Artificial Intelligence is transforming the world

Even the smartest AI can still be taught something.

Trust in Transformation: Trust in a partner who will take those important first steps with you in the future field of artificial intelligence and develop the decisive competitive advantages of the future with you.

Your expert for questions

Hendrik Reese

Hendrik Reese
Partner Artificial Intelligence, PwC Germany
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AI is the most fundamental technological development of our time

Whether autonomous driving, chatbots in call centers or innovative diagnostics: Artificial Intelligence (AI) is radically transforming more and more areas of our lives. For companies, AI is becoming one of the most important growth drivers.

“A key success factor for the acceptance and growth of AI is the issue of trust. When developing and implementing AI applications, it is crucial to focus not only on performance and quality, but to ensure transparency and security.”

Hendrik Reese,Partner Artificial Intelligence, PwC Germany

PwC supports companies in rethinking their business model, identifying risks and leveraging their potential in a targeted manner, and in turn converting these into added value. To do so, we combine our technical AI know-how with our profound expertise in the AI technology's widespread applications, challenges and risks.

How PwC can contribute to maximizing the benefits of KI for businesses and society

As we embark on a new digital decade, AI-powered solutions are set to be at the forefront of business transformation and disruption. In a recent study, we have calculated how big of a game changer AI and machine learning are likely to be: AI could contribute up to 15.7 trillion US dollars to the global economy by 2030. Moreover, by the end of 2024, 75 percent of enterprises will shift from piloting to operationalizing AI, according to the First Gartner Top Trend in Data & Analytics 2020.

However, many organizations still find it difficult to scale AI across their entire business. A large proportion of AI initiatives never progress further than successful Proof of Concepts (PoCs) or experimentations.

One of the major reasons why enterprises are still struggling to anchor AI in a value-adding manner is the lack of an enterprise-wide AI strategy. There is no “One size fits all” for a universal AI strategy to increase competitive advantage and effectuate AI-powered business outcomes.

We support you in developing a value-driven AI strategy, but also help with the practical implementation of AI, finding the right technology and operating model.

Trusted AI

Artificial Intelligence (AI) is now a central part of our professional and private lives. However, it still provokes uncertainty and reluctance among many people. To really trust decisions made by AI, users expect transparent and fair outcomes.

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Our services at a glance

Strategy & Foundations

We support you in developing AI strategies and roadmaps that are fully aligned with your business strategy and objectives. This process begins by identifying strategic AI priorities to clearly outline “What really matters now and in the future?” and “How to achieve this with AI?”.

On this basis, we derive concrete measures and place those in an overarching AI roadmap. We make sure that enabling strategies such as Data Strategy, Data Governance Strategy and Reference Architecture specifications are aligned to each other and incorporated.

Use Cases

With the current extent of available AI technologies, most business processes will benefit from AI solutions. Our approach is built on the lessons learnt from our numerous successful client engagements and based on three elements:

Envision: We start by identifying the most promising sources of value hidden in the data using an agile, sprint-based approach.

Implement: Within a few weeks, we develop fit-for-purpose solutions which are integrated into your unique technology stack. 

Scale: Our AI use case implementations are fully integrated into the systems (end-to-end) and can be used to automate and improve processes in production from day one.

Technology

Building analytics and deep learning capabilities is a challenging task requiring access to modern cutting-edge Data Science and technologies such as Big Data, Cloud Computing, natural language processing and containerization. With the help of our highly skilled technology consultants, we carry out an assessment of the existing AI technology landscape to analyse AI use cases, data sources, data pipelines and analytics architecture.

This helps us to identify the approach to solve your specific business problem and then narrow down the vendors, tools and technologies that best support the approach. 

We add value across many areas, including:

  • Data ingestion and integration

  • Cloud-enabled usage of modern platforms

  • Big data strategy and implementation

  • AI and analytics operationalization

  • Data governance and data quality

Operating Model

AI has the opportunity to work 24/7 as part of broader operational systems. The PwC experts support businesses on their journey from experimentation to industrialization of AI while also improving their operational efficiency and responsiveness with a sustainable operating model for AI.

That is why we focus on creating a data-driven culture with an operating model that transcends four dimensions: data, people, process, and technology. This is how we support a broader AI adoption and ensure that the developed AI solutions address the business challenges you want to solve.

Digital Trust

The use of new technologies comes with high expectations but also with new risks and uncertainties. PwC provides support, from the perspective of developers to the end users, in deriving process-related, technical and organizational requirements and safeguards. Transparency and trust play a decisive role in this process. On the basis of transparency regarding algorithms, data usage, and the field of application, concrete and realistic expectations can be defined, and the associated risks can be better understood and managed with appropriate mitigating measures. From our experience, it is crucial that all areas relevant to AI are included:

  • Security and robustness

  • Performance and functionality

  • Data quality and management

  • Reliability

  • Explainability and bias

Why trust should be at the core of any AI project

70 percent of AI projects do not achieve their desired impact on businesses right away. The reason for this: AI comes with enormous potential, but also with new risks and challenges. When AI projects fail, the reason is often that there is a lack of digital trust in how the transformation is managed to succeed.

Key elements of trust include reliable and robust use cases as well as processes that allow scale with high quality. At the same time, stakeholder engagement and acceptance are key to building trust.

PwC Forecast Plus

One example of an AI-based technology developed within PwC and already widely used in practice is PwC's Forecast Plus – a solution for automated financial forecasting. This forms the technical basis of the Predictive Excellence Platform.

Find out more

“While cutting-edge technology is crucial for delivering AI at scale, it is equally important for real success to integrate AI into business processes and align it with the company’s culture and new ways of working.”

Hendrik Reese,Partner Artificial Intelligence at PwC Germany
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Contact us

Hendrik Reese

Hendrik Reese

Partner, PwC Germany

Tel: +49 151 70423201

Prof. Dr. Frauke Schleer-van Gellecom

Prof. Dr. Frauke Schleer-van Gellecom

Partner, PwC Germany

Michael Berns

Michael Berns

Director, PwC Germany

Andreas  Odenkirchen

Andreas Odenkirchen

Director, Data & Analytics, Technology Consulting, PwC Germany

Tel: +49 151 15535019

Dr. Tobias Franke

Dr. Tobias Franke

Senior Manager, PwC Germany

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