There are so many incredible ways that artificial intelligence (AI) can be applied across the enterprise: conversational intelligence, smart routing, agent augmentation, interaction insights. Yet there’s one form of AI that many companies choose to focus on, and it’s a coin toss as to whether their strategies are effective.
Research from Vanson Bourne shows that chatbot technology is the predominant form of AI for nearly 60% of companies today. While most agree on the importance of AI expansion, the research suggests an inability to effectively do so. Consider the contact center, where 94% of companies agree that effective AI helps improve performance but 70% feel they’re missing the mark.
There’s certainly nothing wrong with prioritizing chatbots, so long as you do it right. Some organizations need to fundamentally shift their perception of the technology to clear a path to truly effective AI. Let’s break this down further…
There’s a general misperception that scripted bots (those programmed by humans to interact and behave in certain ways) are true AI. Scripted bots are the earliest iteration of an intelligence system, having been around for almost a decade, which leads many to mistakenly believe they are the first (and therefore genuine) form of AI. These scripted bots are also widely considered AI because they are the best that many companies can do (Vanson Bourne’s data shows that these kinds of chatbots are the only “form” of AI that most businesses use effectively). Scripted bots are easier to implement with less barrier to entry, while AI-enabled bots require ample time and investment in resources.
True AI is not just a computer programmed to think like humans; the technology has abilities to autonomously solve problems and drive new efficiency gains. Companies can use a scripted bot to streamline customer service, but that solution won’t know how to analyze customer interactions to better understand next-level drivers of satisfaction like sentiment, personality, emotion and relatability. Scripted bots may be able to quickly resolve issues or have full conversations around an inquiry, but that doesn’t make them a true form of AI. Rather than being built on augmentation, these bots are built on automation. They generate data based on continuous conversations, whereas AI takes that data and analyzes it to generate actionable insights.
The good news is that chatbot technology is one of the easiest ways to begin the planned expansion of AI across the enterprise. Consider partnerships you can leverage as part of an ecosystem approach to begin doing work in spaces like voice analytics, sentiment, and customer journey analytics. For example, you could apply machine learning around chatbot conversations to better understand the types of experiences customers are having in that specific communication channel. That can help you pinpoint the top things customers are saying or top issues being reached out about.
Identify one or two relatively simple actions you can take (applications of AI that represent low-hanging fruit for your organization) to augment your chatbot strategy. Master these simpler applications of AI, then start considering how you can leverage the same kind of technology (conversation analysis, pattern recognition, etc.) across other areas of business.