It’s estimated that by 2030, virtual assistants will handle 30% of interactions that normally would be handled by people. This can be a potential game changer for your customer experience, but beware! If customers have a bad experience with your chat solution, that can negatively impact their perception of your brand.

Every company is unique and has different conversational AI needs. While leaders might want to build their own in-house solution to cater to these distinctive needs, this often creates more challenges than it solves. The money, resources and internal expertise needed to create a solution are significant, and many organizations find that they need to launch a “rescue project” to fix their initial do-it-your-self solution.

Getting it right the first time is necessary in an environment where conversational AI is becoming increasingly more important to the success of CX strategy. Below, we’ll explore some of the most common challenges with building your own AI system and how to avoid these pitfalls with a better, more cost-effective solution.

Understand the Technological Limitations of DIY Solutions

Successful conversational AI solutions require a lot of diverse training data — ideally millions and millions of interactions, conversations and other data points. Companies creating their own solution may find it difficult to collect all the data they need to create a high-quality solution. While they’ll be able to program certain specific questions the AI will encounter, customers who have more complex questions will have a harder time getting the answers they need.

Further, DIY projects also require the use of machine learning, artificial intelligence, automatic speech recognition and other technologies that only skilled experts can work on correctly. These technologies are crucial in that they help make sure the Intelligent Virtual Assistant (IVA) understands customer intent and knows how to respond appropriately. When companies partner with an experienced technology vendor, they can avoid these complications and instead have immediate access to a solution that has been extensively trained to understand a wide range of questions and handle diverse requests.

Meeting Customer Experience Expectations

Customers increasingly prefer to communicate first with an IVA rather than a human agent. Maintaining a DIY solution that can continually wow customers is an ongoing battle, especially as customer behaviors and expectations shift over time. A failed DIY conversational AI system can cause many different unwanted outcomes for companies. For example, when an IVA can’t comprehend customer questions or provide an answer in a helpful way, that could lower both customer satisfaction and customer retention.

An intelligent AI solution must also integrate well with other platforms vital to CX — including the analytics technology that lets organizations observe customer trends and behaviors as they interact with the brand. When organizations create their own AI solution, they may encounter a whole new problem in deciding how to get real, actionable CX insights. Without a technology stack that can integrate with your DIY solution, there will be many missed opportunities for insights into the customer journey. Third-party conversational AI solutions offer a much more simple way to integrate conversational and customer journey platforms.

Learning Opportunities

Keeping the Right Talent on Your Team

Behind every great conversational AI tool is a team of experts with the knowledge, time and resources to create and constantly update the solution. Outside solutions providers will have the talent and resources to oversee the solution, but this process is much more difficult to achieve within your own internal team. A very specific skill set is needed, and losing a vital team member with those skills can leave the AI solution in a vulnerable place. In fact, a recent survey of IT/business professionals found that 56% of respondents believe the chief obstacle to AI deployment is a skills shortage.

One of the major skills a team needs is natural language processing. Customers want to interact with IVAs that understand the flow of conversation and respond in a way that is not impersonal or robotic. Finding a specialist with experience and skills to do this type of work requires companies to pay a large salary. (IBM estimates that salary is around $175,000 a year or more.) This simply is not the most cost-effective way to offer an effective conversational AI solution. By partnering with the right third-party solution, companies can avoid these costly human capital investments and still get the technology to communicate with customers effectively.

Finding the Right Conversational AI Partner

For a consistent, reliable conversational AI solution, avoid the DIY project. Skilled specialists offer the technical knowhow and human touch that allows solutions to grow and improve over time, and the best way to access both this technology and these technology experts is through a third party. Solutions like Interactions give you access to all these resources and talent, so you don’t need to worry about all the details that make DIY solutions difficult to achieve.

Learn more about Interactions conversational AI solution here.