leaders. Scores run from 0 to 100.

38/100

Overall readiness

Governance & risk

20

No AI-use policy. Staff may already be pasting customer or company data into public AI tools.

Skills & learning

38

Few staff have used AI tools at work, and there is no structured way to build the skill.

Data & tools

39

Core processes run on paper, email or disconnected spreadsheets, which limits what AI can plug into.

Leadership & strategy

41

No agreed direction on AI. Staff hear mixed messages and pilots stall without a sponsor.

Culture & change

52

Teams are open to changing how they work and trust leadership to handle it fairly.

06 · Role profiles

What changes in each exposed role

Every role scoring Moderate or High, ordered by hours at stake. Lower-exposure roles are listed in the appendix.

Customer Service Representative

Customer Service · 12 people

72High
Hours at stake772/month
Most exposedAnswering standard emails using templates
TaskTimeAI impact
Process routine order status requestsAI queries order system and drafts status; person confirms before sending.33%Automate
Answer standard customer emails using templatesLLMs draft replies from templates; person reviews and sends.28%Automate
Update customer records in the CRMAI suggests data entry from emails; rep verifies and updates CRM.22%AI-assisted
Escalate complex complaints to supervisorsAI flags complaint severity and suggests resolution; rep makes escalation call.17%AI-assisted
What changes

Routine email and order replies will be AI-drafted and checked rather than written from scratch, cutting response time. Reps will shift from template-filling to reviewing AI outputs and owning complex complaints.

Future-state role

This role becomes a quality-gate and relationship role: reviewing AI-drafted replies for tone and accuracy, handling customers who need human judgment, and spotting patterns in complaints to improve service. Stronger performers will move into account retention, upsell and supervisor-level complaint resolution.

Skills to build

Call Centre Agent

Customer Service · 10 people

76High
Hours at stake517/month
Most exposedTaking inbound orders and logging call notes
TaskTimeAI impact
Take inbound phone orders from retailersAI drafts order summaries and flags issues; agent owns order acceptance and relationship.35%AI-assisted
Follow scripts for returns and refundsAI suggests refund path; agent owns dispute resolution, judgment and customer trust.30%AI-assisted
Look up stock availability in the systemReal-time system queries return stock data; agent verifies complex scenarios or holds.20%Automate
Log call notes after each callAI transcribes calls and auto-logs notes; agent reviews and approves for accuracy.15%Automate
What changes

Routine data entry and script-following will shift to AI; agents will spend more time resolving exceptions, handling difficult callers, and building retailer relationships. Call handling will accelerate, freeing time for higher-value account care and problem-solving.

Future-state role

Call centre agents will focus on complex order issues, customer retention, retailer relationship building, and coaching AI on edge cases. The role becomes a hybrid—part AI operator, part account strategist—with less time on clerical work and more on judgment calls.

Skills to build

Accounts Payable Clerk

Finance · 4 people

76High
Hours at stake294/month
Most exposedEntering supplier invoices into accounting system
TaskTimeAI impact
Match invoices to purchase ordersAI matches invoices to POs by line items; clerk resolves mismatches and discrepancies.30%Automate
Enter supplier invoices into the accounting systemOCR and AI extract invoice data; clerk verifies and approves posting.25%Automate
Prepare the weekly payment run listAI compiles approved invoices into payment list; clerk reviews, prioritizes, authorizes.25%Automate
Answer supplier payment queries by emailAI drafts replies to routine queries; clerk personalizes and sends complex resolutions.20%AI-assisted
What changes

Routine invoice entry and matching will shift to AI, freeing the clerk from data keying. The role will focus on exception handling, supplier relationship queries, and payment governance rather than transaction volume.

Future-state role

The Accounts Payable Clerk becomes an AP Analyst, owning invoice exceptions, dispute resolution, and supplier payment performance. They partner with procurement on payment terms and cash-flow forecasting, using automation to handle the routine 80% of volume.

