The future of customer conversations

The future ofcustomerconversationMore than words, more than AI

Talk is cheap, or so the old saying would have us believe. In reality, conversations can have tremendous value. This is true in your personal life. It’s also true for your business. How can you combine people and technology to enable conversations that deliver real business value?

Conversation is fundamentally human. It’s the heartbeat of our families and relationships—and even our societies. Conversations reveal our personalities and let us express our values. They also allow us to understand others and to build the relationships central to our lives.

Conversation is also the foundation of successful businesses—underpinning productivity in the workplace, as well as relationships between brands and customers. Good conversation is not an ‘add-on.’ It’s the lifeline of your business and a measure of how well it’s doing. Conversations enable a brand to express purpose, learn about customers and strengthen relationships.

“Talk, as a phenomenon of social life, exists only to be understood. It is designed by humans, for humans to get every facet of life accomplished. Webuild, maintain and end our personal and professional relationships through talk. We buy and sell. We get and give help.We are excited, persuaded, irritated, embarrassed and consoled in response to the things others say to us. Talk is the tool we have to do all of these things.”1

Good conversations mean good business. U.S. insurer Lemonade lets customers sign up for insurance and file claims in minutes via conversational technology.2

The future of customer conversation: More than words, more than AI 02

Although conversation is natural and intuitive, it’s also a complex construct. Even thesimplest interaction has layers of richness and nuance—it takes effort and understandingto get conversation right. For your business, there is an added challenge: increased demand for communication from today’s “always on” generation. We’re moving to a world where customers expect to engage with brands at any time, across multiple devices, channels and touchpoints. Customers also expect interactions to be in tune with their personal preferences and schedules.

These expectations are reflected across product and service categories. A bar set by a brand in another industry will soon become the standard for yours. According to recent Accenture research, 61% of leading companies say their customers’ expectations are shaped by the most relevant, real-time and dynamic experiences they encounter across all industries. Those experiences impact how and why these leading companies innovate.3

Rethinking the business of conversationAll this change is forcing companies to rethink how they communicate with people and organize the entire business around the delivery of exceptional experiences. Every time customers interact with your brand, they bring a purpose, problem, or a need. They also come with expectations for how quickly or easily that outcome will be realized.4 How will you deliver experiences that respond to customers’ new, often unmet and frequently changing needs—and enable them to achieve their desired outcomes?

More than three-quarters (77%) of CEOs have indicated they will fundamentally change the way they engage and interact with customers.5 As a result, many organizations are turning to conversational artificial intelligence (AI) to meet communication demands, with adoption of chatbots and conversational interfaces reaching unprecedented scale. In fact, in the wake of the COVID-19 pandemic, organizations across industries scrambled to set up chatbots and other conversational AI solutions to handle the spike in call volume. IBM witnessed a 40% increase in traffic to Watson Assistant from February to April 2020.6 Market research and analysis suggest this uptick is only the beginning.

~$5 billionSize of global

conversational AI market in 20207

$13.9 billionExpected size of global

conversational AI market by 2025 at a CAGR of

21.9%8

70% by 2022Percentage of customer

interactions involving emerging technologies

vs. 15% in 20189

Tectonic shifts in customer engagement

The numbers are compelling. But can conversational AI get the words right?


Value interrupted“Conversation is not a new interface.

It’s the oldest interface. Conversation is how humans interact with one another, and have for millennia. Unfortunately, overly literal interpretations of the idea are leading to systems that are hard to use. Being able to exchange text messages with a bot doesn’t necessarily make it easier for people to reach their goals. We must go deeper. Otherwise we’re just making things harder on ourselves and those we’re designing for.”10

Want to deliver lackluster customer experience? Then design experiencesaround the needs of your company, rather than the needs and preferences of your customers. Better yet, design experiences to get customers to do things how the company wants, rather than helping customers do things how they want.11

Accenture research suggests that current conversational AI solutions often fall short in meeting customer expectations. In a 2019 study, one-third of customers who started in chat (whether live or AI-based virtual agents) needed or wanted to go elsewhere to co mplete their inquiry or transaction.Chat had the lowest rate of first-contact resolution among the channels we studied. Furthermore, of customers who exclusively used online chat, less than half (48%) said they would want to use it again next time.12 These experiences have left many people distrustful of chatbots for anything but the most basic tasks.13

At best, poor-quality conversational AI represents missed opportunities. At worst, it could expose your business to reputational damage and even litigation.

