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How Artificial Intelligence (AI) can Transform Customer Experience for the Aviation Industry

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Introduction

Role of AI in enabling the transformation – Hexaware’s View Point Hexaware’s Omni Channel CX Platform - Integrated AI-cognitive solution Customer Experience & Contact Center Transformation solutions Key Use Cases for Airlines & Airports Industry Putting it all together – A Nutshell View

Research from Gartner: How to use AI to improve the Customer ExperienceAbout Hexaware

Introduction

The world has gone digital, and customer experience has been the major shifting force to drive this transformation. Businesses are now accelerating deployment of technology to deliver an integrated digital experience to their end customers. Customer experience is no more a nice-to-have but a must-have to survive in this digital age.

Smart devices, frictionless payments, voice recognition, virtual reality, augmented reality, bots and artificial intelligence are all redefining how consumers and travellers expect to engage with brands. Businesses today need to be on top of the digital game and proactively respond to the ever-changing consumer expectations to stay digitally relevant in today’s context.

The digital transformation of the customer experience revolves around several focal areas and objectives including:

• Facilitating frictionless interactions

• Enabling communications aligned with customer preferences— ensuring relevance, enabling ease of interactions using mobile apps, chatbots, natural voice recognition assistants and messages

• Personalization – subtle and overt

• Creating and reinforcing brand loyalty and positive sentiments

Role of AI in enabling the Transformation – Hexaware’s View Point

Targeted customer engagement and contextualized personalized experience is driven by uncovering insights from an organization’s enterprise data assets. Understanding and leveraging the intelligence is key to delivering relevant and tailored products and services to customers.

Hexaware’s AI-based Digital Solutions enable customers to develop long-term and productive relationships with their clients. Coupled with the domain experience across major industry verticals, personalized, proactive and predictive engagement will result in enhancing the customer’s business value and ROI. It will help the customers in introducing new business models, enhancing engagement with

How Artificial Intelligence (AI) can Transform Customer Experience for the Aviation Industry! is published by Hexaware. Editorial supplied by Hexaware is independent of Gartner analysis. All Gartner research is © 2018 by Gartner, Inc. All rights reserved. All Gartner materials are used with Gartner’s permission. The use or publication of Gartner research does not indicate Gartner’s endorsement of Hexaware’s products and/or strategies. Reproduction or distribution of this publication in any form without prior written permission is forbidden. The information contained herein has been obtained from sources believed to be reliable. Gartner disclaims all warranties as to the accuracy, completeness or adequacy of such information. Gartner shall have no liability for errors, omissions or inadequacies in the information contained herein or for interpretations thereof. The opinions expressed herein are subject to change without notice. Although Gartner research may include a discussion of related legal issues, Gartner does not provide legal advice or services and its research should not be construed or used as such. Gartner is a public company, and its shareholders may include firms and funds that have financial interests in entities covered in Gartner research. Gartner’s Board of Directors may include senior managers of these firms or funds. Gartner research is produced independently by its research organization without input or influence from these firms, funds or their managers. For further information on the independence and integrity of Gartner research, see “Guiding Principles on Independence and Objectivity” on its website.

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their customers and also in improving the brand loyalty and revenue experience.

Our Solution / Services Offerings

• Contact Center Automation

o Omnichannel CX Management

o Virtual Agents

o Virtual Assistants

• Chatbots & Conversational UI

o Secured

o Cognitive

• AI-Voice Assisted Business Apps

o Talking Apps

o Devices

• Legacy Contact Center Digital Modernization

o Cloud

o AI

• Voice of Customer Analytics

o Speech

o Text Analytics

CX Platform

Hexaware’s CX Platform, fully integrated with an AI-cognitive solution, comprises of Natural Language Processing (NLP), AI and Machine Learning (ML), process assessment and Robotic Process Automation (RPA) solutions that help in achieving the next level of customer experience without compromising on data privacy. The platform helps in empowering employees with contextual information and insights to serve the end customers better.

