Infusing AI into customer care, resiliency planning and IT operations

2Infusing AI into customer care, resiliency planning and IT operations

Table of contents

How AI can help augment workflows and increase efficiencies

Create better customer experiences with AI for customer care

Increase resiliency with AI for financial planning and forecasting

Modernize and find efficiencies with AI for IT operations

Get started and optimize with AI

Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

3Infusing AI into customer care, resiliency planning and IT operations

Companies are looking to artificial intelligence (AI) to support their decision making and transform how they work. AI can be used to automate processes, provide deeper insights through data analysis, and engage with customers and employees in new ways. This means AI can have meaningful impact across industries and departments such as customer care, IT operations, and financial planning and forecasting. But integrating AI into existing systems and workflows can be daunting for companies, as many do not want to dismantle or radically overhaul existing systems. Fortunately, AI adoption is not a zero-sum game. AI can be used to work with and augment the current workflows to optimize speed, reduce costs and produce better outcomes.

How AI can help augment workflowsand increase efficiencies

Chapter 1

So how can you best incorporate AI into existing platforms and processes? First, you need to decide if you want to use pre-built AI applications or build your own custom solutions. AI solutions built from the ground up can meet the very specific needs of different data or decision-making processes. While pre-built applications provide their own advantages, as they tend to be more proven and require less development time–all of which could help you implement AI faster and at a lower overall cost.

However, even though AI can create efficiencies, there can still be integration obstacles. To make smarter decisions, many companies find value in a unified system that can connect the client-facing and backend systems together.3 Data can be key to helping unlock these workforce trends and help find additional value for your unified system. And AI can help collect and analyze all the available data so that you can make better decisions about your workforces and processes. To strategically incorporate AI into your existing workflows, you need to do three things:

47% of executives say that it’s hard to integrate cognitive projects with existing processes and systems.1 47%

The impact of AI technologies on business will boost labor pro-ductivity by up to 40%.2 40%

4Infusing AI into customer care, resiliency planning and IT operations

To strategically incorporate AI into your existing workflows, you need to do three things:

IdentifyFirst identify the areas you would like to improve or the problems you would like AI to solve. Where are the areas of your business where AI and data analysis could provide demonstrable value?

AcknowledgeNext, acknowledge what your internal capabilities are. There may be a difference between what you would like to accomplish versus what you can implement within a certain timeframe. But knowing what you’re capable of from a tech and process point of view is critical before beginning an AI implementation.

CreateOnce you understand your capabilities and goals, create a pilot project that lets you see how AI can be integrated. A pilot project also provides your team with a “what’s under the hood” view, allowing them to deepen their understanding of how AI will augment and optimize their own workstreams and capabilities.4

1 Artificial Intelligence for the Real World, Harvard Business Review, February 2018.

2 Artificial Intelligence Poised to Double Annual Economic Growth Rate in 12 Developed Economies and Boost Labor Productivity by up to 40 Percent by 2035, Accenture, September 2016.

3 5 Ways Artificial Intelligence Can Boost Productivity, Industry Week, May 2018.

4 10 Steps to Adopting Artificial Intelligence in Your Business, PCMag, November 2018.

When the right AI systems are in place, businesses can experience increased employee output in addition to better and faster decision making.

5Infusing AI into customer care, resiliency planning and IT operations

Create better customer experiences with AI for customer care

Chapter 2

As data and technology have become more prevalent in our daily lives, the relationships between companies and customers have only deepened. The “data era” of the 2000s was when data on all customer interactions first began to explode, thanks to developments such as smartphones and online shopping. Then the “omnichannel era” of the 2010s began, which created a consistent and singular experience for a customer—no matter how or where they engaged with a brand. Now we are entering the next phase, the critical “relationship era.” Brands and businesses now have the insights and data to engage with their customers and build a genuine, strong relationship. AI is key to building these stronger relationships and ensuring personalized customer experiences can be built and evolve over time.

When it comes to customer care, companies that are successfully leveraging AI focus on three crucial areas:

Knowing the customerAI can help provide a more comprehensive 360-degree view of customers and their behavior by incorporating and analyzing large volumes of internal and external data sources that would not be feasible to add manually. Natural language processing (NLP) also makes customer feedback and other unstructured data more useable, helping create a consistent and thoughtful relationship with customers across channels.