The quest for truly human-centered conversationWhat’s causing conversational AI to fall short of the intended customer and business benefits? Some organizations have focused on replicating human interaction in a limiting, narrow way. They leverage conversational AI in the form of basic chat assistants, for example, instead of using AI to augment conversation in subtler, richer ways. In mistaking human-like conversation for human-centered communication, they are missing opportunities to reimagine experiences that truly meet the needs of today’s customers.

They are failing to understand the complexity of conversation and the diverse mechanisms involved in even the most basic interactions. What’s more, they are glossing over the challenges and tension points this kind of technology can create.

As we have seen, when experience technologies are scoped based on what they can do rather than what they should do, they become a customer experience “bolt-on.” They fall short in supporting the business purpose and brand promise. Even worse, they become an efficiency play that makes customer experience worse—supplanting meaningful, human-centered conversations in the name of lower business costs.

We’re now at a stage where AI technology has advanced and can deliver far more than higher efficiency. It can help businesses enhance customer experience and drive growth by crafting supremely successful, impactful conversations.How do we make that happen? How can we leverage the potential of AI to create truly human-centered conversation? How can we understand and unlock the unique capabilities of AI technology to solve customers’ problems? And how can we take advantage of AI’s potential to enrich and enhance conversation, engaging customers in new and exciting ways?

A new lens for creating AI-powered conversationsTo start, we should distinguish between AI that mimics human conversation and AI that enhances and augments it. While there’s a time, place and use case for basic conversational interfaces, there are less obvious and perhaps more powerful ways to leverage technology in the service of conversation. Identifying them means understanding the distinct characteristics of different types of AI, and how each can be harnessed to augment communication, overcome human limitations, and meet customer needs head on.

It may be tempting to jump straight to a technology that offers a seemingly clear solution to a problem. Instead, take a step back and consider the context of that technology. What needs is it addressing from a human perspective? What can it offer that enhances human communication and activity? What are the implications of that technology from an ethical and societal point of view?

Don Norman14, whom many credit as the father of human-centered design, talks about “affordances”15—namely, the actions and activities users can perform with different kinds of objects or technologies. To put it more simply, affordances are what AI can offer to the user.

When applying AI, what if we focused on affordances as opposed to technologies? Might this approach empower us to solve the human challenge with the right kind of conversation, delivered in the right way? Might it help us unleash the unique capabilities of AI to engage customers in new and exciting ways—without losing sight of the purpose and context of the conversations we’re having? To power purposeful conversations, enrich customer experience and move beyond limited efficiency gains, design your AI-powered conversation with an eye toward the rich context of AI systems.


View the potential through this three-part lens:

01

Augment the human: How can the human-like qualities of AI enrich conversations?

Humans employ a whole host of mechanisms to faciliate communication—visual, auditory, emotional, to name a few. AI can be used to reflect some of those human-like qualities, which can make for communication with greater meaning and better outcomes.

02

Magnify the machine: How can we make the most of AI in the service of conversation?

Instead of getting machines to play by our rules, why don’t we play by theirs? AI systems possess features unlike any mechanisms we employ in human-human conversation. Consequently, they can be leveraged in powerful ways to create conversations and experiences that go beyond what’s possible with people alone.

03

Embrace ethical AI: What are the potential pitfalls to be aware of?

Finally, the use of advanced AI presents ethical tension points. Left unaddressed, these tension points can cause significant damage to the user, the brand, and society at large. When applying AI, enterprises must ensure that these tensions are managed in a way that aligns with their brand and purpose.


Augment the human: How can the human-like qualities of AI enrich conversations?

