CX leaders have a massive opportunity to impact digital business strategies by mastering AI

Customer Service leaders who think artificial intelligence (AI) stops at chatbots are cutting their careers very short. Too many people think that AI for customer service is limited to robotic chat screens and monotonic IVR scripts taking over from human customer service reps. However, with digital business strategies dominating the corporate agenda, the customer service function finds itself core to the success or failure of making these digital customer channels work, and emerging AI technologies are the crucial ingredient to digitizing the customer experience.

AI for customer service has far more sophisticated implementations than simply automating customer interactions. When implemented and designed well, AI in various elements of customer service has the capability to augment and assist an employee’s experience, supporting customer-centricity in back- through front-office processes. As a customer service executive, you need to get on the right track to this reality, as this is where customer service is heading. You won’t want to find yourself lost in a forgotten era, where voice-based call center agents being deployed from a variety of low-cost locations was the core requirement for customer engagement.

How can customer service leaders navigate the spectrum of AI to create digital customer experiences and tangible ROI?

HfS had the opportunity to sit down with several customer service executives at a recent event hosted by events company and thought leaders Execs in the Know. Participants’ AI adoption maturity spanned a vast breadth, with many just taking the first step toward understanding AI capabilities and others already piloting and adopting AI in their customer service organizations. It became clear that, regardless of maturity, company-wide alignment and attention to customer-centricity are ‘an absolute must’ to make any AI investment successful. Customer service leaders must start to take a bigger stand on their business function’s importance to overall corporate strategy; they must educate themselves on how AI can help customer service to deliver enhanced digital customer experiences.

Evaluating technologies can be daunting to customer service leaders, given the astounding speed of advancement, the issue of disparate sets of data, and legacy mindsets across the entire enterprise. In a recent survey of 100 C-suite executives, we found that while overall, three-quarters of respondents had developed a roadmap for cognitive investments (cognitive being a sub-set of AI), significantly fewer (56%) customer service respondents said that they had a clear roadmap for cognitive investments.

Exhibit 1: Customer service leaders have a less clear vision for AI investments than other business leaders 

Source: HfS Research 2018 study “Using cognitive tech to connect customers to business operations”;
sample size: 100 C-level customers

Why are customer service leaders falling behind with AI, and what can they do to catch up?

One of the impediments to creating a clear roadmap for investment is the lack of clarity about what the technology means in terms of service delivery, business cases, and required human governance. The question “What does AI mean?” was posed to the participants at Execs in the Know; there was a wide range of definitions and answers. A challenge for buyers navigating this landscape is the noise and confusion in the market, with so many buzzwords and marketing hype flying around. To help with this, we’ve put a stake in the ground with our HfS Triple-A Trifecta, to put a clear and concise definition around some of these change agents, such as AI (see Exhibit 2).

AI is many things: It is hyped, it is undefined, it is becoming pervasive, and it is fostering emotional, and at times heated, discussions. However, many of those discussions are more focused on more consumer-facing issues, such as self-driving cars, drones delivering Amazon purchases, or robotic home helpers. But the broader market is not yet recognizing the nearer-term impact of AI on B2B and enterprise operations.

Defining the AI problem… and the opportunity

We at HfS have defined AI as tech that aims to automate intelligent activities that humans associate with other human minds, through a combination of reasoning, knowledge, planning, learning, natural language processing (communication), and perception (a.k.a. cognitive—we refer to cognitive in the data in Exhibit 2, below, as the subset of AI which refers to perception).

Exhibit 2: The HfS Triple-A Trifecta

As a CIO in a recent interview put it: “AI is not a strategy. AI is a means to achieving your strategy.” Many of the participants at Execs in the Know felt that they’re viewing AI as a solution looking for a problem. One healthcare executive said they’re literally trying every technology out there right now, trying to find something that sticks—it’s an ineffective and more difficult way to experiment when you don’t know what you’re trying to accomplish. Reducing costs will always be a major part of the conversation, but there are many other objectives that decision-makers should look to achieve when investing in AI capabilities for customer service, including improved customer experience (CX), faster resolution times, and increased employee engagement.

