VOLOVLOAutomation risk & transition, task by task
AskOccupationsMajorsBusinessFoundersChangesNotesMethod
Search occupations, majors…
EN
  • English
  • 简体中文
  • 日本語
  • Español
  • Português
  • Français
VLO
VOLO

Understanding how automation changes work — task by task, with the evidence shown and the uncertainty admitted.

AskOccupationsMajorsBusinessFoundersChangesNotesMethodWill AI replace my job?AboutRole diagnosisOpen dataOntologyVOLO ProPrivacyTerms
© 2026 VOLO
Guides
Ask VOLOFor businessFor foundersRecent changesNotesRole diagnosisFirst AI experimentVOLO ProMethod & evidenceAboutFollow an occupationSearch
Occupations
All occupations
AI / software
Translator / InterpreterBank tellerCopywriterContent moderatorCustomer service representativeAdministrative assistantSoftware tester / QA engineerData entry clerkGraphic designerParalegalVideo editorAccountant / BookkeeperMarketing specialistFrontend developerTax preparer / tax agentVoice actorMedical coderData analystInsurance claims handlerTechnical writer / documentation engineerJunior software developerInsurance underwriterHR / recruiterLoan officer / credit officerFinancial analystProcurement / supply chain specialistJournalistSales / account managerReal estate agentNetwork engineerIllustratorIT support specialist / helpdeskAuditorSupply chain plannerManagement consultantPhotographerBackend developerAI researcherProduct / UX designerBusiness systems ownerE-commerce operations specialistActuaryAnimator and VFX artistWriter and authorRadiologistData engineerProject managerData scientistCourt reporterEditor and proofreaderLawyerMedical assistant / clinic assistantQuantity surveyorContent creatorQuantitative analystMachine learning engineerExperienced software engineerDevOps / platform / SRE engineerBusiness analystMusician and composerProduct managerPharmacistPartnerships / channel managerSecurity analyst (SOC)Financial adviser / financial plannerInterpreterCompliance officerLibrarianArchitectFirst-line manager / team supervisorCounsellor / therapistRetail salesperson / shop assistantCivil / structural engineerElectrical engineerIndustrial engineerSecurity guardInterior designerUniversity lecturerBus driverInsurance agentMechanical engineerSchool teacherGeneral practitioner / primary care doctorAirline pilotWaiter / restaurant serverRadiographer / radiologic technologistAuto mechanic / vehicle technicianPolice officerSonographerAircraft maintenance technicianAir traffic controllerVeterinarianPhysiotherapist / rehabilitation therapistDentistSurgeonConstruction workerSocial workerRegistered nurseCare worker / nursing assistantPlumberAI implementation lead
RPA / self-service
Government service clerkOperations coordinatorMetro train driverReceptionist / front deskPharmacy technician
Robotics
Retail cashier / shop assistantContainer port workerWarehouse workerAssembly line workerMedical laboratory technicianActor and modelWelderChef / cookCleaner / janitorFarmerFirefighterCabin crewElectrician
Autonomous driving
Ride-hail / taxi driverTruck driverDelivery rider / courier
Majors
All majorsEnglish / Foreign languagesComputer scienceAccountingPsychologyJournalism / CommunicationFinanceLawVisual communication designMarketingNursingBusiness administrationEducation and teacher trainingArchitecturePublic administrationMedicineHospitality and tourism managementEconomicsInformation systems
Enter as:I have a jobI am studyingI run a companyI am building something
Recent changes›Business analyst›2025-07-25
PilotCognitive automation2025-07-25

Language-model drafts of functional specifications cut an IT consultancy analyst's drafting time by an estimated 10–15%, but missed tacit knowledge and needed expert revision

Business analystoccupation page →
Event date / reported
2025-07-25
Evidence stage
PilotSmall-scale trial in a real setting. Tells us the deployment conditions are being tested, not that they hold — so one pilot is never enough on its own; two independent ones are.
Tasks this bears on
Eliciting requirements
Interviewing stakeholders and users to find out what they need, including what they do not think to say.
Being augmented≈ Platform inference
Writing requirements and user stories
Turning what was learned into requirement documents, specifications and user stories that developers and testers can work from.
Being augmented✓ Evidence-backed
Where this applies
One project at an IT consulting company, where language models generated functional design specifications and user stories from elicitation summaries and templates, assessed by the company's expert analyst. The analyst estimated drafting time savings of 10% to 15%; some user stories stayed unaddressed across all models because knowledge owned by analysts can be tacit and absent from the elicitation documents; and the authors conclude that the models can enhance early documentation but cannot replace human intervention, with expert analysts still needed for accuracy and completeness.
What this means
In a real consulting project, the model sped up the writing a little and left the hard part — the knowledge in the analyst's head that never reached the documents — untouched.
What it does not yet show
One project, one expert's estimate; not a measured time saving across projects.
What you can check
Open arXiv 2507.19113 and find "time savings of 10% to 15%" in the paper.
Does it change the assessment?
No. The impact index is never moved by a single event. Of the 2 linked judgements above, 0 moved from inference to evidence with this record; the other 1 already rested on earlier evidence.
Source
Pasquale, Ragone et al. (University College Dublin, University of Bari) — "Exploring the Use of LLMs for Requirements Specification in an IT Consulting Company", arXiv:2507.19113 (25 July 2025) · verified 2026-09-29 · Claude (VOLO agent) · interpreted 2026-09-29 · Claude (VOLO agent)
Primary source — published by the party that did this, or the authority of record. No co-signature needed.
All changes for Business analyst →All recent changes →How events become evidence →