01

When incorporating technology in the service of conversation, it can be helpful to break down the various mechanisms that humans employ when conversing. That mechanism might be visual, and so the technology might augment the visual elements that can play a part in conversation. It might be verbal, representing what people hear and how that is intertwined in conversation. Or it might be written and relate to what people read.

These can be described as auditory, visual, linguistic and physiological affordances of AI.

Focusing on how AI systems can augment or extend human cognition can help us unlock more meaningful conversational experiences. After all, conversation is fundamentally driven by what we hear, see, read and feel. Enhancing these capabilities or senses to create more meaningful interactions allows us to unlock value and enhance the user experience. Although AI systems are complex, we can view them in simple terms—for example, how machine vision can help us see, how natural language understanding can help us hear, and how machine learning can help us have more productive conversations.

“We often hear about how AI can be used to automate mundane tasks and free us up to do other things, but we rarely talk about what those other things are. What about an alternative perspective: how might AI help us do the things we love, but better?”Connor Upton, Group Design Director Fjord at The Dock16


Auditory affordancesListening is a fundamental part of any conversation. AI technologies offer affordances that reflect auditory mechanisms of conversations. For example, voice assistants like Alexa and Google Assistant use conversational AI in the form of speech-to-text translation and natural language processing to “listen to” users. They then employ synthetic voice technology to respond, or “talk” back. This technology has advanced to the point that it doesn’t just understand meaning; it also can pick up on user emotions. Tonal recognition analyzes tone to assess a person’s emotional state—and even their health. Amazon Alexa’s team can measure valence (whether emotions are positive or negative), activation (whether the speaker is alert and engaged or passive) and dominance (whether the speaker feels in control of the situation).17

This technology can be used to help people, but it can also be used to manipulate—and so this capability introduces some ethical tension points (more on that later).

For example, SoundSee microphones can be used on an automated vehicle in a warehouse to map the acoustic signatures of various machines to monitor their operational health.18

Visual affordancesAI can expand human senses, leveraging technologies such as computer vision as a match for sight. Consider the example of Dhristi, an AI-powered solution that combines image recognition and natural language generation to improve the way visually impaired people experience the world around them.19 This technology picks up on the number of people in a room, their ages, genders and even emotions based on facial expressions. It then plays those insights back to the user.

Elsewhere, augmented reality and virtual reality provide visual affordances that advance conversations between organizations and customers. These technology provides spatial and contextual awareness that can be key to meeting conversational goals. Companies like Techsee are using these techniques to help customers perform their own repairs with the help of a company representative. Similarly, computer vision can be used to perform a remote diagnostic on devices, avoiding service costs for the business while saving customers’ time, stress and frustration.

TechSee.me’s augmented reality technology provides remote assistance. Using AI-powered conversation and computer vision, it guides users through the repair of their coffee machine.20


Physiological affordancesEffective conversation is not just about words—nonverbal cues and gestures also enhance meaning and emotion. AI technology is advancing to help these systems capture and even relay back nonverbal communication, including body language. How can we design conversations that come closer to the sophistication and subtlety of human-human conversation? Many conversational interfaces present multimodal interfaces, having the ability to receive input and/or deliver output in more than one way. Some of them blend voice recognition, touch and graphical user interfaces. Others employ more complex interaction behaviors, such as eye motion, gestures, facial expressions or even emotional or cognitive states.

SimSensei Virtual Human Interviewer23 provides healthcare decision support. It tracks and analyzes facial expressions, body posture, acoustic features, linguistic patterns and behaviors like fidgeting.

It uses these multimodal signals to identify psychological distress correlated with depression, anxiety or post-traumatic stress disorder. Human clinicians use the results of this interaction and analysis.