Silos between customer service and core business functions impede your ability to plan strategically for AI

In a recent survey of 100 C-suite executives, we asked respondents to identify themselves on a scale of maturity of development toward being a more integrated, less siloed organization. Those in the top quartile of maturity are much more likely to rank improved customer experience as the top benefit (versus only 8% in the lowest quartile), while those in the lowest quartile are much less likely to have a clearly defined strategy for embracing cognitive technology.

This data, as shown in Exhibit 3, indicates that more mature, integrated organizations have a much clearer vision of what they need to do to achieve business transformation, a greater focus on customer experience, and more strategic attitudes about cognitive adoption. This signifies a major shift in priorities as organizations grow. Forward-looking organizations want to focus more on delivering high-quality customer experience and enhancing customer and employee support to create market differentiation, achieving competitive advantage.

This is good news for customer service leaders who are part of a more integrated organization, but it poses more challenges for those looking to move up the value chain within a siloed enterprise.

Exhibit 3: Less integrated companies focus less on AI for customer experience

Source: HfS study “Using cognitive tech to connect customers to business operations”; sample size: 100 C-level customers

Participants in the discussion at Execs in the Know were keen on many opportunities for AI to assist with customer experience-focused outcomes, including: ramping up content for customer-facing digital interfaces, creating consistency in answers to customer queries, offering more effective coaching and feedback, scaling customer service experience, and reducing customer effort. Many organizations are already using AI to impact these outcomes. For example:

• Case-in-Point: Machine Cognitive Virtual Agents identifying fraud within chat functions. We profiled an online gaming company, in our recent Cognitive technology for business outcomes report, which is piloting IPsoft’s virtual agent Amelia to augment human advisors in answering customer inquiries. This company deployed Amelia initially to vet out fraud within the chat functions, where scammers would try to “phish” customer information from chat agents. The Amelia tool was better able to identify these potential “phishers” than human agents, escalating these chats for additional authentication. While many would think that a human agent could better identify fraudulent chatter, the company’s Amelia pilot in chat found that the prescriptive flagging done by the cognitive agent was more efficient and effective. As this verification process previously accounted for a sizable portion of a conversation’s duration, Amelia has been able to reduce chat handling time while improving security through fraud prevention.

  Additionally (and referring to the change management and employee focus described earlier), this company was sensitive to their human advisors’ perceptions of how this approach would automate a part of their jobs. The company also found that, with the right level of transparency, human advisors were enthusiastically on board with the pilot. “When they realized she (Amelia) was there to protect account security and help them weed out fraudulent users, they started to trust the process,” said an IT executive from the company. It has been a win for both employees and customers and a boon for the efficiency and security of the organization.

• Case-in-Point: Machine Learning tools improving contact center performance management.
  We spoke to a contact center executive using AmplifAI, one of HfS’ Q1 Hot Vendors, to apply machine learning to its contact center data to identify and automatically distribute performance-specific “micro-learnings” to employees. The platform generates learning content that customer care agents, sales reps, or marketing reps can access within personalized dashboards and content libraries, in addition to real-time performance dashboards and tracking of performance management and social recognition functions. The tool can create efficiencies in the contact center with lower handle times and greater employee and customer satisfaction. In the sales environment, one executive described how the tool was particularly effective in improving the employees’
  ability to build rapport, overcome objections and transition to close, resulting in improved conversion rates.

The Digital OneOffice framework elevates the strategic importance of the customer-facing function

To take full advantage of what AI technologies have to offer, you must convince enterprise leaders to look at customer experience (CX) from a more holistic perspective. Contact center and customer service execs are used to being treated as the lowest priority, sometimes taking a back-seat to a sexier, revenue-generating project put forward by sales and marketing—but the issue often isn’t just executive buy-in, it’s also governance structure. Many CX leaders we spoke to felt as though their executives are sincerely supportive in theory, but that getting the resources and proving their worth can be a challenge. Companies need to view AI tech as an investment that can not only reduce costs but also improve experiences and create new revenue streams. The HfS Digital OneOffice, as defined in Exhibit 4, below, provides the conceptual framework within which such outcomes can be achieved.

