Reading the news about developments in artificial intelligence (AI) on any given day can leave you feeling a sense of dread 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 may seem that the developers and makers of AI applications are in control of its powerful potential. have lost.

But these reports lose sight of the more effective and better-managed developments that support and optimize the real thing and the exchanges that happen every day between humans and AI. When AI is comprehensively approached for how it can optimize an entire system — including the people within that system — it has a greater chance of delivering meaningful impact.

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

Bots are a good place to start.

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

In 2018, experts heralded the death of chatbots because, as text-based phone trees, they barely offered a personal or expert experience, and their impact was more of a frustration than a pathway to cost savings — and certainly not a mechanism for building brand loyalty. Today’s bots use the understanding of natural language to translate requests into intent and AI-based knowledge to converse more naturally. In addition to enabling better conversations, chatbots are the key to richer conversational intelligence. Sometimes the interactions are very simple at first glance, but they have a cascade effect that profoundly changes a series of customer experiences.

Research from my workplace, Genesys, shows 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) who understands what they need. Good bots are personalized, they know who you are and understand how to respond accordingly, for example by leveraging a customer’s profile or switching to the right agent when needed. Self-service customer engagement is toward delivering that, but businesses need to partner with a partner that can deliver at scale.

For example, TechStyle, an online retailer, implemented AI to differentiate itself from the competition. With 5 million members, 6 million calls per year and 3 million chats per year, communication is at the heart of the business. By integrating AI, TechStyle saved $1.1 million in operating costs in its first year 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 AI market. Companies also need to understand more about how success is measured on the human side of the AI ​​equation. Contact center agents are often a customer’s primary point of contact with a company.

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

In a recent study by Genesys, agents identified their strengths. More than half of respondents ranked thoroughness and completeness as their best skills, while less than 10 percent rated empathy and listening as their strongest points. If you look at this through the lens of AI implementation, there are two crucial points to consider.

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

The ultimate goal is to make the work more rewarding for the employees. This can be achieved by having the key infrastructure and insights needed to deliver better customer experiences.

AI application developers should consider how this affects not only the end user who speaks to an AI chatbot, but also the employee who interacts with AI to create a great brand experience and work experience.

This highlights the second point: the design and implementation of AI should consider empathy and how it augments and supports self-reported, lagging skills for listening and understanding. Ethical work environments that provide agents with the values ​​they most seek include AI that balances high and low-level tasks that support meeting core metrics such as average processing time, but also help agents strive for greater empathy and personalization that leads to more brand loyalty and share in the wallet.

The customer engagement employee is an AI worker, their knowledge and contributions are essential for the implementation of AI. You cannot separate the two. Cynthia Breazeal, a robotics professor at MIT, has said the next generation will no longer be “digital natives” but “AI natives.” Contact center agents are at the forefront of an AI-literate workforce in our society, and we now have the opportunity to provide the technology to support their work and better serve customers.

Is your business ready for the results AI can deliver?

The opinions expressed here by Inc.com columnists are their own, not Inc.com’s.

This post Artificial intelligence is not a strategy. It is a customer experience accelerator was original published at “https://www.inc.com/brett-weigl/artificial-intelligence-is-not-a-strategy-it-is-a-customer-experience-accelerator.html”