FIGURE 1Hexaware’s Omnichannel CX Platform – Integrated AI-Cognitive Solution

Source: Hexaware

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Hexaware’s Customer Experience Transformation Solution

Hexaware provides end-to-end customer experience transformation solution including strategic advisory, implementation and operations. Hexaware’s advisory practice assists customers to develop their transformation business case, build a roadmap towards customer

FIGURE 2Hexaware’s Customer Experience (CX) Transformation Solution

Source: Hexaware

experience excellence, and implement the requisite robotics, analytics and AI solutions to deliver omnichannel personalized customer experience.

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Hexaware’s solution to Digital Contact Centers

To continue acquiring new customers and retaining existing customers, the contact centers across businesses need to adapt to the expectations of new age customers fundamentally.

Following are the challenges that contact centers face:

• Evolving legacy service channels like telephone and chat into a complete experience with improvements in service and cost efficiency

• Providing customer service through channels of the customer’s choice and integrating it with the traditional channels of service.

Contact Centre Transformation Offering:

“Call Center Transformation” offering, leverages disruptive technologies and smart service agents to bring radical and far-reaching performance breakthroughs in the customer care industry across the dimensions of a) Customer Experience and (b) Cost of Service

Conversational interfaces leverage Automated Speech Recognition / Natural Language Processing technologies as cloud APIs. It helps in fetching and pre-loading the contexts from backend systems, supporting escalation to human agents with current context and conversation.

The Middleware delegates authentication/authorization, adds auditing/metering, supports human steps in the process flow, supports business processes and orchestrates API’s, hosted as backend microservices.

Hexaware, in partnership with the best-of-breed API platform providers, enables digital transformation by building and managing APIs with a three-layered API architecture (System API, Process API and Experience API) to enable maximum reusability and agility. Customers can accelerate their digital journey by leveraging the power of AI-and-ML-led digital experiences by integrating smart service agents, for delivering breakthrough customer service.

FIGURE 3Three-layered API architecture – Call Centre Transformation Solution

Source: Hexaware

Architecture

CONVERSATIONAL INTERFACES LAYER

PollyCONVERSATIONAL AI ENGINE

SECURITY

MIDDLEWARE LAYER

ENTERPRISE APPS

ERP CRM COTS LEGACY ITSM tools DATABASE CLOUD API

Lex

MESSAGING CHANNELS VOICE ASSISTANTS VOICE-ENABLED HANDHELD DEVICES

CALLCENTER APPLICATIONS

BACK-END SERVICES

WEBSERVICES RPA TECHNOLOGIES DB ADAPTERS CLI Event Stream

AWS CognitoAuth0

LUIS AzureAD

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Hexaware has developed digital accelerators to enable client’s customer experience:

• CxText: Unstructured data can be digitized using OCR/ICR, NLR and can be integrated with structured data through a matching workflow

• CxPredict: Historical transaction data can be used to make predictions using AI/ML models

• CxBots: Process automation using chatbots for Straight Through Processing and end-to-end flow. APIs are used to fetch live data

• CxCommunicator: Integrate internal systems with the self-learning chatbot to provide intuitive, dynamic and live data to resolve customer queries

In this paper, we have outlined four key use cases that leverage the AI capabilities and digital accelerators, as mentioned above, to deliver better customer experience across airlines and airports industry segment.

Use Case 1Enhanced Passenger Experience through Passenger Flow Monitoring & Analysis

Business Context

Effective capacity management and airport utilization require close monitoring and analysis of queues for security, check-in and immigration processes, etc. Capacity planning and work allocation are essential to delivering a seamless experience.

• Queue Management: Security, immigration and check-in processes at airports can get very stressful for passengers. Lengthy wait times add-up to the stress if the queues are not managed effectively and if processing throughput and capacity is not optimized

• Airport Layout and Capacity Planning: Airport layout and capacity planning is a challenging task that can directly impact passenger experience and reduce revenue from ancillary products and services

• Work-force allocation: With limited workforce available at airports, it is important to optimize the manpower, enhance productivity and maximize utilization

• Secured areas: Monitoring and alerts on the intrusion of passengers in secured areas

Hexaware’s Approach

Hexaware provides a mix of thermal imaging/video analytics solution in combination with its BIG LEAP analytics platform to address the above challenges:

• Determine the flow of passengers across the airports using the thermal, infrared and/or visual camera sensors for high-resolution video capture of passenger movements

• Calculate Performance Indicators like Waiting Times, Queue Lengths, Passenger Flow throughput, Area Occupancy, etc.