Skills to build

Sales Representative

Sales · 8 people

48Moderate
Hours at stake277/month
Most exposedEntering orders and preparing sales reports
TaskTimeAI impact
Visit supermarket and pharmacy accounts to take ordersPhysical visits, in-person relationship building, observing shelf conditions required.41%Human-led
Negotiate shelf placement and promotionsAI analyzes competitor shelving, planograms, promotion data; rep owns final decisions.29%AI-assisted
Prepare weekly sales activity reportsAI pulls sales data, generates report structure; rep reviews and personalizes insights.18%Automate
Enter orders into the sales systemAI captures order details from photos or voice; rep verifies and submits.12%Automate
What changes

Order entry and reporting shift from manual keying to AI-drafted outputs the rep validates in minutes. Field time stays on visits and relationships, but reps spend less time at desks on admin.

Future-state role

Sales reps become account strategists: using AI to handle data entry and activity logging, they invest time in deeper customer relationships, negotiating better shelf space and promotions, and spotting growth opportunities in account data AI surfaces. The role strengthens around consultative selling and account planning.

Skills to build

Inventory Clerk

Operations · 4 people

74High
Hours at stake216/month
Most exposedRecording goods and running daily stock reports
TaskTimeAI impact
Reconcile cycle counts against system figuresAI flags discrepancies and suggests root causes; clerk investigates and resolves.35%AI-assisted
Record goods received into the inventory systemAI can parse delivery docs and pre-fill forms; clerk verifies and confirms entry.25%AI-assisted
Run daily stock level reportsDaily reports fully generated by system query; clerk reviews exceptions and exports.20%Automate
Email reorder alerts to purchasingReorder alerts auto-triggered by thresholds; clerk reviews, approves and sends via template.20%Automate
What changes

Routine data entry and report generation will shift to AI, freeing the clerk from daily paper-pushing. The role will focus on investigating exceptions, validating AI outputs, and ensuring inventory accuracy rather than manual recording.

Future-state role

The Inventory Clerk will become an inventory analyst, responsible for investigating stock discrepancies, improving cycle-count accuracy, and using data insights to advise purchasing on reorder patterns and slow-moving stock. They will own the quality and integrity of automated processes and escalate anomalies for root-cause action.

Skills to build

Accounting Clerk

Finance · 3 people

76High
Hours at stake191/month
Most exposedEntering invoices and receipts into software
TaskTimeAI impact
Reconcile bank statements monthlyAI flags mismatches and suggests fixes; clerk owns reconciliation decision.40%AI-assisted
Enter invoices and receipts into accounting softwareOCR and AI invoice capture extract data; clerk verifies and submits.35%Automate
Prepare standard financial summariesAI generates standard reports from GL data; clerk reviews and releases.25%Automate
What changes

Routine data entry and report generation shift to AI; the clerk's week refocuses on exception handling, verification and control oversight. Manual invoice keying nearly disappears, replaced by validation of automated captures.

Future-state role

The Accounting Clerk becomes a process quality controller and financial analyst, reviewing AI-captured invoices and reconciliation exceptions, analysing variances, and advising on control gaps. They own the accuracy and completeness of the automated pipeline rather than executing it by hand.

Skills to build

HR Administrator

Human Resources · 2 people

72High
Hours at stake94/month
Most exposedUpdating employee records in HR system
TaskTimeAI impact
Schedule interviews and send offer lettersAI schedules slots, drafts letters; admin confirms, personalises and sends officially.30%AI-assisted
Update employee records in the HR systemAI drafts updates; HR admin reviews, verifies and submits to system.25%AI-assisted
Answer staff questions about leave policyAI chatbot answers policy questions 24/7; escalates complex cases to admin.25%Automate
Prepare payroll change formsAI generates form templates and calculations; admin checks accuracy and compliance.20%AI-assisted
What changes

Routine data entry and form completion shift to AI drafting, freeing the HR Administrator to focus on policy interpretation, candidate experience and employee relations. The role evolves from transaction processing to quality control and human touchpoints.

Future-state role

The HR Administrator becomes a people experience specialist, owning interview quality, offer communication, policy guidance for edge cases and data governance. They configure and monitor AI tools, handle exceptions and invest saved time in employee engagement and process improvement.