Linguistic affordancesWhen it comes to enhancing conversation, AI brings many linguistic affordances. Intent recognition can be used to understand what people are requesting and the meaning of that request. AI-powered translation enables real-time translation and speech-to-text to enhance understanding and improve conversation. Natural language processing and machine learning can enable machine to digest and make sense of huge volumes of content—in other words, to “read.” And with the development of technology like GPT-3, OpenAI’s powerful new language generator, machines can even write news articles.21

Conversational AI can process text to extract meaning and engage in conversation with the user. Using chatbot technology can help scale personalized communication and achieve powerful results. For example, Pounce22 is a custom virtual assistant for Georgia State University, created to prevent “summer melt”—the phenomenon of one infive students enrolled in springtime droppingout due to the complexity of the admissions process. It helps students by sending timely reminders and relevant information about enrollment tasks, collecting key survey data, and providing immediate answers to student questions around the clock. In the first year of implementation, the app reduced summer melt by 22%.


developed a virtual customer care agent that allows a conversation to flow over multiple days and with multiple actors, taking advantage of the affordance of asynchronous communication. Consistency and efficiencyWhen it comes to speed, efficiency and consistency in customer relations, there are some clear advantages to machine-human conversation. Well trained AI should be able to provide the response to an infrequent, complex question just as easily as a common, simple one. Furthermore, it shouldn’t need extensive onboarding when you launch a new productor service. High levels of consistency and standardization are key features. But there are downsides to this affordance, as humans are more adept at tailoring conversations to the context and person they are interacting with.

However, the efficiency of AI and immediate access to data it offers can, in fact, be usedto enhance human-human conversations. AI-enabled conversational assistants aren’t just getting customers basic info they need; behind the scenes, they’re also feeding human agents intelligent data and analysis to deliver better, faster outcomes without customers everbeing aware.25

Accenture is working with clients to develop AI that assists human agents with document suggestions, response suggestions and expert conversations.

Fundamentally different from us in many ways, machines can do things humans cannot. Always on and never tired, AI systems afford many benefits over human-human interaction. To tap the full potential and value of AI for effective conversation, we need to embrace the non-human capabilities of AI.

AvailabilityAvailability—the opportunity to interact with AI systems any time of day or night—is a key advantage. The “always on” aspects of such systems have clear business benefits, particularly when it comes to customer service. This technology enables organizations to have conversations with customers outside regular working hours. With that capability, the business can flex to meet user needs and preferences.

The Finnish government created Municipality Kate24—a government services chatbot to handle early-morning and late-evening requests. Kate can answer questions from citizens any other time, too.

AsynchronicityAnother advantage of machine communication is asynchronicity—in which a conversation is stretched over many days. Machines are much better at such conversations, as they can more consistently retain the context and state of the conversation. For example, Accenture has

Magnify the machine: How can we make the most of AI in the service of conversation?

02


ObjectivityMachines have an absence of emotion and moral judgment that provides a distinct advantage in some situations. In scenarios where the subject is sensitive, interactions with AI can afford a degree of anonymity that some customers welcome. This phenomenon is demonstrated by growth in chatbot therapists, such as Woebot26 and Youper.27

Youper is a AI-powered mental health assistant that helps people deal with depression and anxiety through conversation and by tracking moods and feelings.

This inherent lack of judgment also makes AI a good candidate for tasks like debt collection. Debtors may prefer interacting with bots for several reasons, including neutralization of tense situations. By using machines, we can offer a more empathetic approach than customers may experience with high-pressure calls from human agents. An example is ServisBOT’s Collectionsbot,28 which offers the business increased reach and engagement for higher collection rates. It can target hard-to-reach customers and offer a degree of privacy in the process.

Pattern recognitionRegulatory compliance and fraud detection are key concerns for financial institutions. Fraudulent activity, as well as fines for non-compliance, can cost corporations millions. Yet it can be difficult for humans to ensure compliance within complex systems and across high volumes of transactions.

This is where AI has an advantage: it can support regulatory compliance by detecting patterns and anomalies across vast swathsof data.

Eno—the AI-powered virtual assistant29 offered by consumer credit giant Capital One—provides a compelling example of AI as a fraud-fighting tool. Eno combines natural language processing and pattern recognition technologies to facilitate real-time communication with customers. When the system flags a potentially fraudulent transaction, Eno sends the customer an instantaneous query asking if they’re aware of it. Eno then analyzes the user’s responses, both to further personalize the exchange and to look for patterns of deception.


