Artificial Intelligence in the corporate worldWhite paper

2020

AI White Paper

01. EditorialIn 2020, artificial intelligence will no longer be a vision of the future, but a tangible reality: language agents such as Siri, Cortana or Alexa are already pervading our everyday lives. The smart assistants play our favorite music, make restaurant suggestions, recommend films, identify the fastest route to our destination and steer our car better into the parking lot than we could. We use artificially intelligent systems that are becoming more and more a matter of course both at home and at work. AI systems have slipped into our everyday lives and they are here to stay.

What is AI – and what it’s not

However, there are so many keywords and misunderstandings related to artificial intelligence that it is important to consider some basic facts: AI is not about a particular physical form factor, nor is it about a particular underlying code base or technology. AI includes all systems that generate intelligent behavior and strive to imitate human intelligence or, perhaps, even surpass it one day. As a generic term, AI can involve neural networks, deep learning, natural language processing and machine learning, in which systems are able to “learn” by themselves. Examples of machine learning are the ever-improving algorithms underlying predictive analysis and recommendation engines.

AI Predictions

By 2021, most major companies around the globe will have left their planning stages behind and enriched their customer experiences with AI. For consumers, this means that many of their interaction with service providers such as banks and insurance companies will be through intelligent AI-based agents, not people. In the workplace, we will see the smart helpers take on more and more routine tasks – for example in service or quality control – and relieve colleagues. Contrary to many fears, the world of AI will also create new tasks for people: In systems training and control, but above all by creatively cooperating with their new AI colleagues.

The White paper

With this white paper we shed light on the current status of AI use by companies in Germany, Austria and Switzerland: 500 specialists and managers who decide on digital transformation in the DACH-region were surveyed on strategy, opportunities and risks.

Our AI experts report on successful projects from the field. Feel free to ask us for specific results for your own business environment. We look forward to sharing our insights with you - as well as your comments or critical points.

Yours sincerely

Dr. Bruno Messmer, DXC Technology Head of Digital Strategy & Transformation Consulting, North and Central Europe

Table of contents

01. Editorial 2

02. What business thinks about AI 3

03. Where companies invest 4

04. AI tests the use of medication on patients 5

05. Who are the implementers? 6

06. Infographic: Investments in AI 8

07. Collaborating with AI in the corporate world 8

08. The evolution of AI in the corporate world 9

09. Forecast: Intelligent journey into a new world 11

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02. What business thinks about AIThe companies surveyed by DXC see great potential in smart systems. The majority even assume that AI technology will radically change the entire economic model, and thus the world we live in. One out of every five decision-makers is strongly convinced of this development - almost one out of every three believes that the forecast is highly probable, and another third tends to agree with this trend - a total of 81 percent of the surveyed specialists and managers. Conversely, not even ten percent of digitalisation experts expect that the possibilities of artificial intelligence will leave the current economy undisturbed.

How man and machine work together

The question of the future interaction and role distribution between man and machine reveals interesting differences of opinion among the experts: While 43 % believe that AI makes people smarter, 34 % believe that the opposite is the case and that people are more likely to become less smart. And just under a third (30 %) even expect machines to outperform humans in many areas of human intelligence. But the distribution of roles in the future cooperation of intelligent systems and humans will probably be strongly influenced by the fact that man’s imagination and inventiveness cannot be replaced by machines. At least 56% (strong to very strong) are convinced of this.

However, experts forgo the science-fiction visions and view this topic very soberly:

76 percent of decision-makers believe that although AI can be used very successfully for manageable tasks, it will not reach the enormous range and abilities of a human being. This is an important insight when it comes to concrete deployment planning: therefore, every other digitization decision-maker warns of the risk that companies could overestimate the performance of an AI-powered device and that people rely too much on the smart machine.

