by Gábor Riba – this presentation given on 8 December 2017 at the AI Forum Hungary


AI is a collective term for computer systems that can sense their environment, think, learn, and take action in response to what they’re sensing and their objectives

No human in the loop


Automation of manual and cognitive tasks that are either routine or non- routine. This does not involve new ways of doing things – it automates existing tasks.

Autonomous Intelligence

AI systems that can adapt to different situations and can act autonomously without human assistance.

Human in the loop

Assisted Intelligence

AI systems that assist humans in making decisions or taking actions. Hard-wired systems that do not learn from their interactions.

Hardwired / specific systems

Augmented Intelligence

Adaptive AI systems that augment human systems decision making and continuously

learn from their interactions with humans and the environment.


Concerns the automation of complex decisions and trade- offs about limited resources

An area of data mining in which the data is extracted from the past and future outcomes or behaviours are predicted as accurately as possible

What are the actual use cases of AI
at PwC?

Please note that this slide is for demonstration purposes only – the list could basically go on forever


Predictive Application Programme Interfaces (APIs)

Forecasting and developing a series of complex actions to achieve an outcome, taking influencing factors into consideration

The process of capturing spoken words and converting them to binary data, useful for NLP and voice recognition (identifying who is speaking).

The conception, design, manufacture, and operation
of robots, both physical and in software form

Allows machines to recognise their surroundings and the contents in pictures and videos

Deep learning Machine learning


Machine vision


Planning and scheduling

Speech recognition

Natural language processing

PwC’s Digital Services

Enables interactions between
humans and computers in a
language that is naturally used 3

Areas of PwC Hungary AI expertise

Social listening

Review of campaigns, information about brand awareness and the opinion of the public, product validation

• Delivered projects for media authority, sports mega event

Drone Application –

Image Processing.

Drones can be applied in the field of image processing, supervising infrastructure in different industries, e.g. telecommunications, utilities

• Delivered projects for large utility company, energy company innovation unit

• Drone law / Lobby together with clients, universities


Robotic Process Automation (RPA)

Automation of financial processes, e.g. inter- company billing automation based on robotics, business rules and AI

• Focus areas banks, SSCs

• Cooperation with PwC CoE-s


Integrating chatbots into complex solutions

Chatbots can be integrated into many software-based solutions: as customer service, help, personal assistant, etc.

V. Predictions for industry

4.0 and other predictive business models

PwC can build a model for clients based on historical data and public data

• •

Delivered demos to contact centers

Cooperation with several partners with different approach

• National Technology Platform membership (i40)

• Factory visits for future cooperation at several manufacturing companies

e.g. information regarding machine maintenance

e.g. marketing automation, CHURN models, etc.


AI is the biggest commercial opportunity in today’s economy


• = plus $15.7 trillion in 2030

The economic impact of AI will be driven by

global GDP in 2030 as a result of AI

increased productivity

$6.6 trillion in 2030

increased consumption

$9.1 trillion in 2030

  • Productivity gains from automating processes (including use of robots and autonomous vehicles)
  • Productivity gains from augmenting labour force with AI technologies(assisted and augmented intelligence)

• Increased consumer demand resulting from

personalized and/or higher- quality AI-enhanced products and services


In the near term, productivity gains will drive GDP uplift, but increased consumption will eventually overtake productivity

The impact share from product innovation increases over time as new technologies are gradually adopted and consumers respond to improved products with increased demand

in 2030

consumption side impacts
are expected to drive 58% of all GDP gains from AI

Quality and product innovation

Person- alization

over the period 2017-2030

productivity improvements are expected to account for over 55% of all GDP gains from AI

Source: PwC analysis


Healthcare, automotive and financial services have the largest potential to benefit from AI

Areas with biggest AI potential


  • Data-based AI-powered diagnostic support
  • Early identification of potential pandemics
  • Imaging diagnostics (radiology, pathology)


• Autonomous fleets for ride sharing

• Semi-autonomous features e.g. driver assist

• Engine monitoring and predictive, autonomous maintenance

• Ready to go: Automated driver assistance systems (e.g. parking assist, lane centring, adaptive cruise control etc.)

