When I talk to CRE firms about AI, I hear the same line over and over:
“We’re going to wait and see how this plays out before we really invest.”
On paper, that sounds prudent. No one wants to chase every shiny tool.
In practice, “waiting to see” on AI for CRE is not neutral. You are quietly paying for it every day in ways that do not show up on a P&L line, but absolutely show up in your pipeline, your people, and your positioning.
This is what that bill actually looks like.
1. You Lose The Compounding Effect Of Small Experiments
AI is not one big switch you flip. It is dozens of small, messy experiments that stack over time.
When you push those experiments off:
- You still underwrite every deal
- You still scrub every rent roll
- You still write every IC memo by hand
You just do it without building a repeatable AI for CRE playbook along the way.
Firms that started a year ago did not magically automate everything. What they did was:
- Try AI on the rent roll parsing, figure out what worked
- Try AI on OM summarization, refine the prompts
- Try AI on IC memo drafts, tune the voice
Every quarter, the hit rate improves. The quality of prompts improves. The list of things they trust AI with grows.
If you are “waiting to see,” you are not standing still next to them. You are falling a year behind on a compounding learning curve that is very hard to catch once client expectations move.
2. Your Best People Quietly Build Their Own Stack Without You
Analysts, associates, and even some principals are already using AI on their own machines.
If the firm is not providing:
- Clear guidance on what tools to use
- Standard workflows for common tasks
- Guardrails around data and confidentiality
then your smartest people start building their own AI stack in private.
They:
- Paste rent rolls into random chatbots
- Use general models to summarize legal language
- Store prompts and snippets in personal notebooks
You pay the risk. They get the productivity. The organization learns almost nothing.
The cost of “waiting” here is simple:
- You do not see what is working
- You cannot standardize or scale the good stuff
- You cannot protect the firm from the bad stuff
By the time you decide to get serious, the talent that has been quietly doing AI work for you is either frustrated that leadership is behind or has already been poached by a firm that wants that skill set.
3. You Keep Funding Your Competitors’ Data Advantage
Every deal you touch creates data exhaust.
- Underwriting models
- DD memos
- Negotiation trails
- Rent rolls and operating statements
If you are not feeding that into an AI for CRE engine that you control, that data just sits in shared drives and inboxes.
Meanwhile, any competitor who is even moderately serious about AI is:
- Indexing every deal they touch
- Letting AI learn from wins, losses, and passes
- Turning that history into:
- Better screening rules
- Smarter sensitivities
- Faster “no” and sharper “yes”
The hidden cost is that you keep doing the hard, expensive part of the work, and they reap the pattern recognition benefits.
Your work becomes raw material for someone else’s learning curve.
4. You Negotiate Against AI With No AI Of Your Own
We already talked about this in another piece, but it is worth repeating here.
In almost every meaningful negotiation now, the other side has:
- AI summarizing your emails
- AI comparing your mark‑ups to prior deals
- AI drafting counters and talking points
If your position is:
“We’ll adopt AI after the market settles down,”
what you are really saying is:
“We are comfortable negotiating against people who outgun us on preparation, memory, and pattern recognition.”
The cost is not visible on day one. It shows up as:
- Slightly worse covenants
- Slightly tighter timelines
- Slightly riskier language that you “did not notice” in a long document
Each one looks small. Across a portfolio, it is material.
5. You Signal To Clients And Investors That You Are A Follower
Clients and LPs do not need you to be a tech company. They do expect you to be:
- Curious
- Data‑driven
- Willing to test new tools where the risk is controlled
When they ask about AI and you say:
“We are waiting to see what the rest of the market does,”
what they actually hear is:
- “We are more comfortable copying than leading.”
- “We will probably be late to the next obvious improvement too.”
That might be fine if you are selling pure yield, but if you are selling:
- Strategy
- Process
- Edge
then “wait and see” is not a neutral story. It directly contradicts your positioning.
6. You Keep Paying For Manual Work That Could Already Be 50–80% Automated
Some parts of CRE work are not ready for full automation. Fine.
Other parts are frankly not good to still be doing by hand:
- Renaming and sorting OM pages
- Re‑keying rent rolls into Excel
- Manually pulling basic tax and ownership data
- Drafting the first pass of an IC memo from scratch
When firms say “we are not ready for AI yet,” what they often mean is:
- “We do not want to change how work is done.”
The cost is straightforward:
- You pay fully loaded human hours for work that AI could handle at least 50–80% of the way, with your team focusing on review and judgment.
- The people you hired for judgment are spending their days on formatting, copying, and summarizing.