The Digital OneOffice journey provides a huge opportunity for CX Leaders to impact their companies’ digital business strategies

The rapid move towards digital business models has placed the customer at the core of business strategy, and most Global 2000 enteprises today have a Chief Digital Officer driving that narrative.  The CX leader must forge a close alignment with the Chief Digital Officer to be part of this pivotal shift in the overall corporate strategy towards digital business. There has never been a better opportunity for CX leaders to reinvest their impact at the core of the business.

Digital is all about creating new revenue channels using interactive technologies, but it is only truly effective when the business’ operations can be truly integrated into these customer digital channels, in order to cater for customer needs in real-time.  AI technologies are huge enablers in supporting the seamless and autonomous flow of data between the customer-facing front office and the enabling “OneOffice” (what we used to term the middle and back offices supporting the business operation).

The Digital OneOffice (Exhibit 4), is where an integrated support operation has the digital capabilities to enable its organization to dynamically meet customer demand—as and when that demand occurs. OneOffice is realized when the needs and experiences of the customer are front and center to the entirety of business operations. The old barriers between customer and corporate operational functions are dissolved and the constraints of legacy ERP systems are minimized. This, in turn, allows the business to invest in digital technologies and capabilities that enable it to cater proactively to its customers’ need, at the forefront of the market. This provides for greater flexibility, enabling a rapid response if these needs change unexpectedly.

Exhibit 4: The Digital OneOffice conceptual framework

Starting with the ‘why’ will help you create more strategic AI initiatives for CX

The first step is absorbing information about AI technologies and what they mean to business operations. Here are some other guidelines to help customer service leaders navigate the confusing world of AI to bring value to their organizations and help customer service to ascend to a more strategic place in the enterprise.

• Identify the problem. As part of the exercise of identifying whether you have a problem to solve or an opportunity to exploit, it helps to do some soul searching about your organization’s core values. What is your company really in business to do? Then figure out how the customer service function supports that vision. You could start by conducting a survey of customer call center agents and managers to uncover pain points—look at the data behind those negative experiences and perceptions (e.g. time to resolution, etc.) to try to figure out why they are happening.
• If enterprise alignment isn’t there, take a grassroots approach to start collaboration and gain greater visibility for customer service. It’s easier said than done to change the culture within an organization to focus on collaboration more than competition. If it’s not being driven from a C-suite directive, often grassroots initiatives can help contact center execs to gain some visibility and traction with their desired resource investments. A senior manager at an online travel agent described spending a good amount of time planning the vision for customer experience investments and designing services for the following year, only to find out the same thing was being done in various other siloes within the organization. After putting out some feelers within the company, she was able to start an informal group for sharing best practices and ideas. This kind of affiliation might help siloed parts of the organization prevent re-inventing the wheel. The next step is to formalize this group, fostering internal co-creation and involving more people to generate interest.
• Put people and culture first. A focus on change management and creating a transparent, inclusive culture is of utmost importance when implementing AI for customer service. This includes personal change management for individual employees. As one interviewee put it, “You have to be good at two things: learning and change.” Individuals remaining open to change and being willing to learn are key to making AI successful within OneOffice. AI technology may replace human positions to an extent, but the overarching goal should be to make human work more meaningful (which, in turn, will lead to greater business success and employee satisfaction). Many customer service organizations will find that moving up from agent to SME is a sought-after career path that often involves training the AI tools that support customer service. Enterprises should also lean on their partners who have best practices and expertise for more successful implementations of AI.

Whether companies can pivot to put customer service in its rightful place as a strategic priority is largely up to executive leadership and governance—but customer service executives have a big role to play in making that shift. Customer service executives must have a clear and focused AI strategy and educate themselves and their peers about both the potential and the pitfalls that this technology presents.

The bottom line:

No one understands the customer better than CX leaders. This is your chance to become a major contributor to the corporate AI roadmap.

Today’s reality is that digital technologies have become core to business competitiveness by creating new revenue channels made possible by interactive communications with customers, by simplifying business operations to support the business with real-time data, and by supporting broader processes that respond to the needs of customers, as they occur.  AI is the glue that makes these digital customer channels work seamlessly and autonomously – and the customer service leader has a huge opportunity to provide genuine impact to their company performance by supporting this AI roadmap from the customer standpoint.