• Inform passengers about current wait times, alternate options, retail offers, etc.

• Forecast future passenger-flow based on historical passenger footprint data and flight scheduling data sourced from the airlines.

Hexaware AI Opportunity

Passenger numbers through international airports continue to rise every year which places increasing pressure on the capacity of the passenger screening. Travelers share vast amounts of data through apps, social networks, and websites. Additionally, mobile phones equipped with cameras are leading to the creation of limitless digital images and videos. The large volume of digital data can be used to deliver better and smarter services to the people accessing it.

Here are some of Hexaware’s AI solutions:

• Boost Passenger Handling Capacity with AI: Hexaware deploys AI for image processing to improve the airport’s ability to move passengers from arrival through security to their departure gate, thereby enhancing the productivity and throughput of operations.

• Smooth Passenger flow with AI: We expect that travellers will no longer need to produce identification documents at airports and touchpoints like security and immigration. Upon arriving at the airport, travellers can go to a face ID kiosk that captures their biometric information and matches that data with their passport details. The system then creates an electronic token. At subsequent clearance stages and image processing is again employed to verify identity against the token. The system integrates with the existing airport infrastructure such as self-check-in kiosks, baggage drop-points and boarding gates.

• Identify Suspects/Anti-Social People/Activities with AI: Image processing can also spot when someone is lying and could help weed out terrorists and drug smugglers at airports.

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Use Case 2Reduce Airline Contact Center cost by bringing in “Automation using Bots”.

Business Context

• Technology advances in social media and mobile have given travelers immense power to demand better customer service across their entire travel experience.

• More than 70% of the calls are related to enquiries, where customers wait on the phone to be connected to the next available customer service representative and are constantly being put on hold to retrieve information related to the customer query about flights, baggage, gate information, etc.

• Quality of service provided to the customer depends on the customer service representative and may vary from agent to agent. There is also an increased cost of customer service on the basis of per call rate or per minute rate.

• As a result, travelers prefer the immediacy of self-service and have been conditioned to expect quick responses and resolutions to their needs and concerns, making it more difficult for airlines to address each and every query with traditional tools and channels.


Hexaware has leveraged the following digital accelerators to enhance customer experience:

o CxPredict: Predictions are made by harnessing the existing historical and transaction data using AI/ML models.

o CxBots: Process automation using chatbots for straight through processing and self-service. APIs are used to fetch live data.

o CxCommunicator: This digital accelerator integrates internal systems with a self-learning chatbot, to provide intuitive, dynamic and live data for resolving customer queries and advise next steps.


• To make flying a more seamless experience and improve airline customer service, airlines seek new technology to market their services and products while enabling the most convenient modes of supporting the customers with their travel requests.

• AI plays a key role in enhancing the customer experience in call centers, by engaging chatbots- intelligent virtual assistant and natural language virtual assistants.

• By automating responses to basic passenger queries, chatbots decreases agent handling time by 10 per cent or more.

Scenario 1:

• Airline experienced a major computer outage causing cancelled flights and massive delays.

• There is an urgent need to re-accommodate passengers that need to be rebooked on another flight or to inform customers about any modifications to their travel.

AI Opportunity

• Customer Service: In this scenario, Airline can use an omnichannel AI platform that uses machine learning and AI-assisted analytics bots to handle incoming customer requests.

• A bot can free up agent’s time from handling these rebooking requests. The bot can be used to analyze flight data, check for possible flight options and notify customers about the outage to enable alternate travel options for them.

• Bots can help reduce the load on call centers, both in terms of deployment of human agents or the capacity of calling systems used to manage the incoming calls. Instead of picking up a phone, passengers might turn to the airline chatbot, knowing that a chatbot is always available and is able to provide immediate assistance.

Scenario 2:

• Book a ticket without the intervention of an airline agent.

AI Opportunity

• Booking & Upselling: In this scenario, Airline’s “AI” chatbot can enable passengers to book flights by incorporating their travel preferences.

• As the bot interaction is conversational, the interaction feels natural and personable. Additionally, the chatbot responds immediately to the customer’s needs, thereby offering an even better service experience than a traditional email or web form.

