How to Ensure a Better AI Implementation in Your Business

Artificial Intelligence (AI) has exploded into the mainstream over the past few years, thanks to tools like ChatGPT, automated response systems, and other generative AI platforms, as well as industry-specific solutions. Smart businesses across many sectors, including real estate and property management, are quickly working to best implement such tools. But while AI promises speed, scalability, and efficiency, smart implementation is key to reaping optimal rewards.

Recently, PredictAP and D2D Consulting hosted a webinar exploring what better AI implementation looks like in real-world scenarios. Here are some of the top takeaways from industry veterans David Stifter, Founder and CEO of PredictAP, and Dawn Dardzinski, Founder and CEO of D2D Consulting.

AI is Not New, But it is Newly Improved

Early AI tools, like scripted chatbots, required heavy manual input and predictable workflows. Today, AI is more dynamic, with built-in learning models and vastly improved accessibility. As Stifter put it: “There have been tools that do this for a long time, but I think the biggest change is accessibility. Before, you had to have a very high personal technical skill level. Now anyone can jump on ChatGPT and see how interesting this can be. People get it now.”

That accessibility has dramatically shifted the consumer experience, potential use cases, and business expectations. AI is no longer just a futuristic concept. It’s now an increasingly standard practical tool that organizations want integrated into their daily operations.

Changing Business Expectations

Companies today aren’t just chasing shiny new tech, they’re looking for solutions to real business problems, like vacant positions, hiring challenges, or onboarding dozens of properties in a short time.

As Dardzinski explained, “How do you continue to run your operations when you are drastically down staffed? If you can’t get good skilled workers, or even the workers that you do have are so overwhelmed by the volume of work that you do have, that you need something to supplement.”

Organizations are turning to AI not necessarily to replace employees, promote organizational change, maintain continuity of operations and reduce the burden on overworked teams. That means solutions must scale easily, integrate quickly, and provide measurable value, ideally with minimal disruption. The end goal can even include transformational changes of business practices and procedures.

“They’re easier to implement now,” Dardzinski said of many AI solutions. “Whereas before implementations could take months to a year... now the ease of implementation and ease adoption, because the tools have become more simplistic. Even the cost has become more effective, because it’s more accessible.”

Set Realistic Goals, and Get Your Team on Board

“AI is exciting, but a lot of old-fashioned problems still have old-fashioned solutions,” Stifter said. “AI is not the solution to every problem. It’s a solution to some (problems), but in some cases you’re forcing a square peg into a round hole with an AI solution.”

“It’s just like clothes, one size fits most, not all,” added Dardzinski. “You want to get the right size for the organization or for the problem that you’re trying to solve. Define the problem that you’re trying to solve first and then find the right type of AI to solve it.”

AI is also not perfect or infallible, just like a human team member. “I’ve heard someone say, it’s like an incredibly enthusiastic intern,” Stifter joked. It still needs human oversight. The smartest adopters view AI as an essential tool, not a silver bullet, to augment human talent, not eliminate it.

This means managing internal expectations is critical. Teams must understand what AI can realistically achieve, and leadership must communicate clearly that automation is there to support them, not replace them. Equally important is finding the right implementation partner, whether that’s the on-site team from your technology provider or a third-party consultant like D2D Consulting.

Successful AI adoption has less to do with software and more to do with staff attitudes and expectations. Dardzinski emphasized the need to get input from every level of the organization, “from the janitor to the asset managers in the C-suite.” Without stakeholder buy-in and thoughtful change management, even the best AI tool can suffer.

“Even if you have the smartest piece of technology, if all the users hate it, they will torpedo it and it will fail,” added Stifter.

“You have to have a team that’s going to marry the technology with the business operations and be able to train it to your end users, so that when the product is setup they can come out of the gate and immediately start using it, and it is an efficient tool for your organization,” Dardzinski said.

User acceptance testing, consistent communication, training, and involvement at all levels are what ultimately drive adoption and long-term success, she shared.

Make Smart Choices and Emphasize Security

With AI tools increasingly tied to third-party platforms and cloud-based systems, protecting sensitive company data is paramount. Off-the-shelf AI can’t always guarantee privacy, so bear in mind that any proprietary information submitted to a platform like ChatGPT will become part of the public domain and may be accessible by others. As with any third-party platform, organizations must establish clear governance, review licensing terms, and engage in strict online security protocols.

Both speakers were adamant: start with your internal challenge, not with the tool or product as a motivator. “Just because it’s the new hot product or it’s talked about a lot on social media, doesn’t mean it’s best for you,” Dardzinski warned. “Just because it’s a shiny new toy, don’t go chasing after it. Really do your homework and take the time to understand what your needs are.”

In many cases, this means working with implementation partners who understand not only the tech but also the business processes it’s meant to enhance.

Key Takeaways for a Better AI Implementation

Before wrapping up, both panelists shared rapid-fire takeaways:

• Dawn Dardzinski: “Do your due diligence. Know what your problem is before you go solve it. Don’t just adopt that shiny new product.”
• David Stifter: “Work with a partner who will work with your systems. That integration to your existing process and technology is really critical.”

AI isn’t a magic fix, but it is a powerful tool when used effectively. Companies that succeed with AI are the ones that ask hard questions, set realistic expectations, and involve the right people from day one.

If you want to watch the full webinar, you can find it here.