Analýza: Podpora rozvoje umělé inteligence v EU - Tvoříme Evropu
Z hospodářského hlediska nabízí mnoho příležitostí, zároveň však přináší řadu obav a výzev, které se zavaděním nových technologii úzce souvisí.
studie
Umělá inteligence a její rozmach významně ovlivňuje pracovní trh. Ten se bude muset s nástupem AI vyrovnat. Pracovní místa 40 % Čechů by do patnácti let mohla zaniknout právě v důsledku rozšiřování AI. Práci na jejich dnešních pozicích budou moci zvládat stroje, automaty a roboti. Vyplývá to z globální <anchor>studie</anchor> poradenské společnosti PricewaterhouseCoopers. Český pracovní trh byl mezi 29 zkoumanými zeměmi hodnocen jako čtvrtý nejohroženější. Automatizace se může logicky nejvíce dotknout lidí s nejnižším vzděláním. Pravděpodobnost, že přijdou kvůli novým technologiím o práci, je navíc u žen vyšší než u mužů. Častěji totiž vykonávají činnosti, kde pravděpodobnost budoucí automatizace přesahuje 90 %.
PwC's Global Artificial Intelligence Study | PwC
PwC's Global Artificial Intelligence Study \| PwC

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# Sizing the prize

PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution


What’s the real value of AI for your business and how can you capitalise?


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- $15.7tr



Potential contribution to the global economy by 2030 from AI

- +26%



Up to 26% boost in GDP for local economies from AI by 2030

- ~300



AI use cases identified and rated are captured in our AI Impact Index


## Highlights

- Artificial intelligence (AI) can transform the productivity and GDP potential of the global economy. Strategic investment in different types of AI technology is needed to make that happen.


- Labour productivity improvements will drive initial GDP gains as firms seek to "augment" the productivity of their labour force with AI technologies and to automate some tasks and roles.


- Our research also shows that 45% of total economic gains by 2030 will come from product enhancements, stimulating consumer demand. This is because AI will drive greater product variety, with increased personalisation, attractiveness and affordability over time.


- The greatest economic gains from AI will be in China (26% boost to GDP in 2030) and North America (14.5% boost), equivalent to a total of $10.7 trillion and accounting for almost 70% of the global economic impact.


**Getting down to what really counts**

**Getting down to what really counts**

Explore the global results further using our [interactive data tool](#explorer) or see [which of your products and services will provide the greatest opportunity for AI](#impact). You can also [download our report](#download) to get a more detailed analysis and commentary on the positive economic outcomes.

[Download the full report](/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf)

_All GDP figures are reported in market exchange rate terms__All GDP figures are reported in real 2016 prices, GDP baseline based on Market Exchange Rate Basis_

_Source: PwC analysis_

## $15.7 trillion game changer

#### Total economic impact of AI in the period to 2030

What comes through strongly from all the analysis we’ve carried out for this report is just how big a game changer AI is likely to be, and how much value potential is up for grabs. AI could contribute up to $15.7 trillion1 to the global economy in 2030, more than the current output of China and India combined. Of this, $6.6 trillion is likely to come from increased productivity and $9.1 trillion is likely to come from consumption-side effects.

While some markets, sectors and individual businesses are more advanced than others, AI is still at a very early stage of development overall. From a macroeconomic point of view, there are therefore opportunities for emerging markets to leapfrog more developed counterparts. And within your business sector, one of today’s start-ups or a business that hasn’t even been founded yet could be the market leader in ten years’ time.

[View how we got our results](/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study/research-and-methodology.html)

## AI impact index

AI is set to be the key source of transformation, disruption and competitive advantage in today’s fast changing economy. In this report we've drawn on the findings to create our AI Impact Index, where we look at how quickly change is coming and where your business can expect the greatest return.

The areas with the biggest potential and associated timelines are designed to help your business target investment in the short- to medium-term.

### Explore the AI impact by sector

Explore our findings in the data explorer below - the AI Impact scores range from 1-5 (1 being lowest impact, 5 being highest).

- Healthcare
- Providers/Health services
- Pharma/Life sciences
- Insurance
- Consumer health
- Automotive
- Aftermarket & repair
- Component suppliers
- Personal mobility

as a service
- OEM
- Financing
- Financial services
- Asset & wealth management
- Banking & capital markets
- Insurance

- Transportation & logistics
- Transportation
- Logistics
- Technology,

communications

& entertainment
- Technology
- Entertainment, media

& communication
- Retail
- Consumer products
- Retail
- Energy
- Oil & gas
- Power & utilities
- Manufacturing
- Industrial manufacturing
- Industrial products/

Raw materials

Personalization

Data Available

Utility

Estimated Use Case Adoption Time Frames, as a % of Total

Near Term (0-3 yr)

Mid Term (3-7 yr)

Long Term (7+ yr)

Time Saved

Potential AI Consumption Impact

## Which of your products and services will provide the greatest opportunity for AI?

- [Healthcare](#root_container_content-free-container_section-1354499656_tabshome0)
- [Automotive](#root_container_content-free-container_section-1354499656_tabshome1)
- [Financial services](#root_container_content-free-container_section-1354499656_tabshome2)
- [Retail and consumer](#root_container_content-free-container_section-1354499656_tabshome3)
- [Technology, communications and entertainment](#root_container_content-free-container_section-1354499656_tabshome4)
- [Manufacturing](#root_container_content-free-container_section-1354499656_tabshome5)
- [Energy](#root_container_content-free-container_section-1354499656_tabshome6)
- [Transport and logistics](#root_container_content-free-container_section-1354499656_tabshome7)

#### Healthcare

_**High potential use case: Data-based diagnostic support**_

AI-powered diagnostics use the patient’s unique history as a baseline against which small deviations flag a possible health condition in need of further investigation and treatment. AI is initially likely to be adopted as an aid, rather than replacement, for human physicians. It will augment physicians’ diagnoses, but in the process also provide valuable insights for the AI to learn continuously and improve. This continuous interaction between human physicians and the AI-powered diagnostics will enhance the accuracy of the systems and, over time, provide enough confidence for humans to delegate the task entirely to the AI system to operate autonomously.