Time transcendenceAI has many practical benefits for customers and businesses alike. But there are other,more profound capabilities of AI, such astranscending space and time. Consider James Vlahos, who recorded his dying father’s life story—and then used it to recreate his dad as an AI.30

Although there’s been much focus on AIbeing fashioned as broadly “human like,” maybe that isn’t what AI wants. Rather, AI wants to be become more like us as individuals. It wants to become our digital doubles, mirroring us and performing tasks in our name. This is an important affordance as brands learn to interact with our “digital doubles.” AI can help build virtual homes for all the data that pertains to us, becoming the gatekeepers of our digital lives.

Conversation without wordsThe power of AI creates new possibilities for interactions that simply aren’t possible with human-human communication. Perhaps that interaction makes it possible to express yourself without using your voice or entering text. Alterego31 from the Massachusetts Institute of Technology is a non-invasive, wearable, peripheral neural interface. It allows humans to converse in natural language with machines, AI assistants and services, and other people without opening their mouth and without externally observable movements. They communicate simply by articulating words internally. Physiological response (that is, brain waves captured via ECG) is translated into text or visuals that enable conversation. In effect, this is AI as an extension of your mind, with machine-human interaction occurring as “silent communication.”


Embrace ethical AI: What are the potential pitfalls to be aware of?

03

As AI unlocks new capabilities, it brings challenges and tensions that organizations must navigate if they are to be deemed trustworthy. The use of some AI technologies can give rise to a variety of ethical concerns that must be understood and addressed by the business.

Data and privacyData is fundamental to more personalized, effective conversations with customers. But reliance on data must be balanced with the need for privacy. Organizations are undergreater pressure than ever to demonstrate their trustworthiness and ability to effectively manage privacy.

Gartner estimates that by 2021, 35% of the top 50 technology firms will face a consumer liability claim due to safety and privacy lapses in their digital products or services.32 Technical solutions, such as federated learning, are now emerging to enable privacy by design for conversational AI. This results in less exposure to privacy and data protection risks.33 Elsewhere, Sonos has acquired Snips, a voice AI platform which completes all data processing on device. This is seen by many as the antidote to security concerns related to voice assistants.34


Emotion and persuasionSophisticated AI technology provides some impressive affordances, such as being able to pick up on emotion through facial recognition, voice tone, text and other physiological metrics. Understanding acustomer’s context or mood is hugelybeneficial in determining the right way to engage. At the other extreme, however, is the potential for manipulation. Persuasive computing can change people’s attitudes or behaviors through persuasion and social influence, while practices like hypernudging leverage data to influence or ‘nudge’ people to certain decisions.35

MIT Media Lab spinoff Affectiva’s neural network, SoundNet, can classify anger from audio data in as little as 1.2 seconds.36

In applying sophisticated AI technology, we must be mindful of where we’re applying the technology, what we’re trying to infer, how we’re presenting information and the user feedback and choices we offer. These decisions will determine whether we are crossing ethical lines. Before making these choices, we need a clear policy. Companies like Affectiva have refused to work on projects that they feel violate their ethical principles.37

Anthropomorphism and stereotypesAnthropomorphism, which attributes human characteristics to technology, can be a useful tool in improving communication and building empathy and trust.

However, recent reports from the United Nations have highlighted how this can result in systems that perpetuate sexism and historical stereotypes, and respond in ways that encourage inappropriate user behaviors.38

In the past, the choice of a female-gendered assistant has been justified by specific academic research on consumer preferences. But now there is no consensus. Companies must determine the right combination of personality, tone of voice, and appearance to fit the specific context and brand identity. Technology players like Google and Amazon are taking steps to address gender bias in conversational design.39 Other technology advances are helping us respond to a lack of representation for certain genders and the nonbinary community. This includes the 2020 release of Sam, the world’s first non-binary voice solution for the digital assistant market.40


The path forwardA chatbot that interacts with millions of customers could have far more impact on their brand perception than a conversation with the company CEO. In other words, conversational AI powers “make-or-break” moments that should not be designed and implemented solely with a technological focus. Conversational AI demands a far more nuanced approach, including a multifaceted lens for identifying appropriate affordances, incorporating the human touch, and navigating a growing list of security, ethical and moral tensions.

