Asset Living
AI agent across the whole prospect-to-resident lifecycle
In the second quarter of 2025, Asset Living communities equipped with EliseAI's Delinquency module sent more than 130,000 personalized reminders and saw on-time rent payments rise by 591 basis points, while occupancy gained 278 basis points since the start of 2025.
Key points
- Asset Living, number 2 in the NMHC ranking, deployed EliseAI's AI agents across the whole resident lifecycle.
- Leasing, payment reminders, maintenance, renewals and voice all run through a single platform.
- In Q2 2025: 591 more basis points of on-time rent payments, after 130,000 reminders.
- Evidence B: EliseAI case study, figures repeated in Asset Living's September 2025 press release.
Objective
Maintain service quality for residents and prospects during growth from 70,000 to more than 450,000 managed units, by handing repetitive exchanges (reminders, replies, routine requests) to AI agents and keeping on-site teams on the interactions that drive renewals.
The deployment
Asset Living manages more than 450,000 units for more than 500 clients in more than 40 US states, and ranks second in the NMHC Top 50 managers. The portfolio grew from 70,000 units in 2020 to more than 450,000. To absorb this growth, the group deployed the EliseAI platform across the full journey from prospect to resident: LeasingAI answers prospects and follows up with them, including evenings and weekends (nearly 50% of inquiries arrive outside business hours according to the case study), Delinquency sends residents personalized payment reminders, and the Maintenance, Renewals and VoiceAI modules take service requests, lease renewals and calls. EliseAI states that 85% of transactional communications in the resident lifecycle are automated. In the second quarter of 2025, communities equipped with the Delinquency module sent more than 130,000 reminders and saw the on-time rent payment rate rise by 591 basis points. Since the start of 2025, occupancy in equipped communities has gained 278 basis points, a gain the study attributes to continuous prospect follow-up. Asset Living's press release of September 16, 2025 repeats these figures rounded to 600 and 300 basis points. Two caveats. No isolated renewal rate is published, even though the Renewals module is part of the deployment: the effect on resident retention remains publicly unmeasured. The figures come from the vendor and the client, with no control group described. The capacity gain for teams (78.2 hours per community per month in the press release, 72 hours in the body of the case study) is an internal productivity indicator and is not retained here as a client result.
Results Proof B
A quantified case study from the vendor EliseAI, whose same results (rounded) are repeated in the official press release published by Asset Living on its own site and by EliseAI on September 16, 2025; no independent source or financial result confirms them.
How it works
Inferred typical approachThe internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.
The stack in detail
- plateforme EliseAI LeasingAI Continuous replies to and follow-up of prospects, including outside business hours
- plateforme EliseAI Delinquency Personalized payment reminders sent to residents
- plateforme EliseAI Maintenance, Renewals et VoiceAI Maintenance requests, lease renewals and voice agent on the same platform
How it runs, concretely
For ops teams-
1Handling prospects AI
LeasingAI answers incoming inquiries, including outside business hours, and follows up with lukewarm prospects until the tour or the signing.
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2Reminders on late rent AI
The Delinquency module sends residents personalized payment reminders. More than 130,000 messages in Q2 2025.
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3Routine resident requests AI
Maintenance, renewals and calls go through the text and voice agents, which handle the transactional share (85% according to EliseAI).
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4Human takeover on-site team
On-site associates keep the high-value exchanges and in-person meetings, which Asset Living links to renewals.
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5Measurement data team
Asset Living and EliseAI track occupancy, on-time rent payment rate and request resolution times by community.
Each resident's payment status and each prospect's status in the leasing journey. Without up-to-date payment data, a reminder goes to a resident who has already paid; without prospect tracking, continuous follow-up cannot be measured in occupancy.
How your customers perceive this type of use
Sourced studiesLes consommateurs n'acceptent pas les chatbots par defaut : 64% prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (Gartner, 2024) et pres d'un utilisateur sur cinq du service client par IA n'en retire aucun benefice (Qualtrics, 2025). L'acceptation se construit sur trois conditions mesurees par Salesforce : savoir qu'on parle a une IA, pouvoir escalader vers un humain, comprendre la logique de l'agent.
Acceptance conditions
- Etre informe qu'on parle a une IA et non a un humain (pres de 75% le demandent, Salesforce 2024)
- Un chemin d'escalade clair vers un agent humain (45% plus enclins a utiliser l'agent IA, Salesforce 2024)
- Une logique de l'agent clairement expliquee (44% plus enclins, Salesforce 2024)
Red lines
- Rendre l'humain injoignable : c'est la premiere inquietude des consommateurs sur l'IA dans le service client (Gartner 2024) et 50% craignent que l'IA les coupe du contact humain (Qualtrics 2025)
- Remplacer le service client par l'IA sans alternative : 53% envisageraient de partir chez un concurrent (Gartner 2024)
Sources: Salesforce 2024 · Gartner 2024 · Qualtrics 2025
How to replicate
Inference, not sourcedData prerequisites
- Property management software up to date on leases, due dates and payments, accessible to the agent
- History of prospect inquiries and their outcome, to measure occupancy before and after
- A baseline on-time rent payment rate per property
Org prerequisites
- On-site teams willing to leave reminders and routine replies to an agent
- A human takeover rule for sensitive cases (payment difficulty, dispute)
- Legal validation of the tone and content of late payment reminders
Possible stack
- AI agent platform specialized in property management, connected to the management software
- SMS, email and phone channels with a log of exchanges
- Dashboard per property: occupancy, on-time payments, resolution time
The plan, step by step
- Step 1Set the baseline: occupancy, on-time payments, response time to prospects, per property.Deliverable: Quantified baseline before deployment.
- Step 2Deploy the payment reminder module first on a group of properties, with legally validated messages.Deliverable: Automatic reminders in production and comparison with non-equipped properties.
- Step 3Add prospect handling outside business hours, then maintenance and renewals.Deliverable: Resident lifecycle covered on a single platform.
- Step 4Measure the effect on renewals separately, which the Asset Living case does not publish.Deliverable: Renewal rate by cohort, equipped and non-equipped.
First step: Measure, property by property, the on-time rent payment rate and the share of prospect inquiries arriving outside business hours, to know where an agent changes the result the most.
Sources
- S1 How Asset Living Revamped Lead Nurturing and Delinquency with EliseAI Interested party archive pending
- S2 Asset Living Advances Operational Excellence with EliseAI Partnership Primary archive pending
- S3 Asset Living Advances Operational Excellence with EliseAI Partnership (blog EliseAI) Interested party archive pending
An error, newer info, a source?
This page lives on its accuracy. If a figure has moved, if the deployment has changed, or if you have a higher-quality source, tell us. Every sourced correction is verified before publication.