What AI makes possible

Concurrently, AI’s diverse range of application is undisputed - this has already been demonstrated in practice: AI systems are already capable of scanning millions of security-relevant processes and revealing threats. They analyze videos from surveillance cameras to detect patterns or anomalies or offer collision avoidance functions in logistics and autonomous driving. AI systems can read complex sets of medical images and test results and develop a recommendation for a diagnostic and treatment plan. Still, others will simply help to process the information from sensors and assist the colleague in quality control, which is often very tiring for people. The digitalisation experts might use these tangible experiences as a basis for future AI projects, focusing on the human being as the central authority.

Three-quarters of companies in Germany, Austria and Switzerland rate artificial intelligence (AI) as an important topic for the future.

70% of DACH companies are active

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03. Where companies investThe decision-makers between the North Sea and the Alps consider process automation and better support for people in their work to be the most important targets for investment in artificial intelligence (around 80 percent). In addition, the companies in Germany, Austria and Switzerland want to primarily spend money on smart algorithms that proactively enable customer service and develop new offerings supported by AI systems (74 percent each).

The following example shows how the targets set by the DACH decision-makers can be implemented in practice: a medium-sized lighting manufacturer receives around 50,000 enquiries per year - around two and a half to three million documents are submitted by customers for review. In most cases, these are complete building specifications, most of which are not relevant for a lighting technology offer. In the past, the documents were examined by 80 employees. This monotonous process is now handled by AI-based software. The AI system frees the sales department from time-consuming routine work. This enables the salespeople to concentrate on what they do best – namely, qualified person-to-person communication. In this interaction between the sales representative and the customer, for example, practical challenges are discussed that cannot be found in any machine-readable document and from which up-selling options can be derived.

“AI is becoming an increasingly important production tool in many business areas,” says Dr. Bruno Messmer, Head of Digital Strategy Consulting at DXC Technology. “Thanks to advances in pattern recognition, essential for the automatic analysis of text and images, technology is increasingly being used to perform work that relieves people. In individual areas, the capabilities of AI systems exceed those of humans, so that employees are freed from routine tasks and their time, energy and talents can be used for more meaningful tasks,” says Bruno Messmer.

Source: DXC Survey “Artificial Intelligence 2019”.

Question: When you think about investments, what will be the most important fields of deployment for artificial intelligence in your company in the next two years?

Artificial intelligence should be used in the next two years to ...

extremely important important less important unimportant

Automate processes33 47 15 5

30 51 14 5

28 46 19 7

28 46 18 8

Better support employees in their work

Make customer service proactively possible

Develop new offers (products/services)

Artificial Intelligence for automation and employee support

80% want to invest in process automation

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Infographic: AI is important

04. AI tests the use of medication on patientsHospitals have a special duty of care when dispensing medicines: Since even the smallest misdosage or the wrong choice of active ingredient can put patients’ lives at risk, there is a need for complete control and counter-control of prescriptions.

A university hospital in Spain had planned to automate and secure this process with the help of new technologies. The reason: validating prescriptions is becoming increasingly time-consuming and complicated. For example, the mix of medicines - i.e. the combination of different active substances - is becoming more and more diverse. This control requires both medical and pharmaceutical expertise. Due to the large volume of prescriptions, pharmacists only validated around 30 percent of prescriptions and focused primarily on the most critical groups of active substances. This rate had to be improved.

Doctors and pharmacists work with AI support

A DXC technology team of data scientists, UI engineers and hospital experts, together with doctors and pharmacists, has developed a machine learning solution for the automatic validation of prescriptions. The core of the solution is based on a machine learning engine that had already proven itself in practice during clinical coding. This system was extended for the new tasks.

AI IS IMPORTANT

DXC Technology interviewed 500 companies in Germany, Austria and Switzerland to find out what specialists and executives in digital transformation deci-sion-making roles think about

„Artificial Intelligence“

75 %

58 %

…consider AI to be an important subject

… have included AI in their strategic planning

Carlos Nuño Moya, Solution Strategist DXC

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Machine learning recognizes risky prescription models

Today, the learning system uses historical data for the machine training of prescription models.