Interacting with the customerWith first-interaction resolution, customer issues can be solved with urgency. Unlike chatbots, virtual agents fueled by conversational AI can do more than just repurpose and relay basic information through a chat interaction. When equipped with AI-powered search capabilities, conversational AI can remember who customers are, address their needs and transform an encounter entirely.

Predicting and personalizing for the customerOnce this 360-degree view of a customer’s world has been established, AI can help deepen that relationship further by starting to predict and anticipate the customer’s future needs. For example, products can be recommended based on previous purchase history, or personalized support can be provided based on previous queries that needed resolution.1

6Infusing AI into customer care, resiliency planning and IT operations

Customers now demand improved experiences, and the organizations that take advantage of the latest technology are excelling in providing that service. With that, AI solutions such as chatbots have skyrocketed in popularity over the last decade, and customers are now more familiar with them and comfortable using them.

But customer care teams need more than just simple chatbots. They need to give customers quicker ways to find information and resolve their issues. They also need a solution that provides more than just basic answers to simplistic questions. This is where conversational AI comes into play. It uses machine learning and natural language processing to elevate the overall customer experience.

— Assistive Virtual agents can now do more than just answer questions. They can make purchases, schedule events, reroute shipments, and more.

— Conversational

Advanced conversational AI speaks in natural human language and in a human-friendly interface and continuously refines its understanding models.

— Omnichannel It can live across multiple channels, such as websites and apps, external channels such as third-party messaging apps, all for a single point of assistance.

— Persistent It remembers all your previous interactions and draws insights from your previous behaviors.

— Smarter search It can use the most advanced search techniques to surface the most relevant information from your organization’s databases.2

59% of customers say they have higher expectations for customer support than they did a year ago.2 59%

How can robust conversational AI equipped with AI-powered search improve customer experiences? Advanced analytics can help leadership improve call centers in multiple ways:

7Infusing AI into customer care, resiliency planning and IT operations

1 Customer Care: Dynamic and Trustworthy Experiences to Build Strong Relationships With Your Customers, IBM, August 2021. 2 AI for Customer Service, IBM, August 2021.

Learn how Humana, a leading health insurance provider, improved the provider experience with conversational AI

Case study

Learn how IBM Watson Assistant can cut costs, drive revenue, and free up employees and resources for higher value work

Forrester TEI report

Learn how Watson Discovery can reduce costs by finding specific answers and trends from documents and websites using AI-powered search

Forrester TEI reportCase study

Learn how Humana, a leading health insurance provider, improved the provider and customer experience with conversational AI.

Forrester TEI report

Learn how Watson Assistant can cut costs, drive revenue, and free up employees and resources for higher value work.

Forrester TEI report

Learn how Watson Discovery can reduce costs by using AI-powered search to find specific answers and trends from documents and websites.

When agent notes are combined with data mined from calls, emails, and chat logs, customer behavior patterns can be identified and a clearer picture can be developed to show how a contact center is performing. Analytics tools can help reveal patterns in the data collected to then inform strategies for improving processes related to compliance, agent performance, customer sentiment, and even sales effectiveness. IBM Watson Assistant conversational AI and an AI powered search, Watson Discovery, can both drive transformation on their own. But together they have the potential to drive even stronger results.

8Infusing AI into customer care, resiliency planning and IT operations

Increase resiliency with AI for financial planning and forecasting

Chapter 3

Financial and operational planning is one of the business areas that has quickly embraced the use of AI. Operational disruptions, regulatory shifts, market changes, and evolving customer demands all create uncertainty and expose vulnerabilities within a business. Even the slightest market shift can have major impacts and can often result in increased costs or lost revenue.

However, traditional planning tools can’t keep up with the demands and speed of today’s market, with time wasted coordinating spreadsheets, dealing with replicated data, and manually aggregating inputs across business units. Organizations that are integrated in their approach to planning—linking financial and operational plans with their strategic goals—are more prepared to adapt and respond to disruptions as they occur. These enterprises can monitor performance metrics and adjust their business models to proactively address market changes, instead of reacting after a disruption has occurred.

The speed required to generate actionable insights and inform decision-making is constantly increasing. As a result, the window for businesses to make decisions is getting smaller. If businesses want to be resilient, they need financial planning and operational planning that involves more complex decisions, more decision makers, and more data.