Skills to build

Marketing Coordinator

Marketing · 2 people

58Moderate
Hours at stake81/month
Most exposedWriting social media posts for brand partners
TaskTimeAI impact
Compile monthly campaign performance reportsAI pulls campaign data, builds charts and summaries; coordinator verifies and contextualizes.30%Automate
Write social media posts for brand partnersAI drafts posts; coordinator refines tone, brand voice, partner approval needed.25%AI-assisted
Coordinate in-store promotion schedulesRequires phone calls, emails, in-store visits and stakeholder negotiation and trust.25%Human-led
Design promotional flyers in CanvaAI suggests layouts and copy in Canva; coordinator owns design choices, brand fit.20%AI-assisted
What changes

Social media drafting and report assembly will become faster and data-driven, freeing the coordinator to focus on partner relationships and creative campaign strategy. In-store scheduling will remain hands-on but the coordinator will have more time to manage conflicts and grow those partnerships.

Future-state role

The Marketing Coordinator becomes a campaign strategist and partner relationship manager, using AI to handle content drafting and reporting dashboards while owning creative direction, brand alignment and in-store execution. They shift from task-heavy production to higher-value partnership, negotiation and campaign insight work.

Skills to build

IT Support Technician

IT · 2 people

52Moderate
Hours at stake56/month
Most exposedPassword resets and account unlocks from tickets
TaskTimeAI impact
Troubleshoot printer and network issues in personIn-person diagnostics, physical repairs, hands-on testing and user trust require technician presence.40%Human-led
Set up laptops and phones for new staffAI checklists and config templates speed setup; technician must physically handle devices, test.25%AI-assisted
Document fixes in the help-desk knowledge baseAI drafts summaries and suggested KB entries from ticket data; technician reviews, edits, approves.20%AI-assisted
Reset passwords and unlock accounts from ticketsAI can generate reset/unlock commands; technician verifies and executes via ticketing system.15%Automate
What changes

Routine password resets and basic provisioning shift to automated workflows with AI drafting; technician time reallocates to complex on-site troubleshooting, user enablement and knowledge-base curation. Help-desk backlog shrinks, freeing capacity for proactive maintenance and security hardening.

Future-state role

IT Support Technician becomes a hybrid diagnostician and automation owner: handling escalated, complex field issues and managing the exceptions that routine-ticket automation cannot resolve. Increased focus on user enablement, network resilience and security posture rather than volume-driven resets.

Skills to build

Customer Service Supervisor

Customer Service · 2 people

58Moderate
Hours at stake55/month
Most exposedCompiling weekly service-level reports
TaskTimeAI impact
Listen to call recordings and coach agentsAI transcribes, flags coaching moments; supervisor listens selectively, coaches.35%AI-assisted
Compile weekly service-level reports for the operations managerAI pulls data, drafts reports; supervisor validates, contextualizes findings.25%AI-assisted
Build and approve shift rostersAI suggests schedules around constraints; supervisor approves, handles exceptions.20%AI-assisted
Handle escalated customer complaintsRequires judgment, empathy, accountability; trust-building cannot be delegated to AI.20%Human-led
What changes

Routine reporting and scheduling shift to AI-generated drafts; the supervisor spends less time on data entry and more on listening to calls and coaching high-impact moments. Escalated complaints remain entirely human-owned but are informed by better upfront data.

Future-state role

The supervisor becomes a coaching and people leader who uses AI dashboards and call highlights to spot coaching opportunities, rather than manually reviewing hours of recordings. They own escalations and team performance improvement, empowered by AI-prepared insights.

Skills to build

Operations Manager

Operations · 1 person

62Moderate
Hours at stake39/month
Most exposedCompiling weekly performance reports in Excel
TaskTimeAI impact
Coordinate delivery schedules across depotsAI suggests optimised schedules; manager owns depot constraints, customer commitments, exceptions.35%AI-assisted
Compile weekly performance reports for directorsAI drafts reports from data; manager validates, interprets trends, adds context.30%AI-assisted
Prepare PowerPoint decks for monthly reviewsAI generates slides from reports; manager curates narrative, sets tone, approves messaging.20%AI-assisted
Summarise team status updates for management meetingsAI summarises written updates; manager synthesises for audience, adds decisions.15%AI-assisted
What changes

Weekly reporting shifts from manual data gathering to rapid AI-drafted synthesis that the manager refines and validates. Coordination work moves from spreadsheet wrangling to exception-handling and relationship management around AI-suggested schedules.