For this purpose, thousands of characteristics are considered. These include data on patient condition, medication history, prescription alerts, allergies and many other aspects.

Training the prescription models with machine learning was comparable to the task of searching for very few, painful needles in a huge haystack, i.e. identifying and learning combinations that patients could not tolerate.

Mission “prescription check” successful

Today, the automatic prescription validation program tests each prescribed drug according to a set of pre-defined rules, incorporating the expertise of the experts. The prescription is then compared with existing active prescriptions and possible drug interactions. The process considers the patient’s history, including known allergies and current condition. At the end of the pharmaceutical validation process, a prescription is finally approved or rejected. If the result is negative, the case is returned to the prescribing physician for revision.

05. Who are the implementers?Do-it-yourself or do it with partners? As the survey results reveal, there is more than one way for DACH decision-makers to succeed with AI projects. Several different cooperation models are particularly popular - above all, commercial AI solutions from digital corporations.

70 percent of digitization decision-makers for DACH want to focus on commercial AI offerings from large companies such as Amazon, Microsoft, SAP, IBM, Google or others.

Established public cloud providers are ready to help customers get started with AI. One of the biggest emerging areas here are chatbots: across industries, many companies are integrating these AI-based helpers into their website backends to answer standard customer queries. More complex or sensitive questions are forwarded to customer service staff instead. This saves time and money and improves customer service. Another growth area for AI is Natural Language Processing (NLP). But Machine Learning (ML), a part of AI, is proving to be useful for companies across the board. Among other things, ML can be used to identify trends, anomalies and patterns in large amounts of structured and unstructured data and derive action-relevant information from them.

70% rely on commercial AI offers

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Develop or buy?

67 percent of decision-makers wish to build up their own AI competence. Half of those are in favor of working with start-ups. In principle, there is always the question of when it makes sense to develop AI solutions by yourself, and when it should be purchased. This decision should depend on whether AI plays a central role in the company. This is the case, for example, when artificial intelligence offers a considerable competitive advantage – be it through improved speed, forward-thinking analyses, innovation or customer service. Since AI can also contribute to optimizing standard processes such as customer personalization, product recommendations, chatbots or cyber security analysis, it may be more appropriate to use a cloud-based AI-as-a-Service solution or a customized commercial . Whichever way a company chooses: In most cases, developing and managing new AI applications requires new AI skills, tools and platforms, including in-house IT teams.

applies does not apply

We rely on commercial solutions from Microsoft, Amazon, IBM, Google, SAP or others.

70 30

67 33

28 46

We need to build our own A.I. capabilities

We rely on cooperation with start-ups.

Digital companies and start-ups are highly rated on AI issues

Question: How do you plan to implement your artificial intelligence projects?

For artificial intelligence ...

67% want to develop their own know-how

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06. Infographic: Investments in AI

07. Collaborating with AI in the corporate worldThe design potential of artificial intelligence is also undisputed: around 80 percent of companies assume that our world will radically change with the help of smart algorithms.

When asked how artificial intelligence can improve our lives, many people first think of complex visions of the future, such as autonomous cars or fully automated smart homes. However, AI can bring the fastest progress where we spend the most hours every day: at work.

AI becomes a useful helper at the workplace

Experts assume that AI, robotics and machine learning primarily take over manual and repetitive tasks, which are very common in the office or factory. AI will significantly improve productivity by guiding human colleagues through different processes and handling time-consuming tasks. Employees who switch between different devices during the course of a working day, for example, can benefit from an AI-supported workflow. Manually controlled, error-prone routines are transferred to the machine, such as those that occur in many industries with electronic document management.