So, how can businesses address planning needs for today and the future? To thrive during disruption and achieve goals with confidence, planning needs to reflect, connect to, and evolve with your business. This means that planning processes need to be continuous, integrated, prescriptive, and predictive. The traditional planning practice of using historical data is just the starting point; for many operational teams, historical data alone is not enough. To plan and respond with more certainty, businesses need to incorporate external data into their planning processes.

58% of midsize and large companies still use spreadsheets to manage their planning and budgeting processes.1 58%

41% of Microsoft Excel users say spreadsheets can’t handle their data volumes.1 41%

9Infusing AI into customer care, resiliency planning and IT operations

For example, when external data, such as employment trends and weather data, is combined with client data, it can lead to deeper insights into what is driving demand—resulting in a more accurate demand forecast.

A holistic approach to planning using an AI-powered integrated planning solution allows demand, inventory and production plans to automatically update revenue and expense plans, providing finance teams and business leaders a more accurate view of the organization’s performance and financial health.

Predictive analytics and scenario planning are necessary for organizations to make critical business decisions. AI-powered predictive forecasting uses statistical and predictive analytics to identify trends and detect seasonality patterns and outliers, leading to more accurate, consistent, timely and granular forecasts that help you see exactly where you’re going. Scenario planning allows organizations to test assumptions and model multiple scenarios to see the impact of decisions before making them. The combination of predictive analytics and scenario planning allows organizations to best anticipate what’s going to happen and identify new growth opportunities.

Successful planning strategies have certain elements in common. For a strategy to be effective it needs to reflect, connect, and evolve with the business.

Successful strategies need to be:

ContinuousPlan at the speed of your business to adjust planning cadence and respond to markets faster.

IntegratedConnect planning processes across your organization to create betterbusiness unit alignment.

PredictiveIncrease your plan accuracy, speed and consistency with AI capabilities and automation.

10Infusing AI into customer care, resiliency planning and IT operations

1 Spreadsheets are Holding You Back, IBM, August 2020.

PrescriptiveUse AI-driven decision optimization to increase your planning and forecasting confidence.

ScalableDeliver momentum at scale with confidence to fit your growing planning and data needs.

With IBM Planning Analytics with Watson, you can integrate, streamline, and scale planning processes across every part of your organization including finance, sales, supply chain, operations, HR, IT, and marketing. This allows you to have foresight into future performance throughout your business.

Case study

Ancestry unlocks real-time financial insights with analytics guru, Jose Balitactac.

Constellation Research Report

Learn how modern planning platforms combine scenario planning and predictive features to drive business agility and better outcomes.

Forrester TEI Report

Learn how IBM Planning Analytics reduces the labor time of annual budgeting by 63% and processes planning data up to 80% faster for clients.

11Infusing AI into customer care, resiliency planning and IT operations

Modern IT is becoming more and more complex. Organizations are moving to cloud, operating in hybrid environments, and the amount of data being generated is increasing at a rapid place. With all this data now available to leverage, a growing number of departments and teams want to access and use it to generate better insights and be more analytics-driven. However, if your IT teams are monitoring workflows, resources, and processes manually, they are going to create bottlenecks that impede the business or miss critical data that could be leveraged to make smarter decisions.

36% of executives say the primary goals of AI implementation are to optimize internal operations and free up workers.1

AIOps can help navigate the new complex IT landscape by providing visibility into performance data across all environments, analyzing data to identify problems, root causes, and recommended solutions, and automatically generating alerts for IT staff. AIOps brings additional value to IT operations by relieving the burden of manual processes.

When AI tools are leveraged, teams can do more than just keep the lights on. When AIOps helps to find efficiencies, IT teams are given time back to develop additional tools that can bring revenue back into your company, ultimately translating to a positive, direct impact for the CIO. Furthermore, the application of AI, ML, and automation of IT-dependent use cases helps deliver outcomes to organizations, including lower customer attrition, greater yield on IT spend, and healthier growth in an increasingly digital-first world.

Modernize and find efficiencies with AI for IT operations

Chapter 4

AIOps provides three major benefits to your business:

1. ObservabilityBy cutting through the IT operations noise and pulling data from multiple IT environments, AIOps can identify what’s causing a problem and propose solutions faster and more accurately than humanly possible. This helps businesses set previously unachievable MTTR (mean time to recovery) goals.