• AI chatbots can also gather information from frequent flyers, offer facilities or services that appeal to them. These natural language interactions ensure smooth booking as well as offer personalized products and services based on the airline’s understanding of the customer’s past travel history or preferences

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Use Case 3Connect with passengers using Social Media

Business Context

• Statistics indicate that one negative review on social media results in losing 10 or more prospective customers. While social media can be a great promotional tool, the magnifying effect of negative posts requires close management of reputation on social media. Customers on social media are obsessed about sharing their delight or complaints on social channels.

• The customer feedback that once shaped and helped improve airline’s marketing decision is slowly fading away as customers are utilizing social media, apps and web-interfaces to share their experiences.

• In today’s context, suggestions and complaint boxes are deemed useless. Instead, customers publicize their disappointment and resentment online – channelling their concerns within their network while seeking a resolution from the airlines. Across social channels, the customers expect the response to be immediate as against the traditional email support channels.


Hexaware created a single holistic view of the passenger profile using Customer Analytics. Our analytics helped in identifying:

• Customer’s past sentiments/experience, helping us address their concerns, thereby reducing customer churn

• The potential passenger, who have been using competitor airlines, and influenced them to opt for our Customer’s airline

• Key negative sentiments and use these insights to improve airline operations


• A thorough understanding of passengers helped in devising an enhanced and effective social media marketing strategy for airlines. Analyzing social media conversations offers the ability to recommend proactive suggestions and intelligent decisions based on actionable insights.

• AI is effective at analyzing large amounts of data due to its ability to absorb and analyze data to recognize patterns, predict hashtags and trending topics.

• AI allows you to ‘listen’ (audio and video feedbacks in multiple languages) to what is being said about the airline, the competitors and the industry in general. The data can be used to understand

the market better and improve the business strategy. You can also be alerted of any conversations about your airline or industry, and chime in at a relevant time. In real time, AI identifies when an unexpected drop in sentiment occurs for your airline and sends an immediate alert. Diagnostics are run to recognize the root cause and recommend the appropriate course of action.

• Selecting the right time and platform for posting content is a process that can be simplified by using AI via a social media monitoring tool. Tools that have AI features incorporated in them can analyze the data about the reach of posts to come up with an effective content posting strategy.

• Social media monitoring tools can help the airline identify opportunities for interacting with customers by analyzing mentions of the airline brand. AI features embedded within a social monitoring tool allows you to determine when and how to respond to customers. AI allows to automate the process of skimming through social media posts and makes sure that you do not miss out on the key opportunities to engage with customers. With intelligent social monitoring, you can leave the sorting of the posts to the tool. This enables marketers to focus on responding to the customers rather than spending time on organizing and managing social media posts.

Use Case 4Gain a 360° view of the passengers with Integrated CRM

Business Context

• Capture passenger experiences like seat preferences, meal choices or in-flight entertainment options across all touchpoints. Recommend and provide the customer with their preferred choice

• Harness passenger data to enhance customer experience, thereby increasing revenue per passenger for the airline


• Hexaware leverages the below digital accelerators to provide sophisticated passenger intelligence, analytics and reporting, using a modular and composable architecture, scalable API-led extensible application architectures with pluggable components.

o CxPredict: Predictions are made harnessing existing historical and transaction data using AI/ML models.

o CxCommunicator: This accelerator provides intuitive, dynamic and live data to resolve customer queries and advisories by integrating internal systems with self-learning chatbots.

o CxText: Unstructured data can be digitized using OCR/ICR, NLR and integrated with structured data through a matching workflow.

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• Customers desire a personalized travel experience. And, AI technology is helping to deliver this more quickly and effectively than ever before.

• As we move into an era of data explosion, it is becoming more pertinent to find ways to scan through huge amounts of data. AI recommendation engine helps in filtering and ensuring that the viewer gets to see the data that is relevant to his taste, style and preferences

• Using Analytics & Recommendation engine, a comprehensive view of the passenger can be accessed in real time, that can further be used to deliver a differentiated passenger experience and to realize opportunities towards driving ancillary revenues at every step of a passenger’s journey.

