Artificial intelligence (AI) is rapidly changing the world as we know it, and the title insurance industry is no exception. 

AI offers exciting possibilities for title & escrow companies to increase efficiency and improve employee satisfaction by automating many repetitive and manual tasks in the closing process. (Read here for some common title & escrow AI use cases). 

Title & escrow companies that embrace AI now will be well poised to take on future market cycles by providing exceptional closing experiences with fewer resources. Effectively bringing AI into the organization requires a mindset that embraces ongoing learning, company-wide planning, and a forward-thinking adoption strategy. Implementing AI may seem daunting, but there are some straightforward ways to get started.

Build a curriculum that prepares staff to work alongside AI

With the introduction of AI, businesses must invest in training programs to empower employees with the knowledge and skills they need to work collaboratively alongside the technology. A robust AI curriculum may include the following elements: AI literacy training, critical thinking exercises, and hands-on experimentation. 

AI literacy training

A solid understanding of AI terminology is only the starting point for AI literacy. Staff must also understand the strengths and limitations of AI and how these factors influence one’s decision to use the technology for a particular task.

For example, because AI chatbots are known to sometimes create false results, title professionals should understand that chatbot outputs should not be taken at face value and should always be reviewed before they are sent to a client or included in a file. This limitation is also important when evaluating AI tools. Ask yourself, are they built for title professionals to be able to easily review the outputs?

Below are some of the current constraints of AI technologies:

  1. Dependence on data quality. If the data the AI model is fed is not accurate, the tool could provide faulty outputs or even hallucinations (i.e., completely fabricated outputs). 
  2. Potential for bias or harmful content. AI models are typically trained to avoid offensive keywords or overtly toxic language; however, AI lacks the emotional intelligence to understand when things like tone, word choice, and cultural norms matter. 
  3. Ethical and privacy concerns. Current security and privacy concerns related to AI involve potential vulnerabilities in AI systems, the risk of unauthorized access to sensitive data, and the need for robust safeguards to protect against cyber threats and breaches.
  4. Additional unknowns. As new AI advancements hit the market, there is potential for additional limitations to come to light as AI is applied to new scenarios and contexts.

Critical thinking exercises

In addition to learning about the strengths and limitations of AI, it’s also valuable for staff to work through sample exercises in a collaborative learning environment. Encouraging team members to try out AI tools and review the results in controlled exercises allows them to make mistakes in a practice capacity rather than in the real world, where improper AI use could, in the most severe cases, lead to catastrophic results for the business, such as compliance infractions or file errors.

Hands-on experience with AI tools 

The power of AI and its limitations are best understood when one can experiment with the technology. One place to start is with AI chatbots. Chatbots are computer programs that simulate human conversation, allowing users to ask the chatbot questions, obtain information, and even receive assistance with tasks. 

Provide your team with the following best practices to start experimenting with AI chatbots: 

  • Be clear and concise when formulating your prompts. Write prompts in sentence form rather than as questions and use formal and correct grammar.
  • Provide the chatbot with as much information as possible to facilitate its understanding of your inquiry and list the most important information first.
  • Don’t include information in your prompt you would not want in the result. It will use the content in prompts to aid the generation of results.
  • If you don’t get what you were expecting the first time, refine your prompt.
  • Break down complicated prompts into step-by-step inquiries.
  • Always double-check the output of the chatbot for accuracy.

While AI chatbots are a great starting point to experiment and understand the power of AI, these tools are not the most helpful solutions for title professionals to start using AI in their day-to-day workflows. Chatbots are standalone AI tools that require agents to step outside their workflow and into a new application. This system hopping results in slowdowns and the potential for error when information is rekeyed back into the title production system. Additionally, most chatbots don’t possess a specialized understanding of the title & escrow industry, which limits the quality and accuracy of the outputs these chatbots can produce.

For more impactful results, title & escrow companies should deploy AI solutions that work directly within their core production software or with AI tools that are specialized for closing-related tasks. (We cover more details on why embedded solutions offer greater value than standalone AI tools at the end of this article.) 

Develop company-wide AI use policies

In addition to training employees to make thoughtful decisions with AI, businesses must also develop hard and fast policies around AI usage within the organization. These policies will reduce any gray areas and also enable faster decision-making when it comes to selecting AI vendors.

Step 1: Assess AI use cases and objectives across the company

This step should involve leaders from across the organization who can each provide insight into how their teams or departments will benefit the most from AI solutions. By gathering a comprehensive understanding of use cases, the organization can better identify where overlaps exist to ensure that policies address current and future needs across the business.  

Step 2: Create a governance framework 

A governance framework is a set of rules for how AI will be managed and used within the business. The governance framework includes parameters for the day-to-day use of the AI as well as the broader deployment and maintenance of AI. 

An effective governance framework includes the following elements:

  1. How and when employees can use AI. Ethics, responsibility, data privacy, regulations, and security should all be considered when developing these parameters.
  2. Steps employees should take to validate AI-driven decisions. 
  3. Data privacy and security requirements for all AI tools. 
  4. Details on how the AI policy will be implemented, monitored, and enforced.

Step 3: Monitor performance and update policies regularly 

AI is changing fast and businesses must remain vigilant to ensure existing policies are meeting the evolving demands of the technology. Continuous evaluation and regular updates to policies are essential to adapt to tech advancements, regulatory changes, and evolving ethical standards.

Updates should not happen in a vacuum. A transparent and collaborative approach involving key stakeholders will help businesses proactively address challenges and build trust across the organization and with outside parties. 

Leverage embedded AI functionality rather than integrating standalone AI solutions 

When it comes to adopting AI tools, a forward-thinking strategy is essential to ensure sustainable operations as the technology evolves. One factor that is often overlooked is how the technology is introduced operationally. There are two paths for title & escrow companies to choose from:

  1. Integrate standalone AI tools into the technology stack
  2. Work with title software providers that offer embedded AI functionality

AI that is integrated directly into title production software enables title professionals to access AI-powered assistance without leaving their core workflow. This is a powerful advantage for several reasons:

  1. Contextual awareness. When AI is embedded into the system, it has visibility into the entirety of a transaction. This contextual awareness improves the accuracy of AI outputs compared to standalone AI tools that are disjointed from the core system. Contextual awareness also allows the AI to automate more tasks. For example, AI that’s embedded into the system could read a message from a client and then automatically pull data from that message into an order. 
  2. User-centric. Embedded AI empowers users to remain within their core systems and established workflows. This not only expedites the adoption of AI but also improves overall operational efficiency. Rather than making manual decisions about when to deploy AI for a particular task, AI functionality is integrated seamlessly into the process and can easily scale with market volume or company growth. 
  3. Reduce technical debt. Multiple, separate AI integrations are expensive to execute and manage. Plus, a web of disjointed AI tools creates the risk of technical debt in the future when IT teams must streamline a web of fragmented tools into a manageable and trackable system.

Take the next right step 

For title & escrow companies seeking to leverage the power of AI, embedded AI is an ideal starting point. It offers a robust, user-friendly, and cost-effective solution that can revolutionize the way title professionals work. 

To learn more about how your team can take advantage of Qualia’s embedded AI functionality, click below to get in touch with a product specialist.

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