Future-state role

Operations Manager becomes a data interpreter and strategic co-ordinator: reviewing AI-generated plans and reports for feasibility and risk, making accountable decisions on schedule trade-offs, and investing freed time into depot relationships, team development and supply chain resilience planning.

Skills to build

Financial Controller

Finance · 1 person

38Moderate
Hours at stake28/month
Most exposedReviewing and signing off monthly management accounts
TaskTimeAI impact
Review and sign off the monthly management accountsAI drafts variance analysis and account reconciliations; controller reviews, judges and signs off.31%AI-assisted
Coach the finance team on month-end closeAI generates process guides and common-error summaries; controller delivers coaching and feedback.25%AI-assisted
Present cash-flow forecasts to the boardAI refreshes forecast models and sensitivities from live data; controller interprets and presents.25%AI-assisted
Negotiate credit terms with the bankNegotiation requires trust, judgment and accountable decision-making with bank counterparty.19%Human-led
What changes

Monthly close will shift from manual data compilation to AI-assisted variance analysis and exception handling, freeing the controller to focus on forecasting, board communication and team development. Routine reconciliations and account reviews will be drafted and flagged by AI, cutting close cycle time and improving audit readiness.

Future-state role

The Financial Controller becomes a strategic finance partner who owns cash-flow forecasting, board-level insights and team capability—delegating transaction validation and routine close tasks to AI-augmented workflows. The role strengthens around business advising, stakeholder negotiation and leading the finance function through process automation.

Skills to build

HR Manager

Human Resources · 1 person

38Moderate
Hours at stake19/month
Most exposedDesigning annual training plan content
TaskTimeAI impact
Design the annual training planAI identifies skills gaps from data, drafts curricula, and tracks ROI; manager designs strategy and content.35%AI-assisted
Lead disciplinary and grievance hearingsDisciplinary hearings require in-person presence, trust, and accountable decision-making authority.25%Human-led
Advise managers on difficult employee situationsAI drafts scenario analyses and precedent summaries; manager owns the advice and judgment.20%AI-assisted
Negotiate with the union representativeUnion negotiation requires in-person presence, relationship trust, and accountability for binding decisions.20%Human-led
What changes

This HR Manager will spend less time on administrative prep (document gathering, compliance checking, training schedule logistics) and more on complex people decisions, coaching managers through difficult situations, and analysing training ROI and workforce trends. Disciplinary and negotiation work remain fundamentally in-person but will be better prepared with AI-generated risk assessments and pr

Future-state role

The strengthened HR Manager will shift from operational task management to strategic people partnering: designing interventions based on workforce analytics, coaching managers and leaders through complex employment situations, and building training strategies tied to business outcomes rather than calendar. AI handles compliance documentation, initial case summaries, and training logistics, freeing

Skills to build
07 · Reskilling pathways

The skills to build, and where to build them

Grouped by skill theme, largest need first. Providers are checked and current as of this report. Confirm intake dates and costs with each provider.

60 people · 13 roles

AI productivity for everyday work

Using AI assistants to draft, summarise, research and check work safely, including prompt technique, verifying outputs and data-handling rules.

For: Delivery Driver, Forklift Operator, Sales Representative, Inventory Clerk, Warehouse Supervisor, Fleet Mechanic, HVAC Technician, HR Administrator, IT Support Technician, Financial Controller, Director of Business Development, HR Manager, Occupational Health Nurse

53 people · 7 roles

Consultative selling and account management

Letting AI handle order entry and activity reporting, and building the relationship, negotiation and account-planning skills that stay human.

For: Delivery Driver, Customer Service Representative, Call Centre Agent, Sales Representative, HVAC Technician, Marketing Coordinator, Director of Business Development

47 people · 11 roles

Data protection and internal controls

Handling customer, staff and financial data safely when AI tools are in the loop: privacy rules, approval controls, audit trails and checking AI output.