• Personalized services based on passenger profile: Traveler profile can be used to recommend services and products from different categories based on customer’s previous searches and bookings and offer products that the customer is likely to purchase. Airlines can understand the travel behaviour of the customer based on frequent flyer records to suggest cross-sell and upsell opportunities. The data can be used to recommend add on baggage services or meal offerings.

• Targeted offers to increase revenue: The Recommendation engine helps recommend destinations, advance booking options, pricing options and discounts depending upon the past travel behaviour.

• Improve Passenger Service and enable service recovery: Based on the customer choices, the engine can predict if the passenger has experienced a specific situation in the past and offer a solution that the customer is likely to accept. It can offer coupons or reimbursements as a resolution to issues and recover from service failures.

Putting it all together – A Nutshell View

Gartner has predicted that by 2020, 85% of customer interactions will be managed without a human. In this scenario, AI presents a tremendous opportunity to redefine customer experiences and end-to-end customer journeys that are more integrated and personalized, so that they feel more natural to customers.

The real challenge, however, lies in identifying where and how to start developing and aligning the right processes and data, building AI algorithmic models that can bring out the core benefits.

Over the years, Hexaware has been effectively leveraging AI to redesign customer journeys and customer experience transformation through digital channel activation, omnichannel environment, and integration of analytics. Hexaware is employing various digital accelerators to provide sophisticated passenger intelligence, analytics and reporting that can help deliver high-impact customer experiences rapidly and effectively.

Source: Hexaware

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Artificial intelligence will transform the customer experience through deeper understanding of customer behavior. Data and analytics leaders should engage with CX leaders to identify high-value use cases to drive innovation.

Key Challenges

• Customer experience is a high priority for analytics, with artificial intelligence (AI) the latest element of analytics to be applied to it. Many organizations struggle to identify the best use cases for AI pilots and to quantify the business value AI will bring.

• AI creates unique risks and intensifies others, especially in the area of new customer data privacy rules, bias on outcomes, algorithms and business rules behind decisions.

• Employees are worried about possible job loss and whether they can trust AI results.

Recommendations

To modernize analytics and business intelligence strategies for customer experience, data and analytics leaders should:

• Choose, as a starting point, customer experience use cases that have been proven to bring value to organizations, thereby ensuring access to high-quality customer data for the analysis.

• Reduce project risk by extending data privacy policies to address customers’ AI concerns.

• Position AI as a performance improver/decision augmenter by focusing on areas where AI can enhance employee performance rather than replace employees.

Strategic Planning Assumptions

By 2021, 15% of all customer service interactions will be completely handled by AI, an increase of 400% from 2017.

Starting in 2020, AI will be a positive net job creator — eliminating 1.8 million jobs while creating 2.3 million.

Introduction

The goal of improving the customer experience (CX) and thereby customer satisfaction, loyalty and advocacy is a leading candidate for investments in artificial intelligence (AI) for improved, personalized experiences that recognize customers, know them and then anticipate their needs. AI is a collection of technologies and techniques such as machine learning and deep learning that classify and predict — faster, more variously and in greater volume than humans without AI.

Through 2020, AI use cases supporting CX are forecast to deliver the most business value, followed by new revenue growth thereafter. Forward-looking data and analytics leaders already reap benefits from AI in a wide range of ways, the most prevalent of which will be:

1 Improved predictions — Increasing relevancy and personalization by analyzing high data volumes along with contextual data to provide recommendations and advice.

2 More accurate decisions — Improving decisions by processing large volumes of data faster, and by providing the most relevant actions at the right moment with retrained models that improve with each iteration.

3 Enhanced understanding through conversational interfaces and augmented analytics — Natural-language processing (NLP) with interfaces such as chatbots in call centers or personal digital assistants, by using text or voice to analyze language and communicate with users. A model is continuously improved by learning from conversations it has with people.

Many organizations have been augmenting their existing descriptive, transactional and behavioral customer data with contextual and situational data — such as Internet of

Things (IoT), geolocation, video, voice and social — and generating insights that they were not able to before. AI goes further. It can be used in many different ways to improve the customer experience by analyzing higher volumes of multiple types of customer data (see bulleted list below) to produce faster outcomes that improve with each iteration when retrained with new data:

• Descriptive — Customer demographics, purchases and interactions

• Contextual — From people (journeys, life events, searches, sentiment); from devices and things (location, sensors, mobile devices); and from organizations (weather, open data, third-party events)

• Attitudinal — Social, audio, video, preferences, options and attitudes

AI technologies have made it easier to spot the trends buried in data, with the ability to learn, enhancing technologies such NLP to analyze word choice that provides a deeper level of psychological insight. Understanding how the customer interprets issues and makes decisions can be very powerful in improving the customer experience (see Figure 1).

