Artificial Intelligence Is Not a Strategy. It Is a Customer Experience Accelerator

If you read the news covering artificial intelligence (AI) developments on any given day, you may feel pangs of fear and dread. From the recent UN report on AI’s potential to harm human rights to the use of AI in spyware to hack into journalists’ phones, it can seem as though the developers and creators of AI applications have lost control of its powerful potential.

But these reports lose sight of the more effective and well-governed developments that are supporting and optimizing real work and the interchanges happening every day between humans and AI. When AI is approached comprehensively for how it can optimize an entire system– including the humans within that system– it has a higher chance of delivering meaningful impact.

The Global AI Agenda, an MIT report from March 2020, found that customer care was one of the top use cases for AI. 60 percent of executive respondents believe AI will play a role in 11 percent to 30 percent of their processes– a considerable but not necessarily dominant influence on how most businesses operate. The overall acceleration of digital adoption has likely changed these metrics post-pandemic and the need to implement digital and AI solutions is now imperative to be competitive.

Bots are a good place to start.

One of the fastest areas of adoption for AI in the enterprise is chatbot applications. It’s often a good place for companies to get started with AI and see quick results. By 2024, Insider Intelligence predicts that consumer retail spend via chatbots worldwide will reach $142 billion– up from just $2.8 billion in 2019.

Back in 2018, pundits were heralding the death of chatbots because as text-based phone trees, they hardly provided a personalized or knowledgeable experience, and their impact was more frustration than a path to cost-savings — and certainly not a mechanism for building brand loyalty. Today’s bots use natural language understanding to translate requests to intent and AI-enabled knowledge to converse more naturally. Beyond enabling better conversations, chatbots are the key to richer conversational intelligence. Sometimes the interactions are very simple at face value but have a cascade effect that profoundly changes a series of customer experiences.

Research conducted by my workplace, Genesys, finds that the use of chatbots, social media and mobile apps has more than doubled since 2017. What customers really want is instant access to someone (or something) that understands what they need. Good bots are personalized, they know who you are and understand how to respond accordingly such as leveraging a customer’s profile or transferring to the appropriate agent when needed. Self-service customer engagement is trending towards delivering that– but companies need to work with a partner that can deliver at scale.

For example, TechStyle, an online retailer, implemented AI to stand apart from the competition. With 5 million members, 6 million phone calls per year and 3 million chats per year, communication is core to its business. By integrating AI, TechStyle saved $1.1 million in the first year in operations costs and achieved a score of 92 percent in its member satisfaction survey.

Supporting a growing AI-Native Workforce

These successes are the tip of the iceberg in an accelerating market for AI. Companies also need to expand the aperture in how success is measured against the human-side of the AI equation. Contact center employees are often a customer’s primary point of interaction with a business.

The volume of customer interactions agents handle has increased by nearly 20 percent on average and spiked 35-40 percent in some cases during the pandemic, according to a poll among Genesys Customer Advisory Board members. This puts tremendous pressure on agents and technology on the front lines of these interactions.

In a recent Genesys study, agents identified their strengths. Over half of respondents classified thoroughness and completeness as their top abilities, while less than 10 percent thought empathy and listening were their greatest strengths. When looking at this through the lens of AI implementation there are two critical takeaways.

First, employees need systems that support a balance between complex tasks and easy to execute deliverables that satisfy a sense of accomplishment and completion of work at the end of a workday. AI that truly augments and considers human abilities needs to support users holistically and this means balancing high touch, high-level tasks with work that satisfies the need to mark off our list of to-dos at the end of the day.

Ultimately the goal is to make the work more rewarding for employees. Having the important infrastructure and insights needed to deliver better customer experiences can achieve this.

Developers of AI applications must consider how it impacts not only the end-user speaking to an AI chatbot, but the employee partnering with AI to create a great brand experience and a great work experience.

This highlights the second point: the design and implementation of AI must consider empathy and how it augments and supports the self-reported, lagging skill set for listening and understanding. Ethical work environments that offer agents the values they most seek include AI that creates a balance of high- and low-level tasks that support meeting core metrics like average handle time– but also help agents strive for more empathy and personalization that leads to more brand loyalty and share of wallet.

The customer engagement employee is an AI worker, their knowledge and contributions are essential to AI implementation. You cannot separate the two. MIT robotics professor Cynthia Breazeal has said that the next generation will have moved beyond being ‘digital natives’ they will be ‘AI natives.’ Contact center employees are at the cutting edge of an AI-literate workforce in our society and we have the opportunity now to provide the technology that will support their work and better serve customers.

Is your business ready for the outcomes AI can deliver?