Lofty’s AI Index Puts a Number on Real Estate Automation—Here’s What Agents Should Do

Lofty has released what it calls the first AI Index for real estate, offering monthly estimates of how much time its artificial intelligence tools save agents.

The company says Lofty AI completed 1.13 million tasks in October 2026 and saved agents 131,248 hours. Those tasks included follow-up messages, social media posts, homeowner check-ins, CRM updates, and daily planning.

That is a useful shift in the conversation. Most real estate technology vendors promise efficiency without showing the arithmetic. Lofty is attempting to connect AI activity to a measurable business outcome: hours that agents theoretically did not have to spend doing routine work.

But the index is not an independent productivity study, and it is not proof that every Lofty customer gained 131,248 hours of productive selling time. For most agents, the practical question is simpler: does this give me a reason to change my technology stack?

What Lofty is actually measuring

Lofty says its index counts AI-completed tasks, assigns each task a conservative estimate of how long an agent would have taken to complete it manually, and adds those estimates across its products.

The October figures include:

• 387,824 leads receiving an AI follow-up text or email
• Nearly 16,000 hours saved on writing and publishing social content
• Nearly 30,000 hours saved by Lofty Homeowner Agent
• 36% of social media marketing hours saved among large brokerages
• 30% of daily-planning hours saved by solo agents
• More time saved by Michigan agents than agents in other regions

Those numbers are directionally helpful because they identify where automation is doing work. They also expose the limits of the announcement.

The source material does not provide Lofty’s monthly software price, the number of agents included in the calculation, task-level time assumptions, response rates, appointment rates, or closed-business results. It also does not say how many tasks required human review or correction.

That means the index currently measures automated activity and estimated time savings—not revenue, conversion, or customer experience.

How it compares with the tools agents already use

Lofty is not competing only with other AI products. It is competing with an agent’s existing combination of CRM, email templates, social scheduling, calendar tools, and occasional ChatGPT use.

| Option | What it handles | Pricing context | Best fit | |---|---|---|---| | Lofty AI | CRM activity, follow-up, homeowner nurturing, social content, and planning inside one real estate platform | Custom pricing varies by platform package, seat count, optional upgrades, and lead-generation programs—request a quote | Agents, teams, and brokerages seeking an integrated system | | Follow Up Boss or similar CRM | Lead routing, follow-up workflows, calling, texting, and CRM management | Follow Up Boss Grow is $69 per user per month when billed monthly; Pro is $499 per month for 10 users and Platform is $1,000 per month for 30 users, plus applicable tax | Teams that already have a CRM process and want workflow control | | General-purpose AI tools | Drafting emails, social posts, summaries, scripts, and checklists | ChatGPT Plus is $20 per month in the U.S.; other AI subscriptions vary by provider and plan | Agents willing to build and supervise their own process | | Existing manual workflow | Templates, spreadsheets, reminders, and personal follow-up | Direct software cost may be low, but labor cost is not | Low-volume agents with simple databases |

The important distinction is integration. A general AI chatbot can draft a follow-up message, but it generally will not know which leads need attention unless the agent connects it to the right systems and checks the output. An integrated real estate platform can automate more of the workflow, but it also creates greater dependence on one vendor.

Lofty’s strongest case is therefore not “AI writes faster.” It is “AI can perform recurring CRM work inside the same system where the lead history lives.”

The cost question: saved time is only valuable if it changes behavior

Lofty’s headline figure sounds large, but an individual agent should not divide 131,248 hours by the company’s customer count and treat the result as a forecast.

A better calculation is:

Monthly software cost ÷ the agent’s realistic hourly value = hours the system must save each month to justify its cost.

For example, if a system costs $500 per month, an agent who values productive time at $50 per hour would need to recover 10 hours monthly before considering other benefits. That does not mean every recovered hour produces a commission. It means the agent must decide whether those hours will be redirected into lead conversations, listing appointments, client service, or genuinely valuable personal time.

This is where many AI purchases fail. An agent can save time creating posts and still see no business benefit if the freed-up time is not assigned to a better activity.

Before buying or expanding an AI platform, track for 30 days:

• Minutes spent on follow-up, CRM updates, social content, and planning
• Number of leads touched
• Human edits required on automated messages
• Appointments set and conversations started
• Leads that received no follow-up because of system or data problems

Then compare those figures with the vendor’s claims. The relevant result is not “tasks completed.” It is whether response coverage improves without damaging the quality of the relationship.

Who should pay attention

Lofty’s announcement matters most to teams with a large volume of repetitive work.

Brokerages and teams should examine it if agents regularly leave leads untouched, CRM records incomplete, or past clients neglected because administrative work expands faster than headcount. The index may also give operations leaders a starting framework for measuring automation across offices.

Solo agents with large databases may benefit from the same approach, particularly if they already have a consistent CRM process and enough lead volume to create recurring tasks.

Agents should be more cautious if their database is small, their business is primarily referral-based, or their follow-up depends on highly personal communication. Automation can save time, but generic messages can also make a relationship-driven business feel transactional.

Who can ignore it for now

You can probably ignore this announcement if your current problem is not task volume.

AI will not fix poor lead sources, incomplete contact data, weak positioning, unclear response standards, or a lack of time for actual client conversations. It also will not make an unprofitable marketing channel profitable simply by producing more content.

If you are not measuring response times, appointments, and conversion by lead source, adding another AI layer may make reporting more complicated rather than more useful.

The practical next step

Do not adopt Lofty because its industry-wide number is impressive. Ask for the assumptions behind the number, the current US price, implementation requirements, opt-out controls, message review options, and evidence that automated touches improve outcomes for customers like you.

Then choose one workflow—such as new-lead follow-up or past-client check-ins—and measure it against your current process for a month.

If Lofty can reduce manual work while preserving accurate, timely, human-appropriate communication, the index becomes more than marketing. Until the company publishes fuller methodology and business-outcome data, treat it as a useful measurement proposal, not a guaranteed return on investment.

Learn more about the platform here: Lofty

Skip this if...

Skip Lofty for now if you do not have a repeatable CRM process, cannot explain how saved hours will be reinvested, or are unwilling to review automated client-facing communication. In those cases, process cleanup is likely to produce a better return than another software subscription.