While its adoption is still early, the potential impact of AI can be transformational. Organizations must balance the hype about the promise of AI with the reality of optimizing and transforming their business to deliver real benefits.

Analysis

Identify and Map Top AI Use Cases to High-Priority Business OutcomesMany large organizations are already committing resources to improving CX by leveraging AI. According to the Gartner Research Circle 2017 AI Development Strategies Survey (see Note 1), the top three applications of AI are all about customer experience (see Figure 2).

Research from Gartner:

How to Use AI to Improve the Customer Experience

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Source: Gartner (April 2018)

FIGURE 1Customer Experience Data and Outcomes


FIGURE 2 Top Three AI Application Integrations for Customer Experience

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The same 2017 Gartner Research Circle survey found that just 6% of respondents had AI deployed or in use. However, 55% of respondents in Gartner’s 2017 CX Innovation Survey said they expected to use machine learning (which is one form of AI) for CX projects within the next three years (see Note 2).

One of the top three challenges to adopting AI is difficulty in identifying use cases, as indicated by one-third of the respondents to our Gartner Research Circle survey (see Figure 3).

To overcome the challenge of use-case selection, first focus on use cases that have already been proven by other organizations to deliver business value, starting with the most live production implementations.

Figure 4 shows the most common use cases for AI for CX, and the category of benefit that each delivers for CX. Source: Gartner (April 2018)

FIGURE 3The Top Three Challenges in the Use of AI


FIGURE 4Finding the Customer Experience Use Cases for AI

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FIGURE 3The Top Three Challenges in the Use of AI

This is not an exhaustive list of all potential CX use cases, rather, a list of use cases that show the most promise. Use this to select the first round of use cases that will deliver the most value to your organization. A selection of AI implementation examples follows Figure 4.

Implementation examples:

Conversational interfaces/chatbots — A European bank reduced inbound customer service calls by more than 50%, created more personalized experiences and reduced the time customers spent waiting for answers to questions. It deployed an NLP-based virtual customer assistant (VCA) that aligned online chat with the call center. The VCA assisted customers with information searches and basic transactions, such directing customers to appropriate links or forms, as well as providing call center agents with an answer engine to respond to customer questions more quickly.

Audience and customer segmentation — A transportation company doubled its sales volume during a campaign and increased sales leads significantly by leveraging AI to learn and adapt to changing conditions and high volumes of data such as weather and click rates. Analysis of outcomes and actions included identifying unknown audiences, proposing creative and messaging combinations and prioritizing the optimal channel for distribution.

Knowledge base for customer-facing workers — A local government reduced customer service response times by 50% and increased customer satisfaction by predictive case intelligence. Automated answers were generated by AI so that when an agent receives a new question, they are presented with an AI-suggested response to save time. The models were trained on historical logs using a deep learning algorithm.

Run Pilot Projects for the Top One or Two Cases

First, establish a cross-functional team consisting of CX domain leaders from marketing, sales, customer service, operations and IT, and your chief data officer (CDO) to identify the business opportunities.

Include business analysts who are close enough to the pulse of the business to find the opportunities and to demonstrate curiosity about the how the analysis can improve CX.

Second, develop a set of key performance indicators (KPIs) that align with corporate goals such as new revenue, cost optimization, and customer experience improvements that impact customer satisfaction, customer loyalty and advocacy. It is important that the AI initiative is treated as a business implementation and not a “shiny” new technology object with no business value attached to the outcome. Define the financial business outcomes aligned with metrics and identify the few most relevant CX metrics to measure and validate the business outcomes.

Third, identify opportunities for AI, based on the CX gaps in your organization. A useful method for finding the biggest opportunities for your organization is to undertake customer journey mapping in order to learn the areas of disconnect and dissatisfaction across high-value/high-volume customer journeys. Through linking together a series of customer interactions, you can understand what the customer was trying to achieve and ensure that your processes are designed to make that goal as easy to achieve as possible.

