Point of View

Enterprise Leaders Must Look to Cognitive Assistant Services as a Critical Building Block for the Digital Enterprise

September 4, 2018

A new wave of services, powered by the change agents of smart analytics and artificial intelligence (AI), is on the horizon. One application has been to create cognitive assistants that can execute on business outcomes and impact enterprise operations; these cognitive assistants are part of the realm of services that are poised to help create more agile, predictive, and customer-centric organizations, as we have outlined in our HFS Digital OneOffice conceptual framework. It is critical for leaders across the enterprise to understand the capabilities and business cases for cognitive assistants and how they can be used as building blocks in the digital enterprise – these powerful tools have the capability increase sales, find new revenue streams, improve employee experience and many other business outcomes.  Business leaders in all areas of the enterprise should carefully examine and identify these opportunities and problems where cognitive assistants can have an impact.


Cognitive assistants are a crucial element of the digital business operations ecosystem


In our inaugural research for the HFS Top 10 Cognitive Assistant Providers, we explored the emerging market in the provider ecosystem for services that we call cognitive assistants—the intelligent, automated interactions that replace or augment human customer-facing transactions and processes or internal enterprise interactions and processes.


Today’s digital enterprises are not just looking for ways to become more efficient; they are also looking for ways to differentiate. It’s not just about the front office; when companies reorganized in the way we have outlined with OneOffice, they will often look within for ways to make operations internally more aligned with the customer. Cognitive assistant capabilities, whether deployed within middle and back office functions or directly with the customer, are using the power of AI and analytics to help companies transform and ultimately become more competitive.


These services incorporate capabilities that go well beyond traditional tools like chatbots and interactive voice response (IVR) to have a greater impact on business outcomes. There are many naming conventions including smart agents and virtual assistants—we think “cognitive assistant” is indicative of where the market is going. But, it is most important to understand what business problems these bots solve (rather than what they are called), the services they provide, and the opportunities they present. Cognitive assistants can combine characteristics of conversational and voice-focused services, but ultimately they are more sophisticated virtual assistants with the ability to learn and the potential to substitute for human-agent interaction. Exhibit 1 outlines some of the common characteristics of cognitive assistant services.


Exhibit 1: Characteristics of Cognitive Assistant Services



Source: HFS Research, 2018


Cognitive assistants are part of the evolution in the continuum of service agent automation and intelligence (see Exhibit 2). “Dumb bots” become more intelligent ones as they gain experience; these more sophisticated cognitive assistants are poised to significantly impact business operations. Most people are familiar with more consumer-focused conversational assistants like Alexa and Siri or traditional chatbots that provide automated conversations using rules-based programming. Enterprise-level cognitive assistants, while still nascent, have learning and processing capabilities that transcend those basic conversational tools. At the more sophisticated end of the spectrum, cognitive assistants will have the abilities to self-learn, self-remediate, and execute on business processes. They are also often able to understand structured and unstructured data and to use natural language processing to learn, comprehend, and recommend next steps. Advanced cognitive assistants may also enable predictive decision making using real-time analytics. They can be used externally to communicate with customers in customer service inquiries and internally to augment customer service staff with knowledge management, to support the IT help desk, or to assist with HR or finance processes (such as employee onboarding).


Exhibit 2: Cognitive assistants are on the spectrum of service agents



Source: HFS Research, 2018


Cognitive assistants have higher applicability to both business and IT processes than do other elements of AI and analytics (see Exhibit 3). As detailed in our HFS Blueprint Report: Enterprise Artificial Intelligence (AI) Services 2018, RPA and chatbots are low level; data science projects, autonomics, and cognitive assistants are more complex and require significant investments. For many buyers, all those chatbot proofs of concept are a risk-free toe-dip into the sea of AI with the hope to learn some valuable lessons. AI is not a linear progression, neither from RPA nor chatbots nor any other starting points; with new entrants coming from all directions into this space, there are both ample opportunities and disruptive threats.