2. Application resource managementInstead of receiving every alert from every IT environment, AIOps teams can choose to only receive alerts that meet specific parameters—complete with all the context needed to make the best possible diagnosis and create the fastest solution. The more AIOps learns and automates, the more it helps keep processes running with less human effort.2

3. Predictive ITBecause AIOps never stops learning, it keeps improving at identifying less-urgent alerts or signals that correlate with more-urgent situations. This means predictive alerts can let your teams know of potential problems before they cause slowdowns.

12Infusing AI into customer care, resiliency planning and IT operations

Successful AIOps tools either operate on a platform model where they have an operational platform that does everything, or they add on tools that enhance what they already have in place. But whether you use a full platform or integrate specific tools, AIOps can help you get a full picture of your IT systems and give you an accurate assessment of what’s happening, what’s going well, and where improvements could be made.

For businesses looking to get the benefits of AIOps, including automation to drive resource and stability benefits, IBM can help. You can reduce the complexity and number of operation tools you’re managing and integrate with strategic tools, all through IBM’s assembled platforms—such as IBM Cloud Pak® for Watson AIOps—that give you added flexibility.

1 131 Myth-Busting Statistics on Artificial Intelligence (AI) in 2021, AI Multiple, August 2021.

2 AI Ops, IBM, April 2020.

Learn how IBM Watson and lessons from the Masters Golf Tournament can help businesses create new value.

Case study

Learn about what market trends are driving the increased adoption of AIOps platforms and recommendations when choosing a solution.

Gartner AIOps Market Guide

Learn how CIOs and their teams are shifting to the site reliability engineering (SRE) operating model, using AI to ensure IT resiliency and robustness.

AIOps Use CaseCase study

Learn how IBM Watson and lessons from the Masters Golf Tournament can help businesses create new value.

Gartner AIOps Market Guide

Learn about what market trends are driving the increased adoption of AIOps platforms and recommendations when choosing a solution.

AIOps Use Case

Learn how CIOs and their teams are shifting to the site reliability engineering (SRE) operating model, using AI to ensure IT resiliency and robustness.

13Infusing AI into customer care, resiliency planning and IT operations

Infusing AI into your applications and workflows can help you make more accurate predictions, automate decisions and processes, and optimize your organization’s time and resources. No matter what business unit or department you are looking to transform, an AI-powered solution can help you excel.

Have questions? Ready to start integrating AI into your business? Schedule a free one-on-one consultation with an IBM AI expert.

Take the next step

Resources and solutions

Get started and optimize with AI

Chapter 5

Learn more about how AI can transform your existing workflows and processes with these additional resources and solutions.

Customer Care

• Watson Assistant can help create the best customer experiences by using AI and natural language processing to remove the frustration of long wait times and unhelpful chatbots. It can also learn from customer conversations to improve and resolve issues the first time.

• Watson Discovery is an AI-powered search and analytics solution that eliminates data silos and retrieves information buried deep inside your enterprise data. It uses market-leading natural language processes to find meaningful insights from sources throughout your organization.

• GBS Cognitive Care services from IBM can help drive smarter workflows and evolve technologies across your entire organization. Industry experts can help you implement a data-driven strategy to operationalize and accelerate AI integration throughout your enterprise.

Forecasting and resilience

• Planning Analytics with Watson is an AI-infused, integrated planning solution that allows you to move beyond the limits of manual planning. It breaks down business silos so you can quickly create more accurate plans and forecasts—all in one platform.

Talk to an expert

• OpenPages® with Watson is a highly scalable governance, risk and compliance solution that is driven by AI. It can help centralize risk management functions within a single environment so you can more easily manage, monitor, and report on risk and compliance.

• Cognos® Analytics can help clean and connect your data and create visualizations that show you where your business is today, while helping you predict what will happen tomorrow. With Cognos Analytics, you can get insights at a glance and in real time.

14Infusing AI into customer care, resiliency planning and IT operations

IT Operations

• IBM Observability by Instana® provides your business with enterprise observability, which helps you to manage the performance of complex applications and software no matter where they live.

• Turbonomic for IBM Cloud Paks continuously analyses applications’ resource needs. It fully automates actions that ensure applications get what they need to perform, while still adhering to your business policies.

• IBM Cloud Pak for Watson AIOps can deliver visibility into performance data and dependencies across multiple environments to help you innovate faster, reduce operational costs, and transform your IT operations. Automated capabilities can alert staff to problems, identify their causes, and recommend solutions.

15Infusing AI into customer care, resiliency planning and IT operations

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