Particular elements to look at are repeated activities such as multiple calls to a service desk or revisiting the same page on a website, transitions from one channel to another, and customer cancellations.

Fourth, issues that especially lend themselves to the benefits and value that AI can deliver:

• Repetitive tasks that can be automated, such as data mining for trends, patterns and outliers in the data

• Tasks that consume high volumes of data, such as analyzing customer emails in a call center to determine relevant responses, or dynamic pricing based on multiple variables

• Opportunities to respond to the customer in a contextual manner in real time, such

as enticing a customer to purchase on a website based on an instantaneous personalized offer that knows the customer’s intent and predicts the best response

Fifth, prioritize use cases that address the business needs at your organization by using the following criteria:

• Proven use cases with delivered outcomes

• Business value of the outcome aligned with the organization’s business goals, with relevant success measures in place such as revenue increase, cost reduction, CX improvement

• Data is readily available for the use case

• Business leaders’ willingness to sponsor

Start with the least complex task where you have the most complete data. It may take several iterations of training data for the best result. The objective is to learn from the pilots in order to influence your longer-term roadmap.

Extend Data Privacy Policies to Address Customers’ AI ConcernsAI introduces or increases a range of risks to the CX and the business; two of which are particularly important.

• AI provides more granular insights into customers by uncovering patterns in data that are too complex for humans to uncover. The impending EU General Data Protection Regulation (GDPR) will require organizations to evaluate, justify and document why they are collecting and processing customer data.1 Initiatives such as the GDPR limit what organizations can do with data and analytics on personal information. Examples include how and when customers can be classified and profiled, and what actions can or cannot be taken by the organization based on that profile. AI capabilities are expressly intended to improve classification, prediction and actions based on those outcomes.

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• Clear, transparent and accessible information on how you process personal data will lead to improved CX in your organization.Take the opportunity to understand how customer data can drive value.

Confirm that bias does not lurk in your data and algorithms, to ensure fairness and protect your brand reputation; avoid discrimination in machine learning.2

Recommendations:

• Keep in eye on regulations such as the GDPR to make sure you are compliant, by:

• Putting in place a process to explain how the AI algorithm came to a decision. For example, what the algorithm was designed to do and the core rules it used to make a decision

• Checking for bias in the data the AI algorithm it is trained on by having checks and balances for when the bias appears; don’t assume that this will not happen

Position AI as a Performance Improver/Augmenter for Employees, not as a CompetitorNo drones or driverless vehicles for delivering packages — that’s one of the major 2018 demands from the U.S. Teamsters labor union in the big contract negotiation it’s undertaking with UPS.3 Employee concerns about job displacement must be addressed to build a high degree of trust between employee and machine.

While the reality is that a small percentage of jobs will eliminated, the majority of employees will eventually have some tasks in their job impacted by AI. It is important to provide guidelines for employee engagement, and guidance on the benefits to the employees, to minimize their concerns:

AI can augment analysis through analyzing volumes of data not humanly possible; it is rarely a complete replacement for human decision making. In the majority of cases, the benefit will come from optimizing human decisions and actions. Business benefits and examples include:

• More business value will be created through augmenting human decision making, rather than replacing humans.

An example is a sales manager who asks for an analysis of sales or the sales pipeline, who could be provided with an explanation or narrative of the statistically important drivers of change, complete with trends, patterns or outliers.

AI will not reduce the need for human touch in CX, as demonstrated by:

• Delivering relevant answers to customer-facing workers so they can provide a personalized service. Updating knowledge bases, if there are wider issues that need to be responded to, and warning customers of problems before they are even aware of them.

The key is to balance the human touch and technology in order to maximize efficiency while still providing a personalized service

Recommendations:

• Evangelize AI with your employees by focusing on the areas where AI can enhance employee performance rather replacing employees, in order to reduce suspicion and increase adoption.

• Provide them with examples of new knowledge bases and automated workflows and, by inclusion in pilots, demonstrate how they can do their jobs better and faster with the new insights from augmented analytics.

