Trying to implement AI into your onsite operations without a framework is like trying to take a roadtrip without a map. Without key landmarks, specific objectives, and a well-defined destination you run the risk of getting off track, which could have negative results when it comes to trying to evaluate the performance and ROI of your new AI tool. That’s why we developed an easy-to-follow roadmap for implementing AI with inputs and expertise from Jacob Kosior, Vice President of Client Strategy at EliseAI and former Vice President of Centralized Services at Cardinal Group Management. Grab your snacks and buckle up, we’re going on an AI implementation roadtrip.
Step One: Outline Your Operational Goals & Objectives
It’s going to be difficult to tell if your AI rollout is meeting your operational needs or not without concrete objectives to evaluate how well the new technology is supporting onsite efforts. Here’s how you can make sure your goals tightly align with business objectives.
Identify Specific Operational Challenges to Solve with AI
We’ve seen some property management companies have success right out of the gate with AI, and we’ve also seen others stumble coming off the starting line. One immediate make or break factor is how well defined your operational roadblocks are. Ask yourself: where are the shortcomings in my existing property management processes? Is it slow response times to resident and prospect inquiries, slow management of maintenance requests, inconsistencies in communications to residents, or large amounts of outstanding bad debt?
AI is a powerful tool to fill-in gaps in operational processes and it’s only maximized when the challenges are well-defined. Being laser focused on which operational challenges you’re trying to solve and setting expectations for the AI can help you measure and evaluate the impact of a new tool. For example, saying “our leasing performance is poor” is a general and vague challenge that might not be as helpful as choosing a specific challenge, like “we have a hard time managing the volume of inbound prospect communications.” Having specific, measurable objectives can help you drill down into the real issues at play, rather than tackling broad problems with a wide variety of underlying issues.
Align Your AI Implementation Goals with Your Overall Business Strategy
Beyond just evaluating the impact AI can have on specific operational challenges it’s crucial to consider how AI implementation supports your overall business goals. While operational challenges are good for expectation setting and to track performance, it’s important that you’re able to report on your AI’s ROI and impact on the overall business to organizational decision makers in order to justify the continued cost of the new tool. Some business strategies you can look to tie AI implementation to include:
- Centralizing rent collections with a dedicated, specialized team supported by AI
- Reducing lead leakage in leasing efforts by deploying AI for 100% answer rates
- Improving responsiveness with leads to reduce the lead-to-lease timeline
- Improving resident experience through proactive communications
- Improving turnaround time on work orders and reducing manual work order recategorizations
When evaluating AI’s impact on key business goals, it’s important to note how those KPIs are currently being measured so you can track performance improvement over time. For example, if a faster lead-to-lease timeline through improved lead responsiveness is the goal, it’s important to have context on what that timeline currently looks like without AI support. The historical data is crucial for context on where we are, before measuring where we are going. Without defined benchmarks, it’s difficult to measure before and after performance.
Step Two: Involve Key Stakeholders from the Start
Getting and keeping all your stakeholders on the same page is pivotal when trying to boost adoption and measure the impact of the new tools. Ensure all stakeholders understand the previously-defined operational challenges and business strategy related to the AI deployment. If teams fall out of sync or stakeholders aren’t aligned on the “why” and “how” AI is being implemented, the AI rollout could be marred in competing narratives around impact and effectiveness. Here’s how you can make sure your key stakeholders get and stay onboard with the AI initiative.
Engage Cross-Departmental Teams to Ensure Alignment
Set expectations about the role of AI from the beginning of the process to all your cross-departmental teams. They need to know that AI isn’t just a leasing tool or a collections tool, and that AI isn’t a set-it-and-forget-it integration to be managed by Marketing. AI will fundamentally change the onsite operations and processes of communities deploying the tool and effective rollouts include stakeholders from multiple departments to contribute to the change management aspect of AI implementation.
With that in mind, cross-departmental engagement is key to ensuring everyone fully grasps the functionality of AI and the necessary reshaping of roles and responsibilities that go with implementing it. Here are some department by department responsibilities you should consider when thinking about stakeholder alignment during an AI rollout.
For your Operations team, make sure to communicate:
- Why AI is being introduced into onsite processes
- How onsite team members are expected to engage with the AI agent
- Who is responsible for managing additions and approvals to the AI’s knowledge
- What SOPs may need to be revisited as part deploying AI
For your Marketing team, ensure:
- All lead sources and vanity phone numbers set up correctly
- Email addresses for the new AI agent are created and active
- Guest cards are being accurately routed to the new AI agent
- Leasing process documentation is updated to reflect the addition of AI in the lead, applicant, and/or lease signature process
For your IT and Systems teams, make sure:
- All integrations with the existing PMS/CRM are live
- Your new AI agent is set as the default for inbound guest cards
- Any access concerns are addressed through SSO
For your teams that handle training, make sure to ask:
- What onsite training materials need to be adapted to include the use of AI in onsite operations?