Those people leave sooner. Their replacements are harder to hire. Their compensation expectations are higher. The hidden cost of “waiting” shows up in turnover and recruiting friction, not just time sheets.
7. You Miss The Chance To Shape How AI Actually Works For CRE
Right now, tools are still malleable.
If you jump in early:
- You influence how workflows are built
- You get your firm’s quirks encoded into the system
- You build AI coworkers that actually match how you think about risk, returns, and process
If you come in three years late, you get:
- A generic “CRE solution” that reflects someone else’s view of how underwriting or asset management should work
- A set of defaults that your team fights instead of trusts
The hidden cost is that you lose the chance to build firm‑specific AI assets that are hard for competitors to copy.
What “Not Waiting” Actually Looks Like In Practice
Getting off the “wait and see” path does not mean signing seven‑figure software contracts and rewriting your org chart.
It can be as simple as:
- Pick three workflows that are low‑risk and high‑repetitionFor example:
- OM and rent roll intake
- IC memo first drafts
- Ownership / tax / market data pulls for new deals
- Standardize how you want them done
- One clean template for each
- Clear definition of “good enough” output
- Use AI for CRE tools to handle the first pass
- AI generates the draft
- Human reviews, edits, and stamps
- Capture what works, not just what saves time
- Prompts that consistently produce good output
- Checks that catch issues early
- Edge cases where you absolutely want a human to own it from start to finish
- Report back to yourself
- Time saved is nice
- The real metric is:
- How many more deals you can screen
- How many more sensitivities you can run
- How many more conversations you can have with clients and tenants because the admin work is off your plate
If You Are Still On The Fence
If you are genuinely not sure where to start, do this:
- Take one month of actual work.
- Identify every task that:
- Involves text, numbers, or structured documents
- Is repeated at least weekly
- Does not require a senior person’s final say to even begin
Run a controlled test with AI for CRE on those items only.
After that month, ask two questions:
- “Do we understand our deal flow, risk, or client communication better than we did 30 days ago?”
- “Did we create any reusable workflows or AI coworkers that will compound next quarter?”
If the answer is yes, you are already paying the cost of “waiting to see.” You are just no longer pretending that cost is zero.
CRE Agents is launching on February 26th.
Frequently Asked Questions About The Hidden Cost Of Waiting On AI For CRE
AI for CRE refers to AI workflows and tools specifically tuned for commercial real estate tasks such as rent roll parsing, OM summarization, underwriting support, and IC memo drafting. General tools like ChatGPT can help with some of this, but purpose-built CRE AI is trained or prompted around the data formats, terminology, and judgment calls that are unique to the industry.
No. Most firms getting value from AI today started without dedicated tech staff. The key is identifying repetitive, text or numbers-heavy workflows and running small experiments with existing tools. You need curiosity and a willingness to iterate, not a software engineering department.
This is exactly why waiting without a plan is riskier than starting with one. If you do not provide approved tools and clear guardrails, your team will use whatever they can find on their own, often with zero data protections. Getting intentional about AI lets you choose tools with proper security, set policies around what data can and cannot be shared, and maintain control.
Most firms report noticeable time savings within the first 30 days on targeted workflows like OM intake or first-draft IC memos. The bigger payoff, including better screening speed, reusable prompts, and compounding institutional knowledge, typically starts showing up after one to two quarters of consistent use.
The highest-value starting points tend to be tasks that are high-repetition and low-judgment on the front end: OM and rent roll intake, ownership and tax data pulls, first-pass IC memo drafts, and market comp summarization. These free your team to spend more time on analysis, negotiation, and client relationships.
AI should not be running your underwriting unsupervised. The model that works is AI drafts, human reviews. You use AI to handle the first 50 to 80 percent of the work, including the formatting, data entry, and initial structuring, and your team focuses on review, judgment, and final sign-off. Mistakes become easier to catch because your people are not fatigued from hours of manual grunt work.
Often more so than for large firms. Smaller teams feel the pain of manual work more acutely. Every hour an analyst spends re-keying a rent roll is an hour they are not screening the next deal. AI lets a lean team punch above its weight on deal volume, speed, and preparation quality.
CRE Agents is launching on February 26th as a purpose-built AI platform for commercial real estate firms. It is designed to turn the exact workflows described in this post, including OM intake, IC memos, deal screening, and more, into repeatable, AI-assisted processes that compound over time.
It is not one big line item. It is a slow bleed across multiple areas: lost compounding on AI learning curves, talent attrition, unprotected data practices, weaker negotiation prep, and thousands of hours spent on work that is already automatable. The firms that started a year ago are not just saving time. They are screening more deals, retaining better people, and building institutional AI knowledge that is hard to replicate.