Exhibit 3: Cognitive assistants have high business and IT applicability, high investment requirements



Source: HFS Enterprise AI Blueprint, 2018


Cognitive assistants are being adopted rapidly


Interest in and adoption of cognitive assistants is growing rapidly. As shown in Exhibit 4, while 37% of enterprises are currently using chatbots for customer interactions, more (63%) are in the evaluation stage of more sophisticated cognitive assistants. We believe this is due to cognitive assistants’ greater capability to impact business outcomes. While chatbots can work in a well-designed self-help scenario functioning as a glorified FAQ or something similar, when poorly implemented they can be an obstacle and point of frustration for customers—the new digital version of “IVR jail.” A more sophisticated conversational service can offer the capability to apply advanced digital technologies for contact avoidance, experience enhancement, and efficiency improvement.


Exhibit 4: Enterprise adoption of cognitive assistants



Source: HFS Research, 2017, x=154 enterprise decision makers


Thus, the evolution of cognitive assistants is not simply about cost reduction or call deflection. Enterprises are often investing in cognitive solutions as a point of competitive differentiation. Cognitive assistants have been shown to deliver improved security, better customer and employee experience, and greater visibility over business processes. The most notable benefits C-Suites have realized through their cognitive technology investments have been improved data security and simplified business processes. In the front office or call center, many cognitive assistants are used as helpers to live agents, helping them to find information for customers quickly or to recommend personalized offers. When used within internal enterprise processes such as HR, cognitive assistants have shown the ability to speed up onboarding processes and reduce security concerns and errors.


Cognitive assistants are having real impact in today’s enterprises


Our recent research explored the market for service providers that help their customers design, develop, implement, and operate cognitive assistants; we found that cognitive assistants have applicability across many industries and use cases. For example, travel agents are using cognitive assistants in combination to analyze travel information and natural language understanding and processing to provide intelligent travel choices for customers. This enables agents to focus their energy on the more unique nuances of travel planning and, as a result, customers experience personalized and efficient booking. Similarly, a gaming company uses cognitive assistants to help weed out would-be “phishers” who prey on live representatives and try to trick them into leaking customer data. A cognitive assistant could become a knowledge partner in the healthcare industry; physicians, nurses, researchers, and others can locate, present, and apply the most current clinical knowledge for improved clinician efficiency and capacity and quality care. In financial services, cognitive assistants have the potential help banks to address risk and fraud management more effectively.


Exhibit 5 lists a few compelling examples of cognitive assistant usage from service providers and their customers; they showcase the breadth of use cases and outcomes possible.


Exhibit 5: Examples of cognitive assistants in production



How to approach cognitive assistant services


  • Leverage service provider expertise. Developing these problem and opportunity cases and implementing and operating this kind of conversational automation is where the demand for service provider expertise comes in. Enterprise business leaders are faced with the task of digital transformation but are struggling to get beyond the challenges of hype, a lack of digital mindsets, and the need to figure out the right problems and opportunities for applying these technologies. They often lack both the internal talent and the vision to understand what they want to use the technology to accomplish and what new metrics to use. As the head of AI strategy for a European bank lamented, “I’ve struggled with seeing this (cognitive assistants) as a pure cost savings effort. It’s much more about the customer experience, but how do you measure that?”
  • Focus on augmentation rather than replacement. Automation tools can often replace a human interaction—we see this a lot in self-service, especially in the case of straightforward, focused inquiries. Tools can typically free the employee to do something less transactional, more valuable to the customer, and more “human.” However, with cognitive assistants, the capabilities are more powerful and therefore more nuanced. Generally, the successful use cases we’ve seen are about making live agents more efficient and effective; often that means that the bot is working side-by-side with the employee as a kind of assistant, synthesizing and presenting data, aimed at making their lives easier and processes more intelligent and agile.
  • The success of cognitive agents is more about culture than technology. An unwillingness to change and let go of past investments is often what is holding back businesses from experimenting with or successfully implementing cognitive agents. When investing in cognitive solutions, some of the primary issues to be addressed are change management, cultural re-alignment, and a shift in talent requirements. Those who have successfully implemented cognitive agents spoke of the need for transparency and being clear about the anticipated business outcomes. Business leaders need to be focused on employee impact and demonstrate how cognitive agents can enhance their jobs, not diminish or eliminate them. It is necessary to place employees, as much as customers, at the center of any digital business transformation, to ensure that culture, values, talent, and business process expertise are not lost amid the changes.


Bottom line: Cognitive assistant technology is here—now enterprises must apply it to the right business problems and opportunities.

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