If you want to integrate AI into your lawn or landscape business, there are several considerations to ensure it is worth the effort and utilized to its fullest.
First, consider your goals for implementing an AI solution. Will it help with cost efficiency and allow your team to do the same work with fewer resources or boost your team’s performance by accomplishing more with the same resources? Whatever your goal is, that will help you calculate your ROI as you monitor AI’s impact on your KPIs.
“You can even A/B test the product by giving team A the models, but withholding it from team B,” says Michael Ding, founder and CEO of Bobyard, an AI-powered takeoff and estimation software. Ding did his AI research at Stanford University and is currently partnered with NVIDIA, Google, and Amazon cloud services. “Then set up a time frame and measure the team’s performance.”
You should also evaluate how an AI solution fits into your existing technology stack and what might be needed to improve the end-to-end process.
“If certain teams are using AI and not their upstream or downstream counterparts, then thought needs to be given on how the information input and output will be handled to not cause bottlenecks for the company as a whole,” Ding says.
Training Your Team
Getting your team onboard with actually using your AI solution is critical for it to be truly useful for your operation. If only some or none of your team is using this technology consistently, you can’t expect it to have a true impact on the business.
“So many companies spend the money on a new system but don’t take the time to utilize all of its features and so don’t get the full ROI,” Ding says.
Ding advises clearing your team’s mindset toward AI and stressing it is there to remove mundane, error-prone tasks that take up their time, not take jobs.
“There is a lot of unease about AI replacing jobs and adopting it,” Ding says. “The first thing companies should do is educate them about these new technologies to make sure that there is alignment on what these products are being used for. Talk specifics about exactly what they do.”
Ding adds that while most jobs in landscaping can be augmented by AI, not a single job can be entirely automated.
Once everyone is on the same page, then you can go about training them on what AI is and isn’t and where it can help versus where it’s not the most useful. Ding says you also need to teach your team how to use AI effectively, which includes crafting better prompts and checking for errors.
“By leveraging AI just like other office productivity software, employees can spend more time on customer relationship building, value engineering, unique designing, and having the time to enhance their own skills as they prepare for the next step in their careers,” Ding says.
Ethical Considerations
AI is transforming the landscaping industry, but its ethical use requires careful consideration. One major concern is AI-generated design theft, where minor modifications to a competitor’s work could misrepresent originality. Clear guidelines are needed to ensure AI enhances creativity rather than facilitates intellectual property misuse.
Misleading AI-generated renderings can create unrealistic client expectations, leading to disputes and reputational damage. Transparency in AI-assisted visuals is essential to maintain trust.
Additionally, AI-powered customer interactions, such as automated proposals or chatbots, can improve efficiency but risk making client engagement feel impersonal. To retain a high-touch experience, AI should support — not replace — human expertise. Businesses that integrate AI responsibly will gain a competitive edge while maintaining integrity in design, communication, and client relationships.
Another concern you may have is developing a dependency on AI, but Ding argues there was a similar concern with the introduction of the internet, mobile apps and cloud technologies.
“Today no one asks how landscaping companies or any company should avoid becoming too dependent on spreadsheets or CAD software or cloud solutions in landscaping,” Ding says. “Similarly, AI should be seen as a productivity tool that enhances efficiency and frees up valuable time for more impactful work — whether it’s creating custom designs, value engineering, or pursuing more business opportunities.”
He argues that the focus should be on how AI can complement and elevate employee expertise rather than fearing overreliance on AI.
The Future of AI
One point against AI has been its level of energy consumption and overall lack of sustainability. Ding counters this with Moore’s Law, which is the observation that the speed/efficiency of chips will roughly double every two years. This means the cost and energy needed to run chips will decrease over time.
“Companies and research institutions are actively working on optimizing algorithms to reduce their computational needs, making AI models more efficient without compromising performance,” Ding says. “This includes techniques like model pruning, knowledge distillation, and leveraging specialized hardware that uses less power.”
Additionally, many AI infrastructure providers and tech companies are transitioning to renewable energy sources to power their data centers.
“As the industry shifts towards more sustainable energy solutions, the environmental impact of AI systems will continue to decrease,” Ding says. “It used to be the case that computers take up entire buildings; now it’s on your wrist, takes up much less power and it’s way more powerful.”
Ding anticipates AI will expand in two different ways in the near future. One will be increased industry applications that cater to specific needs and the level of intelligence will increase.
“This means that the things you need to double-check or set up decreases,” Ding says. “For example, instead of telling the tool to measure the irrigation system’s laterals, it would just know to do that on its own by reading the notes in the drawing/other documents you feed it and figuring out the scope of work on its own.”
