As we have seen across multiple industries, AI changes and accelerates most repeatable processes, helping organizations meet their objectives faster. This new rhythm, however, also means that implementing this innovative technology represents its own challenges and opportunities.
In this entry, we will discuss some of the challenges of implementing conversational AI and how to address them effectively.
The era of hold times is coming to an end. Most modern businesses have realized that their customers are busy people, with unstructured lifestyles and schedules looking for the best service possible 24/7. As a result, implementing self-service options to provide around-the-clock service as well as the option to solve common problems without any additional guidance is predominant across most industries.
While before it may have been commonplace to wait for hours for a representative to take your call, today, customers want fast answers across channels. This phenomenon in turn changes how businesses think about customer support, from being a passive or reactive activity to becoming a proactive system. Instead of responding to problems, the best businesses identify behavioral patterns and with the help of conversational AI technologies build a set of self-service options that anticipate potential issues for their customers.
Modern businesses understand that customers are vital and that, unlike any other historical period, they have more options to choose from as well as information at their fingertips. Adapting and becoming a proactive brand is no longer just an option, but a norm that sets category leaders apart from their competitors.
Each business has unique challenges in implementing conversational AI. However, given our experience, we have found a few patterns worth exploring if you’re looking to implement this technology into your business.
Language is a very complicated and nuanced system. Even if you speak the same language, are from the same geographical location, and have a similar background, misunderstandings can happen. In our current multilingual, and culturally diverse environment, this challenge becomes even more relevant, especially for businesses that want to ensure their conversational AI solutions are relevant and helpful for their customers.
AI technologies are efficient at recognizing patterns and executing them. Language, like most human activities, follows multiple patterns, making it a great application for AI bridging the customer service gap. Nonetheless, communication is also a contextual and nuanced dimension of our interactions, and having multiple dialects and using slang makes it even more difficult to implement a genuine automated conversational AI solution.
Find a partner that specializes in natural language processing but also has a clear strategy to integrate with your current business and systems. Enterprise expertise when implementing conversational AI is vital to ensure long-term success. Keep in mind that conversational AI is not just a technological integration, but it also touches upon multiple aspects of the business that not all vendors dominate.
Having the right data when you manage large organizations with multiple departments and priorities is a challenge for any conversational AI partner. On the one hand, ensuring the data is as accurate as possible can be more complex than anticipated, and on the other, even if the data is accurate it may need to be more horizontal across the organization leading to siloed information and poor strategic choices.
The lack of data hygiene can also affect your end customers by providing inaccurate information or failing to solve their concerns with your services or products. Without the right information, not even the most powerful conversational AI solution can proactively help your customers. Ultimately, it is up to their human counterparts to ensure data quality.
Once again, to circumvent this particular issue it is vital to find a partner that prioritizes the quality of the information and creates multi-departmental bridges to reduce potential errors. Moving forward with a vendor that knows how to leverage complex business ecosystems to your advantage is the best way to ensure data quality, consistency, and therefore, a higher potential for informed decision-making.
Conversational AI providers are one the fastest growing new industries. As a result, there are multiple options and vendors to select when implementing conversational AI that may have developed efficient technologies but possibly failed to create the integrations that mature businesses require in order to run efficiently.
For instance, legacy systems are generally a challenging scenario for conversational AI vendors given the ad-hoc nature of the integration. Inexperienced providers without the right understanding of enterprise cycles and the challenges of integrating with legacy systems may not be the best partner.
Find a conversational AI technology partner that excels both at the technological and enterprise management level of integrating with organizations. Implementing conversational AI is not just an important effort in terms of technology but it also represents understanding and navigating complex legacy systems, inter-departmental stakeholders and priorities, and building on top of your foundations.
Technological innovations always have detractors who are not yet ready to try anything new. To some conversational AI providers, the job is done when the technology is in place, regardless of user adoption and overall perceived value. However, companies with enterprise-level experience generally have more mature mechanisms not just to set up conversational AI, but also to ensure user adoption.
Starting with proactive communications that anticipate potential issues or provide service or product updates is a softer way to gain customers’ trust in conversational AI. Sending a timely notification, offer, or reminder can be a genuinely helpful way to help detractors understand that having to talk to a human agent to solve a problem is not always necessary.