Acronym Key and Glossary Terms

AI artificial intelligence

NLP natural-language processing

VCA virtual customer assistant

Evidence

Based on Gartner primary research, analysis of hundreds of use cases provided through client inquiries and client interactions at Gartner data and analytics events, and from vendors.

1 The EU General Data Protection Regulation (GDPR); enforceable from 25 May 2018. Regulation (EU) 2016/679, is a regulation by which the European Parliament, the Council of the European Union and the European Commission intend to strengthen and unify data protection for all individuals within the European Union (EU). It also addresses the export of personal data outside the EU.

2 See “How to Prevent Discriminatory Outcomes in Machine Learning.” World Economic Forum. Practical guidelines on how to avoid discrimination in machine learning.

3 “Union Heavyweight Wants to Ban UPS From Using Drones or Driverless Vehicles.” CNBC.

Note 1. The 2017 Gartner AI Development Strategies Survey

The Gartner AI Development Strategies Survey was conducted via an online survey from 5 April to 21 April 2017 among Gartner Research Circle members — a Gartner-managed panel composed of IT and business leaders. Gartner Research Circle IT and IT-Business members were invited to participate. In total, 83 members completed the survey.

The survey was developed collaboratively by a team of Gartner analysts, and was reviewed, tested and administered by Gartner’s Primary Research team.

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The results of this study are representative of the respondent base and not necessarily of the market as a whole.

Note 2. The 2017 Gartner Customer Experience Innovation Study

The 2017 Gartner Customer Experience Innovation Study was conducted by online survey in February 2017. A total of 165 IT and


FIGURE 5Plans for Emerging Technologies for Customer Experience Projects

business leaders with responsibility for and knowledge of CX activities participated (see Figure 5). For the full report, see “Survey Analysis: Customer Experience Innovation 2017 — AI Now on the CX Map.”

Source: Gartner Research Note G00333850, Melissa Davis, 11 April 2018

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About Hexaware

Hexaware is the fastest growing next-generation provider of IT, BPO and consulting services. Our focus lies on taking a leadership position in helping our clients attain customer intimacy as their competitive advantage. Our digital offerings have helped our clients achieve operational excellence and customer delight. We are now on a journey of metamorphosing the experiences of our customer’s customers by leveraging our industry-leading delivery and execution model, built around the strategy — ‘Automate Everything, Cloudify Everything, Transform Customer Experiences.’ We serve customers in Banking, Financial Services, Capital Markets, Healthcare, Insurance, Manufacturing, Retail, Education, Telecom, Travel, Transportation and Logistics. We deliver highly evolved services in Rapid Application prototyping, development and deployment; Build, Migrate and Run cloud solutions; Automation-based Application support; Enterprise Solutions for digitizing the back-office; Customer Experience Transformation; Business Intelligence & Analytics; Digital Assurance (Testing); Infrastructure Management Services; and Business Process Services. Hexaware services customers in over two dozen languages, from every major time zone and every major regulatory zone. Our goal is to be the first IT services company in the world to have a 50% digital workforce.

Learn more about Hexaware at http://www.hexaware.com

About Travel & Transportation PracticeTravel and Transportation Practice is a focused and one of the key verticals for Hexaware. The practice provides digital & end-to-end IT solutions and services to leading companies in Airlines, Rail, Logistics and Hospitality domains. Catering to a huge base of large and mid-sized airlines & airports globally; the practice has 40+ elite and longstanding customers with over 1200 strong technical & functional consultants, industry experts.

Hexaware has been effectively leveraging AI to redesign customer journeys and customer experience transformation through digital channel activation, omnichannel environment, and integration of analytics for some of the leading clients in these sub-segments. We have our proven expertise in application transformation management (ATM), legacy modernization, advanced analytics, product engineering, digital assurance (testing), infrastructure management services, digital and business process services to deliver solutions for passenger travel, ticketing & reservations, cargo, revenue accounting, web-booking & e-Commerce, CRM & loyalty, crew management, MRO, baggage & airport operations. Being an IATA Strategic Partner, we are helping some key airlines to drive major initiatives around passenger experience, NDC & airline distribution.

For more details, please visit: https://hexaware.com/industries/travel-and-transportation/

http://www.hexaware.com

https://hexaware.com/industries/travel-and-transportation/

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