• Medium-term potential: On- demand parts manufacturing and maintenance

• Longer-term potential: Engine monitoring and predictive, autonomous maintenance

Financial services

• Personalised financial planning • Fraud detection and anti-money

• Process automation for back office &

customer facing operations

• Ready to go: Robo-advice, automated insurance underwriting and robotic process automation in e.g. finance and compliance

• Medium-term potential: Optimised product design based on consumer sentiment and preferences

• Longer-term potential: Moving from anticipating what will happen and when e.g. insurable loss (predictive analytics) to proactively shaping the outcome (prescriptive analytics) e.g. reduced accident rates or improved consumer outcomes


  • Ready to go: Medical insurance and smarter scheduling (e.g. appointments, operations)
  • Medium-term potential: Data- driven diagnostics and virtual drug development
  • Longer-term potential: Robot doctors carrying out diagnosis and treatment


AI will also disrupt a number of other industries

Technology, Retail communications


Enhanced monitoring and auto-correction of manufacturing processes


Transport and logistics

Areas with biggest AI potential

  • Personalised design & • production
  • Anticipating customer demand – e.g. using
    deep learning to • predict orders
  • Inventory and delivery management •
  • Ready to go: Product • recommendation based on preferences •
  • Medium-term potential: Fully customized products •
  • Longer-term potential: Products that anticipate demand from market signals

and entertainment

Media archiving & • search – bringing
together diffuse content for recommendation Customised content • creation (marketing,

film, music, etc.)

Personalised • marketing, advertising

Ready to go: Content • recommendation Medium-term • potential: Automated telemarketing Longer-term

potential: Use-case specific and individualized • AI created content

Autonomous trucking and delivery
Traffic control and

Supply chain and production
optimization •

On-demand production

Smart metering – real- •
time information on
energy usage, reduced •
bills reduced congestion More efficient grid

• Enhanced security

operation and storage

Predictive infrastructure maintenance


Ready to go: Greater
automation metering

Medium-term potential: Intelligent automation from supply chain optimization to predictive scheduling

Longer-term potential: Using prescriptive analytics in product design

• Medium-term

Ready to go: Smart • potential: Optimized •

power management

• Longer-term potential: More efficient and • consistent renewable
energy supply e.g.

improved prediction and optimization of wind power

Ready to go:

Automated picking in warehouses Medium-term potential: Traffic control
Longer-term potential: Autonomous trucking and delivery


AI will have an impact on your business model across all five aspects



AI is opening up new possibilities

Customer engagement

AI is reshaping interactions with customers, from sales and marketing to billing and after-sales support


AI can improve operational efficiency and provide significant competitive advantage

People and talent

AI is creating brand- new job categories

Concurrently, new technologies beget new companies and new job categories


Changing regulatory landscapes

The regulators themselves are likely to be in a catch-up mode for a while

The prize is being far more capable, in a far more relevant way, than your business could ever be without the infinite possibilities of AI


Realizing the potential in AI


How vulnerable is your business model to AI disruption? How soon will the change arrive?

4 questions to address to keep pace and capitalize on the opportunities

Do you have the right talent, data and technology to help you understand and execute on the AI opportunities?

Work out what AI means for your business

Prioritize your response


How can you build trust and transparency into your AI platforms and applications?

Are there game- changing openings within your market and, if so, how can you take advantage?

03 Make sure you have the right talent and culture,

as well as technology


Build in appropriate governance and control

Start thinking about AI now. Companies that fail to adapt and adopt can quickly find themselves undercut by competition


Thank you!

© 2017 PricewaterhouseCoopers Hungary Ltd. All rights reserved. PwC refers to PricewaterhouseCoopers Hungary Ltd. and may sometimes refer to the PwC network. Each member firm is a separate legal entity. Please see for further details.

All information contained in this presentation shall be considered PwC confidential. You cannot publish or otherwise disseminate all or part of this information to any third party whatsoever, without the prior permission of PwC.


Net effect of AI, not growth prediction

Our results are generated using a large scale dynamic economic model of the global economy. The model is built on the Global Trade Analysis Project (GTAP) database. GTAP provides detail on the size of different economic sectors (57 in total) and how they trade with each other through their supply chains. It gives this detail on a consistent basis for 140 different countries.

When considering the results, there are two important factors that you should take into account:

Our results show the economic impact of AI only – our results may not show up directly into future economic growth figures, as there will be many positive or negative forces that either amplify or cancel out the potential effects of AI (e.g. shifts in global trade policy, financial booms and busts, major commodity price changes, geopolitical shocks etc).

Our economic model results are compared to a baseline of long-term steady state economic growth. The baseline is constructed from three key elements: population growth, growth in the capital stock and technological change. The assumed baseline rate of technological change is based on average historical trends. It’s very difficult to separate out how far AI will just help economies to achieve long-term average growth rates (implying the contribution from existing technologies phase out over time) or simply be additional to historical average growth rates (given that these will have factored in major technological advances of earlier periods).

These two factors mean that our results should be interpreted as the potential ‘size of the economic prize’ associated with AI, as opposed to direct estimates of future economic growth.