Building user feedback loops that start with lower friction interactions is a good place to start. While you can of course build an entire conversational AI service solution, sometimes, starting with proactive communications where customers are less likely to be under stress might have better results and help you build trust.
Large enterprises generally have a diverse and multilingual set of customers. For conversational AI technologies, this represents a potential problem given the complexity of training models in multiple languages and dialects.
Failing to build a strong understanding of every process that can then be extrapolated across multiple languages can be harmful to your business, and damage customer’s trust.
Ensuring that you work together with a provider that understands how complex this process can be and takes the time to build multilingual solutions is the best way to ensure all your customers get the service they need.
Integrating conversational AI solutions is an ongoing process that requires permanent updates to ensure effective operations. Beyond the initial steps to introduce conversational AI, an effective and permanent solution requires significant resources, expertise, and alignment to ensure customer satisfaction and business success.
Choosing a technology partner that has permanent customer support to ensure your conversational AI solution meets your standards is essential. Rather than prioritizing those that only shine in terms of technological infrastructure, prioritizing a partnership with conversational AI providers that understand the intricacies of larger and more complex processes can make a difference.
A common mistake when implementing conversational AI is prioritizing the wrong KPIs from the get-go. While the right indicators may differ according to your business objectives and priorities, generally, the impact must be a multi-departmental agreement that works for the business and your customers.
Unfortunately, many companies simply adopt their current customer service KPIs with a new tech ecosystem that does not match them.
Remember that setting up conversational AI in your business is not just a technological process but also an internal and external culture change that requires a nuanced approach.
Being thorough about alignment, measuring the right things, and understanding and differentiating leading vs. lagging indicators are some of the best practices for creating long-lasting impact with conversational AI.
While conversational AI is a great tool to solve many different scenarios, it does not have the capacity of emotional understanding a human agent has. Recognizing and appropriately adapting the right type of inquiries to be treated by a conversational AI solution vs. a human agent is one of the most important starting points.
If users are under extreme emotional conditions, generally speaking, a conversational AI solution that identifies such cues and connects them with a trained customer representative is a good choice. Likewise, if the reason customers are reaching out is relatively simple and a routine procedure rather than anything else, letting them use a self-service option to fix it might be better given that it does not have any emotional load that requires human supervision.
Finding a solution that does not simply see conversational AI as a replacement for human engagements is the priority for enterprises. Rather than pretending that the emotional intelligence of an IVA solution with AI can replace an experienced human agent, the objectives must be to build the right cadences and journeys to ensure that ultimately the business solves problems in the best way possible. Sometimes, that may be quickly transferring the call or chat to a human agent while in other instances it may mean making it easy for customers to fix issues independently.
Conversational AI is trained on data that companies must curate to prevent any cultural misunderstandings. Nuances and sensitivities are generally something where human agents excel, so if the particular scenario at hand is more complex than anticipated, a system to quickly transfer to a rep must also be set up.
Having said all that, however, it is important to have a partner that has the patience and permanent service to allow enterprises to adapt to the cultural landscape around them. Integration and kicking off the new conversational AI solution is just the beginning of a process that evolves and it’s alive and must adapt to cultural movements.
Rather than focusing exclusively on product features, enterprises should take into account the capacities of their conversational AI provider to prioritize cultural complexities and sensitivities permanently. Implementing conventional AI is just the beginning of a process that requires training, updates, and changes.
Not all conversational AI solutions have a similar price point. While that may seem like a great characteristic of choosing this sort of technology, it actually can become a hurdle that companies must overcome to choose the right partner for their business.
Some businesses have less complex service ecosystems than others, meaning that a provider on the cheaper side of the spectrum is ideal. Most mature companies, however, are more complicated and require a technological partner that might have a higher price given its experience across all aspects of the business, not just the technology itself.
Prioritize the type of priorities and expectations of conversational AI implementations. Afterward, find the technology partner that actually matches your needs.
Don’t underestimate the potential additional costs that can occur down the line with providers without the proper experience at an enterprise level.
Mosaicx is the conversational AI of choice for robust and mature enterprises. With multiple decades of experience, as well as a technically superior product and white-glove customer service, we help enterprises meet their goals. Talk to one of our solutions experts and learn how to implement conversational AI in a way that enables business growth and delights your customers.