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We surveyed 17 YPO CRE CEOs. There’s a massive gap between those experimenting with AI and those actually integrating it into their day-to-day. Our report’s most important finding is that less than 25% of firms had moved beyond pilots into multiple live, non-chatbot AI workflows.
Specifically, four of the 17 firms (24%) reported multiple live workflows.
This contrasts sharply with the group’s enthusiasm: 14 of 17 rated AI an eight-to-ten priority, and 13 said leadership was strategic or actively pushing adoption.
The firms broadly fell into three groups:
- Six had no formal AI initiative, despite some employee experimentation.
- Six remained at the chatbot or copilot stage.
- Five had some production use beyond chatbots, but only four had multiple live workflows.
This gap shows why buying software is not an AI strategy. A pilot can succeed with carefully selected data and close supervision.
Production requires the solution to handle real work repeatedly, accommodate imperfect inputs, escalate exceptions, and continue functioning after the original champion steps away.
That is precisely the gap Automation Mining closes.
Rather than guessing where AI might help, we work with leadership, process owners, and subject-matter experts to:
- Validate systemic bottlenecks and process-level problems through prework and kickoff.
- Shadow priority processes to map workflows, people, data, systems, and operational nuances.
- Score opportunities across strategic alignment, financial impact, risk, operational effectiveness, stakeholder impact, time to value, market demand, competitive advantage, and cost-benefit.
- Narrow the possibilities to the one-to-four initiatives with the greatest enterprise impact.
- Deliver an AI roadmap, change-management plan, process documentation, and statements of work that lead directly into execution.
The survey also challenges the assumption that larger companies will automatically lead.
Every firm reporting production use beyond copilots had a back office of 25 people or fewer, while all three respondents managing more than $3 billion remained at the chatbot/copilot stage.
The sample is too small to establish causality, but it suggests that disciplined workflow design and ownership may matter more than company size.
Although the respondents were CRE firms, their priorities—finance, reporting, operations, transactions, risk, and stakeholder communications—are found in nearly every industry.
These workflows involve recurring work, fragmented data, repetitive handoffs, and identifiable exceptions requiring human judgment.
The roughly 25% of firms with multiple live, non-chatbot workflows is the number to remember.
When you go to happy hour or conferences or Forum meetings, everyone’s talking about AI, but very few people are actually doing it well. Most are simply enthusiastic about it.
Conviction is widespread and experimentation is common, but production remains very uncommon.
The advantage will probably not come from your enterprise Claude / ChatGPT subscription. Everyone’s got that.
It will come from finding the right process, designing the future-state workflow, and carrying it through implementation.