- Do any materials need to be created to supplement the training materials available in EliseCRM?
For your HR team, make sure to ask:
- How do job descriptions need to change to reflect the introduction of AI into onsite operations?
- If your company already has a policy on using generative AI tools in the workplace, does that need to be updated to reflect the addition of a conversational AI tool in your technology stack?
Ensure Clear Expectations for Managing AI Interactions
It is pivotal that you clearly define expectations for your onsite teams in regard to their relationship with AI. That way, when the performance of the AI tool and your team are evaluated, you can ensure that misalignment wasn’t the cause of any bumps in the road.
First, share the challenges you’re hoping to solve with AI and what the definition of “success” looks like in regard to AI with your onsite teams. That way, everyone is on the same page from day one. Make sure you identify the points of contact who will be responsible for managing your AI’s knowledge and handoffs of conversations that the AI is not capable of resolving on its own, or needs knowledge approval in order to answer accurately in the future. Ensure you communicate expectations and set goals for standard response times, escalation processes, and the desired impact of the new AI solutions you’re deploying to the designated PoCs.
Set Up Regular Meetings for Feedback and Obstacles
Communication during AI rollout should be a two way street, as the feedback of the team members who actually have to interact with the AI every day can give you insights into what is and isn't going well. Ensure that these meetings keep the initial “why” and “how” into perspective, so that feedback is shared in a forward-thinking manner, rather than defaulting to “how it’s always been done.” Hosting group meetings is a great way to ensure the feedback you receive is constructive and relevant. These meetings should include the stakeholders from across departments, as well as relevant onsite team members who regularly interact with the tool. These meetings also provide an opportunity to assess the organization’s readiness to implement additional AI tools, reinforce the high-level obstacles, and highlight how AI is being added to the operational process to address existing challenges.
In addition, feedback from onsite team members is key to understanding how organizational SOPs, training materials, and job descriptions may need to be adapted to include the use of AI in onsite roles. As we previously covered on our blog, AI is going to have some growing pains for everyone. Feedback from your onsite teams can go a long way toward mitigating some of that pain.
Step Three: Integrate AI with Existing Systems
Adding AI solutions to your tech stack can help improve leasing velocity without increasing headcount and reduce bad debt, but it’s key to ensure it works with your existing tech stack. Choosing a solution that plays nice with the software you’re currently using and strategically testing your integrations can be the difference between a smooth rollout and a botched one.
Audit Your Impacted Systems and Integrations
Ensuring your AI solution integrates with your PMS and CRM is key, but it’s important for property management companies to consider how other systems may be impacted by implementing AI. For example, if your utility billing is managed by a third-party and automatically posted to resident ledgers, how does the timing of that posting impact conversations around AI collections? Or what if you’re already using a third-party software for mass-texting? How will that impact the resident experience with texts also coming from your AI agent, albeit from a different phone number? Finally, are there any custom workflows in the PMS or CRM that need to be replicated with your AI?
Getting answers to these questions goes a long way in ensuring that implementing AI creates efficiencies across a wider array of operational considerations..
Understand and Utilize the Data
Making a strong business case for the continued adoption of AI relies on surfacing the right data to the right stakeholders at the right time. It’s important to understand what data is available in each system, including your CRM, PMS, and on the AI platform itself. It isn’t always easy to know what source of data is best for assessing AI performance, but you can use the original challenges and objectives for implementing AI as a guide as you evaluate the usefulness of the AI. Finally, ensure all the stakeholders on your team have a shared understanding of the data you’re gathering and how it aligns with your organizational objectives.
Continue to Optimize
Think of AI as a bright new team member—it has the potential to be your best employee, but will take time to get ramped up. With that in mind, it’s important that you regularly audit your AI’s performance to ensure alignment with system updates and evolving processes. This includes adding and approving pending knowledge, to maximize the machine-learning capabilities of your new AI agent. You should also be providing feedback to the team that makes the AI on how conversations are going, and whether or not the roadmap for the AI aligns with company objectives. At EliseAI, we emphasize working closely with customers as we roll out new features, regularly testing product enhancements in conjunction with leading property management companies across the country.
Putting It All Into Practice
Now that you have a framework for implementing AI into your onsite operations, it’s time to find the right AI solution for your portfolio. Fortunately, EliseAI offers a wide range of conversational AI solutions, including products designed to improve leasing performance, reduce bad debt, and automate 90% of tedious tasks your onsite teams have to manage every day.