80% assume that the world will radically change due to AI systems

INVESTMENTS IN AI

DXC Technology interviewed 500 companies in Germany, Austria and Switzerland to find out what specialists and executives in digital transformation deci-sion-making roles think about

„Artificial Intelligence“

80 %

80 %

75 %

Companies will invest in AI in the next 2 years to …

… make em-ployees more productive

… supportstrategic decisions

… automateprocesses

50 %…  believe that the economic model will radically change

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Machines helping on command

The way we interact with AI-based systems is also rapidly changing. Voice-operated systems provide people at work with a natural, user-friendly interface for actions requested by the user. Today, they are already able to accompany conversations, document action points, take notes, or create calendar entries - ideal for meetings. Meanwhile, chatbots are making life easier for employees and customers by answering simple technical questions directly and providing step-by-step instructions on how to fix common problems.

In addition, in the near future AI will translate automatically, reliably and in real time between different languages, helping global companies interact with customers in multiple countries. By relieving employees of their workload, new areas for more human creativity are created in all deployment scenarios - an effect that will clearly have a positive impact on business development.

08. The evolution of AI in the corporate worldSystem developers from Robotic Process Automation (RPA) look at how people carry out professional activities. These actions are simulated and automated with robotic software systems. The use of artificial intelligence is currently ensuring that the field is booming: by the end of 2022, at least 85 percent of large and very large companies will be using software robots - according to the Gartner Group’s RPA prognosis. In order to make good use of the opportunities offered by RPA, the implementation of three development stages in a company’s practice is recommended:

Stage 1 – Automation of standard tasks

In the first stage, companies should use RPA to quickly automate simple routine tasks. Often these are simple scripts for desktop workflows. An example: For an energy company, DXC has built a software robot to automate processes in the SAP system. These routine tasks took place around 300 times a month and took the team 15 minutes each to complete. The employees who were previously responsible were freed from these boring tasks within just six weeks and are now devoting themselves to other tasks. The processes now run automatically in the SAP system. At this stage, the software robot only imitates the behavior of a human user. It is not yet intelligent in the sense of AI, so it does not think, does not check and does not generate new knowledge.

Stage 2 - Learning new tricks

In the second stage, the robot is brought closer to the human model - not in the sense of emotions, but by equipping it with multi-skills. At this stage of development, the robot is no longer a machine with savant syndrome, but has numerous new capabilities. What does that mean in concrete terms? The software robot sends, receives and processes data streams from various systems. It can read texts, analyze and evaluate databases, execute processes and solve new problems thanks to the use of AI and machine learning.

By 2022,

85% of companies will rely on some type of robot

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A good example of this is invoice management: usually experienced employees check incoming and outgoing invoices. With international customers, this is a very complex process due to different laws, contracts or compliance regulations. However, since this data is available digitally, the robot software prepares decisions and verifies invoices. The invoice and exchange formats are taken into account as well as international regulations. For example, DXC Technology has developed a solution for a global consumer goods company that allows 357,000 invoices in 250 different formats to be regularly checked and processed. The robotic software uses text mining to read the invoices, arrange them and trigger the processes for accounts receivable accounting in the SAP system. It can generate queries independently and usually “understands” the incoming responses. If this is not the case, a human colleague trains the robot until he “realizes” how to solve certain problems.

Stage 3 - Predictive Services

With the help of AI algorithms, the software robots in the third stage will work on complex processes largely independently. No processes need to be preconfigured or programmed. One example of this is predictive services. Here, the virtual employee recognizes problems before they occur and can apply patches independently - for example, if network problems are involved. Industrial companies monitor their systems and receive regular status reports. When an incident or anomaly is reported, an engineer usually searches for the reason and fixes the problem. With predictive services, this process can be automated. An analytics engine working with AI algorithms recognizes that the machine is very likely to fail soon as a result of the event. As a virtual engineer, a software robot then automatically searches the system for various parameters; it can start and process 50 queries simultaneously. If the cause is in the network, he instructs the Level 3 employee at the service desk - or he notifies the virtual network agent bot, which automatically rolls out the corresponding patch. Predictive services create new options for collaboration between man and machine. For an automobile manufacturer, for example, the number of tickets created by end-users could be significantly reduced. Every ticket means that the end-user must deal with the system instead of being able to productively take care of his work. This results in productivity losses and frustration for the employee, who is kept away from work. Instead, the AI detects errors in the systems before they happen and automatically alerts an IT engineer to intervene. The error is thus eliminated before it takes effect. Engineering jobs that require physical intervention can already be supported by AI systems and corrective actions can be coordinated. The Workplace Services area and its associated applications can already be optimized to a very large extent through this type of automation.

