I have been watching the AI debate closely this year. You probably have too.

Fortune just published findings from a study of nearly 6,000 CEOs, chief financial officers, and senior executives. 90% said AI has had no measurable impact on productivity or employment at their companies. 70% of those firms are actively using AI. The average CEO spends 1.5 hours a week with it.

The headlines wrote themselves. AI is overhyped. The productivity gains are not real. Jobs are safe.

On the other hand.

Jack Dorsey just cut 40% of Block's workforce, more than 4,000 people, and said every company will reach the same conclusion within a year. Oracle is reportedly considering 20,000 to 30,000 cuts to fund AI expansion. U.S. payrolls dropped by 92,000 in February.

The headlines wrote themselves there too. AI is replacing jobs now.

Both sides are loud. Neither is asking the right question.

The Question Nobody Is Asking

The debate is about jobs. Will AI replace them, augment them, create new ones.

That is not the question that moves your business forward.

The question is: what does AI do to your business model? Not your headcount. Your margin. Your cost to evaluate a deal, run a property, manage a portfolio, communicate with investors.

This is the shift from "will AI" to "how can AI." And it requires something most organizations have not done. Not adding AI to old workflows. Integrating it into how you actually work.

Why the Numbers Do Not Move

Economist Robert Solow identified this pattern in 1987. Computers were everywhere except in the productivity statistics. The same thing is happening now.

At the task level, AI works. A Harvard and BCG study found that professionals using AI completed 12% more tasks, 25% faster, at 40% higher quality. But at the company level, the gains vanish. PwC's 2026 CEO Survey found 56% of executives say they have gotten nothing from their AI investments.

The technology is not failing. The implementation is. Most organizations bolt AI onto existing processes. Same workflow, slightly faster input. That is not a business model change.

In hospitality, the data is sharper. 91% of operators still rely on manual reporting even within automated systems. Only 11% have a fully integrated technology stack. 27% spend more than 11 hours per week consolidating data across platforms.

The technology is available. The way most people work has not changed. This was the case for me as well.

The Levers That Actually Move

I learned, when you integrate AI into the workflow itself, the impact is real and measurable.

Compressing deal evaluation and client-scope analysis from days to hours. Underwriting accuracy. Cross-referencing multiple data sources simultaneously to catch what sequential manual review misses. Investor communications. IC memos, quarterly reports, lender narratives. Asset management reporting. Variance analysis, comp set tracking, NOI reconciliation. Operational workflows. The 11 hours per week of data consolidation, compressed. Capital raising. Investment Memorandum preparation, market positioning, LP outreach.

Each of these is a line item. Each one has a cost today. AI compresses that cost when it is woven into the process. The margin improvement compounds across the portfolio.

But what I have realized most is this. AI allows me to spend more time on the activities that actually move the needle. When the data work is compressed, my focus shifts to the tasks only an experienced human can do. Pattern recognition across deals. Judgment calls on pricing. Relationship strategy. That is where the value lives.

One Lever, Pulled

Here is what this looks like on one deal.

I evaluated an $11.5M extended-stay acquisition last week. Nine source documents arrived: compiled financial statements, monthly revenue reports, QuickBooks summaries, an appraisal, a pro-forma, and email correspondence. The question was whether the deal was worth pursuing and at what price.

AI extracted and cross-referenced data across all nine documents. It built a full 12-month year-over-year revenue comparison. Computed GOP, EBITDA, EBIT, and free cash flow with percentage-of-revenue columns. Ran a 10-property comparable sales analysis with per-unit pricing. The output was a 12-page deal memo with 15+ formatted tables and a draft email to a potential partner. Manually, that work is 10 to 14 hours spread over two to three days. With AI integrated into the workflow, it was one extended session.

But here is where the value lives.

The AI's first pass naively annualized revenue at $1.8M because it didn't account for seasonality inherent in hospitality. Wrong. Corrected, revenue was just over $2M, closer to trailing 12-month revenue. The monthly analysis revealed a split pattern with a weak first half of the year followed by recovery. Neither the seller's projections nor a simple annual comparison would surface that. The comp analysis showed the asset priced at 42% above the most recent comparable sale, but didn't account for the retail lease revenue in one of the assets.

Four rounds of revision. Each one required judgment to correct the analysis and shape the strategy. AI compressed the work. Judgment made it investable.

What AI Cannot Pull

I wrote last week about three things that remain outside AI's reach: wisdom and judgment, experiences, and relationships. That has not changed. The 90% of CEOs who see no impact are measuring whether AI replaced a person. The better measure is whether it reshaped a process, and whether the operator had the judgment to direct it.

Even better, whether the operator is able to spend more time on judgment-related activities instead of the work AI replaced. And whether they have the skill set for this revised role.

That last measure points to questions we all face in this new reality.

• Am I learning how AI can improve my old workflow habits?
• Do I have the skills and judgment to develop and manage the revised workflow?
• What does my role look like when AI handles the data work, and am I using that recovered time to drive decisions that show up in my P&L?

The Reframe

Stop debating whether AI takes jobs. Stop waiting for a headline to tell you whether it works.

Open your P&L. Model it. If AI compresses 10 hours of deal analysis into 3, what does that mean across 10 deals a year? If it cuts investor reporting time in half, where does that margin go? If the 11 hours per week your team spends on manual data consolidation drops to 2, what does that do to your operating budget over 12 months?

But the bigger reframe is not about time savings. It is about what you do with the time you get back. The operators who treat AI as a cost-cutting tool will get incremental gains. The ones who use it to shift their own role toward higher-value judgment, strategy, and relationship work will build something structurally different.

The ones asking "how can AI" are not just saving hours. They are repositioning themselves in their own business. The ones still asking "will AI" are spending 11 hours a week on manual reporting inside automated systems while the market reprices around them.

Don't let that be you.

-Damon

P.S. The AI work I write about is how I move faster. What I actually do is help extended-stay owners and operators get deals done. Capital readiness. Acquisitions. Portfolio growth. Exit strategy. If you are sitting on trapped equity, running legacy operations, or thinking about what comes next,

​Schedule a call or reply to this email. I work as an external executive alongside founders and investors who are ready to grow or ready to transition. Either way, I can help.