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Proof B Live confirmed

Asset Living

AI agent across the whole prospect-to-resident lifecycle

IndustryReal estateLeverRetentionFamilyConversationImplementationMartech platformStagepost-purchase
Pattern proven in 11 industries still untouched in Retail & e-commerce, CPG & D2C, Tech & SaaS +2 See the pattern map
+591 bps
On-time rent payment rate in communities equipped with the Delinquency module, Q2 2025 (rounded to 600 bps in the press release)
"saw a 591 bps increase in on-time rent payments" S1

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

+591 bps
On-time rent payment rate in communities equipped with the Delinquency module, Q2 2025 (rounded to 600 bps in the press release)
"saw a 591 bps increase in on-time rent payments" S1
130 000+
Personalized payment reminders sent to residents in Q2 2025
"sending over 130,000 personalized, empathetic payment reminder messages" S1
+278 bps
Occupancy rate of equipped communities since the start of 2025, attributed to continuous prospect follow-up (rounded to 300 bps in the press release)
"have seen a 278bps overall increase in occupancy rates" S1
85%
Share of transactional communications in the resident lifecycle handled by AI
"automating 85% of transactional communications across the resident lifecycle" S1

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 approach

The internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.

demande ou echeancestatut de paiement et de bailreponse, relance, rappelcas a traiter par un humainpaiement, signature, mesure Prospect et locataire SMS, e-mail, chat ettelephone Agents IA de location,recouvrement,maintenance, EliseAI Donnees de bail, depaiement et de demandes Equipes sur site AssetLiving

The stack in detail

How it runs, concretely

For ops teams
CadenceContinuous: the agents reply at any hour, payment reminders go out at each rent due date
Operated byAsset Living's on-site teams, who take over the exchanges the AI does not handle, supported by the EliseAI platform
  1. 1
    Handling prospects AI

    LeasingAI answers incoming inquiries, including outside business hours, and follows up with lukewarm prospects until the tour or the signing.

  2. 2
    Reminders on late rent AI

    The Delinquency module sends residents personalized payment reminders. More than 130,000 messages in Q2 2025.

  3. 3
    Routine resident requests AI

    Maintenance, renewals and calls go through the text and voice agents, which handle the transactional share (85% according to EliseAI).

  4. 4
    Human takeover on-site team

    On-site associates keep the high-value exchanges and in-person meetings, which Asset Living links to renewals.

  5. 5
    Measurement data team

    Asset Living and EliseAI track occupancy, on-time rent payment rate and request resolution times by community.

The signal that drives it

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 studies

Les 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.

64%
Consommateurs qui prefereraient que les entreprises n'utilisent pas d'IA dans leur service client (2024)
53%
Consommateurs qui envisageraient de passer a un concurrent s'ils apprenaient que l'entreprise prevoit d'utiliser l'IA pour le service client (2024)
pres de 75%
Consommateurs qui veulent savoir s'ils communiquent avec un agent IA (2024)

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

See full acceptance: by country, by use, by generation

How to replicate

Inference, not sourced

Data 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
Team to operateA head of leasing operations who owns the deployment, a data profile for per-property measurement, a legal contact for late payment reminders, and the site managers who handle human takeover.

The plan, step by step

  1. Step 1
    Set the baseline: occupancy, on-time payments, response time to prospects, per property.Deliverable: Quantified baseline before deployment.
  2. Step 2
    Deploy 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.
  3. Step 3
    Add prospect handling outside business hours, then maintenance and renewals.Deliverable: Resident lifecycle covered on a single platform.
  4. Step 4
    Measure 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

  1. S1 How Asset Living Revamped Lead Nurturing and Delinquency with EliseAI Interested party eliseai.com · 2025 · accessed 2026-10-05 archive pending
  2. S2 Asset Living Advances Operational Excellence with EliseAI Partnership Primary assetliving.com · 2025-09-16 · accessed 2026-10-05 archive pending
  3. S3 Asset Living Advances Operational Excellence with EliseAI Partnership (blog EliseAI) Interested party eliseai.com · 2025-09-16 · accessed 2026-10-05 archive pending