IN SUMMARY

The three stages of the AI evolution are showing that the digital transformation should start in every company without any loss of time. The spectrum ranges from simple automation of tedious routine tasks to smart solutions for complex tasks. In any case, robotic process automation can help digitize the processes and generate benefits for the business that can be critical in a highly competitive market.

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09. Forecast: Intelligent journey into a new worldAI systems today are already capable of astonishing performance and, due to their distinct “savant syndrome”, are exceptionally good at some tasks: Artificial intelligence recognizes patterns in huge amounts of data, wins against people at go or poker, chats with customers in customer service or relieves employees of repetitive tasks. The gradual combination of these individual talents into a general artificial intelligence is currently being pushed by billions in investment from countries such as China and the USA, as well as private organizations.

Classic working roles are disappearing - new ones are being created

For societies, this will raise the question of how people want to deal with intelligent systems in the future. In more and more aspects of life, AI systems offer themselves as alternative assistants. At the same time, we will learn which human capabilities are preferable to machines. The world of work is thus on the verge of upheaval. We will see that machines do not only relieve us of heavy physical work, a truth accepted since the Industrial Revolution. What’s new is that artificial intelligence can take the load off mental work or take over tasks. Therefore, traditional work roles will disappear, and new ones will emerge.

Tomorrow’s world of work - 3 examples

1. The AI trainers will have to take on the task of familiarizing intelligent systems with complex new environments. The multi-layered deployment scenarios need human ability to have a cross-border overview, and to detect and eliminate errors while executing activities during the learning process.

2. The AI supervisor also remains a human being in the most important tasks. Independently acting, decisive AI systems will have to be controlled by people for a long time to ensure compliance with government and corporate rules - as well as trust in general.

3. The AI Explainers are responsible for the transparency of AI solutions. Self-learning systems based on neural networks are capable of extraordinary performance. However, there’s a possibility that the traceability of the solutions is no longer given. Therefore, there will be a growing need of more and more “mediators” and “explainers” of suggestions, which were worked out by AI, so that they can be understood and accepted by humans.

Man or machine - AI needs transparency

With the rapid spread of intelligent systems, consumers will increasingly develop the expectation that products should be intelligent. In addition, when interacting with companies, people will want to know whether they’re dealing with an AI system or a human being. Virtual influencer Lil Miquela, who has been shaped like a human being thanks to AI, and the controversy surrounding her advertising activities have shown that transparency in dealing with AI-based services will be extremely important in building trust. For companies, this trend means making products and services “smart” using AI and incorporating this goal - along with the questions of acceptance - into strategic planning.

Dr. Bruno Messmer, Digital Strategy Consultant at DXC

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Man thinks and steers

In a world full of artificial intelligence, the ability to work creatively - based on combining rational thinking with experience and the still-not-fully-understood power of intuition and imagination - will remain the most important unique selling point of human beings in a world full of intelligent machines. The potential of AI to analyze and learn from data and based on these learnings, simulating the effects of economic and political decisions and proposing new solutions will be a valuable technological contribution to human society.

Learn more at www.dxc.technology

About DXC TechnologyDXC Technology, the world’s leading independent, end-to-end IT services company, manages and modernizes mission-critical systems, integrating them with new digital solutions to produce better business outcomes. The company’s global reach and talent, innovation platforms, technology independence and extensive partner network enable more than 6,000 private- and public-sector clients in 70 countries to thrive on change. For more information, visit www.dxc.technology.

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