Consider developing a five-step framework to guide Conversational AI development—from understanding the context of your conversations to identifying opportunities to use affordances to make them more effective for your customers and your business. Working through this framework is a solid first step in the journey to conversational AI that benefits your customers and your business.

Conversational AI Development Framework

FoundationEstablishing the core design,

data and AI foundation for successful customer

conversations and journeys. Our approach will help you navigate complexity by uncovering the human-centred affordances

technology can bring to conversations.

ImmersionUnderstand the complexity of existing customer conversationsin an organization, as they address different needs, span multiple channels and involve different people. This grounding is needed to inform future-state designs.

ScalingScale the conversations across the journey leveraging an Human+AI operational model.

DiscoveryIdeate how to improve conversations using conversational affordances and the tensions organizations should be aware of.

ExperimentationCustomer expectations and business demands are fluid: investment in agile experimentation capabilities is key for ongoing success.

DesignGiven the scale of customer conversations across the enterprise, it is critical to leverage a Human+AI operating model to design conversations at-scale

across needs, affordances and channels.

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“Business of Experience: The Future of CX.” Accenture. Retrieved from: https://www.accenture.com/us-en/insights/interactive/business-of-experience.

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Accenture C-level BX Survey; data collected from November 2019 to January 2020, with a refresh inMay-June 2020.

“Conversational AI Market by Component (Platform and Services), Type (IVA and Chatbots), Technology (ML and Deep Learning, NLP, and ASR), Application, Deployment Mode (Cloud and On-premises), Vertical, and Region - Global Forecast to 2025.” Markets and Markets, June 2020. Retrieved from: https://www.researchandmarkets.com/reports/5136158/conversational-ai-market-by-component-platform?utm_source=GNOM&utm_medium=PressRelease&utm_code=m3d7t3&utm_campaign=1426757+-+Global+Conversational+AI+Market+Analysis+2020-2025&utm_exec=joca220prd.

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“Accenture Develops Artificial Intelligence-Powered Solution to Help Improve How Visually Impaired People Live and Work.” Accenture, July 28, 2017. Retrieved from: https://newsroom.accenture.com/news/accenture-develops-artificial-intelligence-powered-solution-to-help-improve-how-visually-impaired-people-live-and-work.htm.

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https://www.forbes.com/sites/insights-ibmai/2020/06/25/how-ai-is-revamping-the-call-center/?sh=7fd671ee34b2

https://cdn2.hubspot.net/hubfs/3807088/Marketing%20Content/ServisBOT%20eBook%20-%20Transform%20Engagement%20with%20an%20Army%20of%20Bots.pdf?utm_campaign=General%20Thought%20Leaders%20hip&utm_source=Lead%20Flows&utm_medium=Website

https://www.forbes.com/sites/insights-teradata/2019/05/06/designing-ai-that-knows-how-you-feel/?sh=2f58863b446f

https://www.forbes.com/sites/insights-teradata/2019/05/06/designing-ai-that-knows-how-you-feel/?sh=2f58863b446f

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AuthorsGrace Hughes Conversation Design Lead, The Dock andAccenture Interactive

Sharad Sachdev Advanced Customer Engagement GlobalAI Lead, Accenture

Mark Curtis Head of Innovation and Thought Leadership, Accenture Interactive

John BolzeGlobal AI Growth Officer, Accenture

ContributorsPatrick Connolly Responsible AI Research Manager, Accenture

Robert Giusti Senior Design Researcher, The Dock, Accenture

Josephine Spence Advanced Customer Engagement Offering Development Lead, Accenture

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The future of customer conversations

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