For: Customer Service Representative, Call Centre Agent, Sales Representative, Accounts Payable Clerk, Inventory Clerk, Accounting Clerk, HR Administrator, Financial Controller, Operations Manager, HR Manager, Occupational Health Nurse

  • IAPPPrivacy fundamentals and CIPP certification
  • LinkedIn LearningData privacy; internal controls; responsible AI
  • CourseraData privacy fundamentals; AI governance
44 people · 8 roles

Process automation and exception handling

Configuring, checking and improving automated workflows (invoice capture, order processing), and owning the exceptions automation can't handle.

For: Delivery Driver, Call Centre Agent, Accounts Payable Clerk, Inventory Clerk, Accounting Clerk, Customer Service Supervisor, HR Administrator, Operations Manager

39 people · 5 roles

Workplace health and safety

Strengthening the safety-critical, hands-on judgement in the role, and using digital tools for inspections, incident logs and records.

For: Delivery Driver, Forklift Operator, Warehouse Supervisor, Fleet Mechanic, Occupational Health Nurse

  • NEBOSHInternational General Certificate in Occupational Health and Safety
  • HEART/NSTA TrustOccupational safety and health programmes
28 people · 4 roles

AI-assisted customer service

Working alongside AI reply-drafting and call-summary tools, and shifting agent time to complex resolution, retention and account care.

For: Customer Service Representative, Call Centre Agent, Accounts Payable Clerk, Customer Service Supervisor

  • HEART/NSTA TrustCustomer service / customer engagement programmes (NVQ-J)
  • CourseraAI in customer service; customer experience management
  • HubSpot AcademyCustomer service and service-hub courses (free)
27 people · 9 roles

Data analysis and dashboards

Moving from keying data in to checking it, analysing it and acting on it: Excel, Power BI, basic statistics and reporting automation.

For: Sales Representative, Inventory Clerk, Accounting Clerk, Warehouse Supervisor, Fleet Mechanic, Customer Service Supervisor, Marketing Coordinator, Operations Manager, Director of Business Development

21 people · 4 roles

Advanced technical and diagnostic skills

Deepening the hands-on expertise AI can't replace, and adding digital diagnostics, smart equipment and connected-maintenance skills.

For: Forklift Operator, Fleet Mechanic, HVAC Technician, IT Support Technician

12 people · 8 roles

Leading AI-augmented teams

Redesigning roles, running AI pilots with staff, coaching through change, and reinvesting time saved on reporting into people and planning.

For: Warehouse Supervisor, Customer Service Supervisor, IT Support Technician, Financial Controller, Operations Manager, Director of Business Development, HR Manager, Occupational Health Nurse

5 people · 2 roles

Finance business partnering

Shifting finance roles from transaction processing to variance analysis, forecasting and advising the business.

For: Accounts Payable Clerk, Financial Controller

  • ACCAData analytics and business partnering CPD
  • CourseraFinancial planning and analysis (FP&A)
  • UWI Open CampusAccounting and finance continuing education
3 people · 2 roles

Modern people operations

Automating HR administration and moving HR time to employee experience, workforce planning and people analytics.

For: HR Administrator, HR Manager

2 people · 1 role

AI for marketing and content

Using AI for content, design and campaign reporting, and putting human time into strategy, brand judgement and partner relationships.

For: Marketing Coordinator

2 people · 1 role

IT service automation

Automating routine tickets (resets, provisioning) and moving IT time to security, cloud administration and user enablement.

For: IT Support Technician

08 · Roadmap

A 12-month path from audit to results

0–90 days

Set the rules and prove it works

  • Publish an AI-use policy covering approved tools, data handling and human review. Governance scored 20/100.
  • Run one pilot in Customer Service: AI support for “Process routine order status requests”. Measure time saved and quality against a baseline.
  • Give the 35 staff in High-exposure roles AI productivity training, starting with the pilot team.
  • Name an executive sponsor and a working group: HR, IT and one manager from each exposed department.
90–180 days

Redesign roles and build skills

  • Scale the pilot to the rest of the department if it hit its targets. Adjust or stop it if it didn't.
  • Redesign the most exposed roles around the future-state descriptions in this report, and agree them with staff.
  • Launch the reskilling pathways: AI productivity for everyday work; Consultative selling and account management; Data protection and internal controls.
  • Start a second pilot in the next department on the exposure–readiness matrix.
180–365 days

Redeploy capacity and re-measure

  • Move freed hours into planned priorities such as service quality, collections, account growth and new services. Track where they go.
  • Update job descriptions, performance goals and pay bands for the redesigned roles.
  • Repeat the readiness survey and re-run this audit to measure progress against the baseline.
09 · Measures of success

How you'll know it's working

Suggested targets. Agree the final numbers at the debrief.

