If you use Siri on your mobile device or Alexa or Google at home, you know that artificial intelligence (AI) is a fast-growing component of the consumer world. Six billion devices are going to begin proactively asking for support in the near future, according to Gartner. Voice-enabled AI applications like these and others are making life more convenient for millions of people around the world.
However, the adoption of AI applications has been slower in the enterprise sector for several reasons. One may be that it isn’t clear how AI can fit into the organization’s day-to-day operations or its overall mission and vision. It’s also a piece of the technology puzzle that fits across different internal “silos,” leaving CIOs and CTOs wondering where to start first. Collaboration across business units is key to successfully using AI to its potential.
Before we launch into a roadmap, let’s define what we mean today (and perhaps in the future) when referring to “AI.” AI in its truest sense means “artificial intelligence” and has oftentimes been equated with “machine learning.” Early versions of “AI” are ones that can consume incredible volumes of data and provide a response based on the data (good or bad) that it has been receiving.
In the future, AI will mimic human instinct and reasoning, perhaps even to the point of changing its ethics and morals based on the situation. The fear factor of this will cause companies to proceed cautiously.
But, for those of us understanding AI as meaning augmented intelligence/augmented experience, the path is much clearer. An augmented experience is one that is more predictable and programmable; one where we feel comfortable receiving an outcome in line with our expectations. This is a great place to start when thinking about AI within your organization.
Many times these terms are used interchangeably. Augmented experiences can be a precursor for artificial intelligence, but they can also stand on their own.
For many organizations, the contact center is a natural place to consider an AI (augmented intelligence) deployment. That’s because many centers are already using some form of AI to provide better and more efficient service to customers.
For example, IVR systems have been in use for decades, answering questions, handling transactions, and routing inbound callers to the most appropriate agents. Chat bots are another form of AI, guiding consumers through a decision-making process and handing off those inquiries to an agent when necessary. Today, the best chat bots do not appear “human” and provide context to the agent. Context in this circumstance means all of the interaction that has been happening between the bot and the consumer. This information should be passed along to the agent, so the customer doesn’t have to repeat it and the agent is more informed about the transaction. Letting consumers know this is an automated system is necessary, so they will be more understanding if the bot can’t assist them. Over time, there will be less and less need to do this.
AI doesn’t have to appear as a customer-facing application. Many agent experiences can be enabled by AI, as well. Bot products are showing up at all major vendors to provide real-time information to agents assisting callers. Examples include popping relevant information to handle a specific situation, to enacting workflows based on the choices that an agent has made in the process.
Continue to the second part of this blog series.
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