Scully Company

Renee McIntyre

Strategic AI Adoption

Renee McIntyre is a marketing leader specializing in real estate sales, marketing strategy, portfolio occupancy and revenue growth. A Certified Training Facilitator for the National Apartment Association, she holds degrees in tourism and hospitality and marketing.

The Problem Was Never the Mowing

As vice president of marketing at Scully Company, a multifamily property management firm, I spend a good amount of time considering how technology, data and better processes can drive business performance. AI has become a significant part of that work.

I'm optimistic about AI's potential, but the more I observe how organizations are using it and discuss its implications with industry peers, the more convinced I become that we are approaching this opportunity backward.

Imagine your lawn is struggling. The grass is brown, patches are dying, and it feels crunchy under your feet. Something clearly needs to change, so you invest in the latest robotic lawn mower. It's wildly impressive. It maps your property, navigates obstacles and promises to make lawn care practically effortless, but you never really take the time to learn how to use it.

You stick with the basic settings and go back to your life, barely scratching the surface of what your expensive new machine can do. And despite your investment, the lawn is still dying, because the problem was never the mowing. It was the lack of water. We are seeing something remarkably similar happen with artificial intelligence.

We invest in this extraordinary technology and provide licenses to employees without taking the time to understand its capabilities or provide direction. And more importantly, we are adopting solutions without first identifying the problems we need to solve.

Just because we can use AI doesn't always mean we should. Instead of asking, ‘Where can we use AI?’ we should be asking, ‘What are we trying to accomplish, and could AI help us get there?’ That distinction is the foundation of an intentional AI strategy.

What Are We Actually Trying to Achieve?

Every week brings another AI product promising to transform productivity, reduce expenses or revolutionize the way we work. It's important to understand advancements and capabilities, but I worry we are beginning to mistake implementation for progress. An AI tool can be impressive and still be the wrong investment.

In construction, where workforce capacity, project coordination, cost management and operational efficiency are persistent challenges, the greatest opportunity may not be the latest industry-specific AI platform. Instead, it might be a relatively simple solution to an inefficient process that's been frustrating your team for years.

AI’s greatest potential goes beyond saving time. The real opportunity is what we enable people to do with the capacity we create. If AI gives a project manager five hours back each week, that's an efficiency improvement. If those five hours allow that person to solve complex problems, strengthen client relationships or improve project outcomes, we have created value that goes well beyond the hours saved.

This is the opportunity leaders should be pursuing. Not simply doing more with less but enabling people to do more of the work that requires their expertise, creativity, judgment and human connection. The work only humans can do.

A Roadmap for Intentional AI Adoption

There is no one-size-fits-all AI strategy. Every organization has different challenges, resources, values and priorities. But there are four essential steps every business can take.

1. Locate Your Starting Line

Before introducing new tools, understand how AI is already being used within your organization. Employees may be experimenting independently, creating both opportunities you can scale and risks you need to mitigate. Assess employees' AI literacy, establish clear policies and understand where data quality, privacy or accuracy concerns could limit adoption. Technology is advancing quickly, and our ability to use it responsibly and effectively needs to advance alongside it.

2. Identify the Problems Worth Solving

Start with your biggest operational challenges, not the latest flashy product demonstration. Engage employees across departments in this process, particularly those closest to the work. Where are people losing valuable time? What processes create frustration? What limits your team's ability to deliver excellent results? Look for opportunities where solving a problem would meaningfully improve performance or create capacity for higher-value work.

3. Experiment with Purpose

Once you have identified a challenge, explore solutions and start small. Define what success looks like before beginning a pilot. Establish measurable objectives, assign ownership and evaluate the results honestly against the pre-determined success metrics. Did you improve efficiency, accuracy, quality or customer experience? Most importantly, did those improvements produce meaningful business value? If the answer is no, don't be afraid to move on.  Enthusiasm is not a performance metric.

4. Learn, Share and Scale

AI adoption should not happen in isolated departmental experiments. Encourage knowledge sharing, celebrate meaningful improvements and learn from what doesn't work. Invest in developing your team alongside your technology. When something works, build on it. When circumstances change, reassess. An intentional AI strategy is not a plan you create once. It's an ongoing approach to improving your business.

Where Do You Begin?

You don't need to launch an organization-wide AI transformation tomorrow. Start with one problem that matters. Understand what is causing it, explore whether AI is the right solution, and give your people the knowledge and support to use it effectively. Then ask one more question: ‘If we solve this problem, what will our people be able to do better?’

The real measure of an AI strategy isn't how much technology you have implemented. It's what your business and your people can accomplish because of it. Challenge first. AI second.