MeasureBaseline (this audit)6 months12 months
Hours redeployed from automated or AI-assisted work0 hours/month800 hours/month (25% of the opportunity)1,921 hours/month
Staff in High-exposure roles who have completed AI training0 of 3518 of 3535 of 35
AI readiness score38/10048/10058/100
Live AI pilots with measured results024 or more
Organisation AI Exposure Index (re-audit)49.4—Re-scored; exposure is managed, not necessarily lower
10 · Method and assumptions

How this audit was produced

Scoring

  • Each role was scored 1–99 for AI exposure with the calibrated, task-based engine behind the AiProof Careers diagnostic, anchored to reference occupations.
  • Each task was then assessed individually as Automate, AI-assisted or Human-led, with an estimate of its share of the working week.
  • Organisation and department indices are headcount-weighted averages of the role scores. Bands: High 67+, Moderate 34–66, Lower ≤33.

Hours and value at stake

  • Hours at stake = people × weekly hours × 80% (the share of the week the listed tasks are assumed to cover) × task share × AI rate. The AI rate is 60% for Automate tasks, 25% for AI-assisted tasks and 0% for Human-led tasks. Converted to months at 52 ÷ 12 weeks.
  • The AI rates are planning assumptions, not measurements. Replace them with the time savings measured in your own pilots.
  • This report states impact in hours. A money value can be added on request, calculated from your loaded cost per role.
  • This is capacity that can be redirected to other work, not a projected headcount reduction.

Limitations

  • Results depend on the task descriptions supplied. Roles described in general terms score less precisely.
  • AI capability changes quickly. This is a point-in-time view, and we recommend re-auditing every 12 months.
  • AI-generated assessments were reviewed by the author, but individual task estimates are indicative rather than time-and-motion measurements.

Data handling

  • Role-level data only. No names or personal data were collected.
  • Role and task descriptions were processed through Anthropic's API solely to produce this report.
  • Source data is deleted within 30 days of delivery, in line with the engagement agreement.
Appendix

Role-by-role results

RoleDepartmentPeopleScoreBandHours / moTask mixMost exposed work
Accounts Payable ClerkFinance476High294Entering supplier invoices into accounting system
Accounting ClerkFinance376High191Entering invoices and receipts into software
Call Centre AgentCustomer Service1076High517Taking inbound orders and logging call notes
Inventory ClerkOperations474High216Recording goods and running daily stock reports
Customer Service RepresentativeCustomer Service1272High772Answering standard emails using templates
HR AdministratorHuman Resources272High94Updating employee records in HR system
Operations ManagerOperations162Moderate39Compiling weekly performance reports in Excel
Customer Service SupervisorCustomer Service258Moderate55Compiling weekly service-level reports
Marketing CoordinatorMarketing258Moderate81Writing social media posts for brand partners
IT Support TechnicianIT252Moderate56Password resets and account unlocks from tickets
Sales RepresentativeSales848Moderate277Entering orders and preparing sales reports
Financial ControllerFinance138Moderate28Reviewing and signing off monthly management accounts
HR ManagerHuman Resources138Moderate19Designing annual training plan content
Warehouse SupervisorOperations332Lower51Documenting stock discrepancies and safety incidents
Occupational Health NurseHealth & Safety132Lower23Maintaining confidential health records
Forklift OperatorOperations1428Lower53Pre-shift forklift inspection checklists
Delivery DriverOperations1828Lower343Collecting signatures and cash on delivery
Fleet MechanicOperations328Lower34Recording maintenance logs for vehicles
HVAC TechnicianFacilities228Lower28Quoting small repair jobs
Director of Business DevelopmentSales128Lower29Quarterly commercial strategy documentation
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