Dublin: using forecasts to decide how many staff to roster
Dublin Airport's clearest AI story is short-term passenger forecasting tied to capacity planning. A vendor-reported contact-centre system remains a secondary, less independently established claim.
Terminal 2 at Dublin Airport. Photograph: Doyler79 / CC BY 3.0 (cropped to fit). Shows the airport, not an AI implementation.
The picture at Dublin
A forecast that reaches the roster
Airport operators cannot move security lanes or recruit extra staff when a wave of passengers has already arrived. Dublin's capacity planning work uses passenger forecasts to inform the staffing plan before that pressure becomes visible.
The airport's head of capacity planning described this as a leading AI use in February 2026. A Transportation Research Board case study also connects prediction models with staff rostering, providing more operational context than a generic AI announcement.
An undated supplier case study describes an AI contact-centre installation, but the current evidence is not strong enough to place that beside forecasting as an equally mature airport programme.
Selected implementations
The capacity-planning use worth following
01 / Deployed
Putting passenger demand into a staff roster
The operational problem
Workforce plans made from historic averages may fail when departures create short-term spikes at processing points.
What the sources report
Airport World reported a February 2026 account from Dublin Airport's capacity planning lead describing AI short-term forecasting. A TRB case study says daa prediction models feed directly into staff rostering.
Why it matters
Linking a forecast to an actual staffing decision makes this more substantive than a model demonstration.
What remains unproven
Forecast accuracy and a measured change in passenger waiting time or staffing efficiency are not published in the current evidence.
Evidence supports a reported claim; it does not automatically establish a measured operating benefit.
The wider register
What else is happening at Dublin?
3CLogic describes an AI contact-centre solution used by daa in an undated case study, but the record is reported_unverified. It belongs in the wider register pending dated buyer-side confirmation and outcome evidence.
3CLogic AI contact centre on ServiceNow at Dublin Airport, vendor-reported · Reported · unverified
3CLogic says in an undated case study that Dublin Airport operator daa uses its AI contact-centre software inside ServiceNow, with an intelligent phone menu, automated ticket creation and SMS.
Evidence supports a reported claim; it does not automatically establish a measured operating benefit.
An operating decision, not a model score
Dublin's strongest claim is the connection between prediction and a roster someone actually uses.
The next reporting step is to establish whether that changed waiting times, overtime or staff utilisation, and against which baseline.
Live data from the Aerostack register. Status reflects published evidence only. See Our approach for how records are graded.
Aerostack register · 2 tracked deployments
Aerostack tracks AI deployments across airports and airlines, with the published evidence behind each record. Photography is real aviation imagery. Record thumbnails may show the named airport or airline; other photographs do not.
