Conversational AI Is Here to Stay, but Don’t Overlook the Risks Before Basking in the Rewards

We’re at a point where organizations should not bypass implementing and using AI in some capacity in their operations. The benefits of the technology are too great to overlook in how it can augment employees in their work and solve business use cases in more efficient ways.

Conversational AI chatbots can help simplify and streamline entire processes through the automation of day-to-day activity. Its benefits are unmatched – whether you’re an HR professional who uses this technology to optimize onboarding and recruitment with ease or a call center agent who needs to tap into the right information for customers in seconds.

But this is not a technology that you can implement and then walk away from. To maximize its value and benefits, it requires continuous monitoring and iteration. On top of that, as with any new technology, the risks involved need to be fully realized. Accuracy and security are at the top of the list and if left unchecked, an organization can expose itself to negative reputational or even financial repercussions.

With stakes that high and the presence of conversational AI chatbots increasing by the day, it’s critical for organizations to overcome these hurdles from the start so that they can fully reap the rewards that this technology will bring.

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Hallucination and reliability issues

Accuracy remains a problem as generative AI continues to proliferate in the market. According to a report from Aporia on AI models, 89% of machine learning engineers say their LLMs exhibit signs of hallucinations, for example.

It’s an issue that’s even made headlines. Google’s new AI Overview feature was found recently to recommend that users add glue to their pizza when baking so that they can get the cheese to stick better. Google claimed the issue was due to an information gap and a misinterpretation of language when searching for results.

For all the incredible capabilities and thoughtful responses that AI can provide, hiccups can and will happen, and the ultimate cause of this problem is improper AI training. There’s much that can be done to fix this, and it starts with training data. The varying levels of training data and algorithms used from model to model is the underlying issue here. Thus, ensuring that AI models are provided with the highest quality data is the key to the chatbot operating as error and bias-free as possible.

Direct human feedback is another solution to this, and it’s also where increased voice functionality is a benefit. With all the added contextual information that voice provides, it’ll become a crucial part of AI model training moving forward. Business leaders expect the tools their organizations use to operate to be accurate, otherwise they risk damage to their reputation and customer base. They can’t afford to throw their weight behind an AI that is putting out inaccurate information alongside all the factual insights it’s generating.

Having to frequently look over the chatbot’s output defeats the purpose of the rapid and informative information it’s capable of providing. If this problem isn’t fixed, it’ll cause serious problems for businesses when it comes to trust from its customers.

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Data privacy and security

While hallucinations and accuracy remain issues with AI chatbots, recent data shows that it’s not the only problem that’s keeping business leaders up at night. According to a new study from Alteryx, while over three-quarters of organizations said there was business value in using generative AI, 80% listed data privacy and security concerns as their biggest concerns.

With AI rapidly becoming integrated into our daily lives, it’s important that organizations get data security right or risk losing external confidence in their solutions. This underscores the fundamental shift that’s emerging as technology is ingrained in some capacity in every business’s operations and infrastructure.

Security is often the first question that an organization will ask a prospective AI provider about before integrating the technology into their processes. They’ll be particularly interested to understand how the model retains data, if the model is used to train itself, and about data leak risks. This is where the benefits of utilizing a small language model come in handy, where it can be integrated and deployed into an organization’s on-premise environment, so there’s no outside access to the internet required to utilize the full capabilities of an AI chatbot.

Ultimately, any data sharing practices and storage need to comply with stringent privacy regulations, as well as regular security monitoring and data encryption. Failure to meet strict standards can be detrimental as any data breaches can harm a businesses’ public standing and potentially trigger legal or financial penalties.

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AI is the key to better productivity

Generative AI use has boomed, and business leaders are seeing the results, as 77% reported running successful AI co-pilots within their organizations. This shows that many organizations are placing their trust in this technology, and are now being rewarded with deployments that are paying dividends for their business solutions.

But it’s important to remember here that AI models benefit from a human touch and being iterated continuously, otherwise if not updated or left unchecked, it can cause serious issues. When this proactivity is fully acted upon, AI will continue to be a tool that enhances processes and helps us in so many different ways. It’s been remarkable to see its use cases and integrations grow across any sector imaginable.

For example, in healthcare we’ve seen conversational AI chatbots transform the digital experience for patients by acting as an efficient virtual assistant for all of their needs. From quickly analyzing user responses to prompts regarding symptoms and risk factors to improving the scheduling process and helping the patients make the right appointment, this technology can improve satisfaction on both sides.

In an HR setting, a conversational AI chatbot can streamline new candidate onboarding and employee retainment. By optimizing the common tasks that make up these processes, it can help HR professionals better identify the right candidates for open positions. When an HR team isn’t swarmed with applications to analyze, they’re freed up to develop stronger relationships with the most promising candidates and keep current employees satisfied.

These examples show how speed, efficiency, and personalization can all be amplified when AI technology is integrated into business solutions. Simply put, the experience for internal and external users is made better and organizations can directly see how technology like a conversational AI chatbot can help them accomplish their objectives in a more productive fashion.

Conversational AI is such a fascinating technology because of how it’s being used to solve business needs that have existed for decades in new and exciting ways. The value it’s creating for organizations in only the last several years has been great to see, and there’s no signs of slowing down. It’s too important of a technology to disregard, and it’s time we all move forward with it.

But we also can’t sit back and let this technology fully take off without taking into account the risks around accuracy and security. Conversational AI chatbots are here to stay, and they’ll only keep improving as they become more skilled at processing requests quicker and even more personalized, like a true personal assistant for every use case that’s needed.

It’s important that all stakeholders truly get this right as this technology continues to expand exponentially so that they can have the greater functionality and peace of mind that it can bring.

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