_**Barriers to overcome**_

It would be necessary to address concerns over the privacy and protection of sensitive health data. The complexity of human biology and the need for further technological development also mean than some of the more advanced applications may take time to reach their potential and gain acceptance from patients, healthcare providers and regulators.

#### Automotive

**_High potential use case: Autonomous fleets for ride sharing_**

Autonomous fleets would enable travellers to access the vehicle they need at that point, rather than having to make do with what they have or pay for insurance and maintenance on a car that sits in the drive for much of the time. Most of the necessary data is available and technology is advancing. However, businesses still need to win consumer trust.

**_Barriers to overcome_**

Technology still needs development – having an autonomous vehicle perform safely under extreme weather conditions might prove more challenging. Even if the technology is in place, it would need to gain consumer trust and regulatory acceptance.

#### Financial services

_**High potential use case: Personalised financial planning**_

While human financial advice is costly and time consuming, AI developments such as robo-advice have made it possible to develop customised investment solutions for mass market consumers in ways that would, until recently, only have been available to high net worth (HNW) clients. Finances are managed dynamically to match goals (e.g. saving for a mortgage) and optimise client’s available funds, as asset managers become augmented and, in some cases, replaced by AI. The technology and data is in place, though customer acceptance would still need to increase to realise the full potential.

_**Barriers to overcome**_

Consumer trust and regulatory acceptance.

#### Retail and consumer

**_High potential use case: Personalised design and production_**

Instead of being produced uniformly, apparels and consumables can be tailored on demand. If we look at fashion and clothing as an example, we could eventually move to fully interactive and customised design and supply in which AI created mock-ups of garments are sold online, made in small batches using automated production, and subsequent changes are made to design based on user feedback.

**_Barriers to overcome_**

Adapting design and production to this more agile and tailored approach. Businesses also need to strengthen trust over data usage and protection.

#### Technology, communications and entertainment

**_High potential use case: Media archiving and search_**

We already have personalised content recommendation within the entertainment sector. Yet there is now so much existing and newly generated (e.g. online video) content that it can be difficult to tag, recommend and monetise. AI offers more efficient options for classification and archiving of this huge vault of assets, paving the way for more precise targeting and increased revenue generation.

**_Barriers to overcome_**

Cutting through the noise when there is so much data, much of it unstructured.

#### Manufacturing

**_High potential use case: Enhanced monitoring and auto-correction_**

Self-learning monitoring makes the manufacturing process more predictable and controllable, reducing costly delays, defects or deviation from product specifications. There is huge amount of data available right through the manufacturing process, which allows for intelligent monitoring.

**_Barriers to overcome_**

Making the most of supply chain and production opportunities requires all parties to have the necessary technology and be ready to collaborate. Only the biggest and best-resourced suppliers and manufacturers are up to speed at present.

#### Energy

**_High potential use case: Smart meters_**

Smart meters help customers tailor their energy consumption and reduce costs. Greater usage would also open up a massive source of data, which could pave the way for more customised tariffs and more efficient supply.

**_Barriers to overcome_**

Technological development and high investment requirements in some of the more advanced areas.

#### Transport and logistics

**_High potential use case: Autonomous trucking_**

Autonomous trucking reduces costs by allowing for increased asset utilisation as 24/7 runtimes are possible. Moreover, the whole business model of transport & logistics (T&L) might be disrupted by new market entrants such as truck manufacturers offering T&L and large online retailers vertically integrating their T&L.

**_Barriers to overcome_**

Technology for autonomous fleets is still in development.

## Way forward: Four steps to making the most out of AI

- [![](/gx/en/issues/data-and-analytics/assets/tab-ai-1.png)AI and your business](#tab_4-0-root_container_content-free-container_section-867541035_secondarynavigation)
- [![](/gx/en/issues/data-and-analytics/assets/tab-ai-3.png)Prioritise your response](#tab_4-1-root_container_content-free-container_section-867541035_secondarynavigation)
- [![](/gx/en/issues/data-and-analytics/assets/tab-ai-2.png)Talent, culture and technology](#tab_4-2-root_container_content-free-container_section-867541035_secondarynavigation)
- [![](/gx/en/issues/data-and-analytics/assets/tab-ai-4.png)Governance and control](#tab_4-3-root_container_content-free-container_section-867541035_secondarynavigation)

![](/gx/en/issues/data-and-analytics/assets/tab-ai-1.png)

AI and your business

![](/gx/en/assets/home/ai-study-hp.jpg)

### Work out what AI means for your business

The starting point for strategic evaluation is a scan of the technological developments and competitive pressures coming up within your sector, how quickly they will arrive, and how you will respond. You can then identify the operational pain points that automation and other AI techniques could address, what disruptive opportunities are opened up by the AI that’s available now, and what’s coming up on the horizon.

![](/gx/en/issues/data-and-analytics/assets/tab-ai-3.png)

Prioritise your response

![](/gx/en/industries/healthcare/publications/ai-robotics-new-health/ai-data-explorer.jpg)

### Prioritise your response

In determining your strategic response, key questions include how can different AI options help you to deliver your business goals and what is your appetite and readiness for change. Do you want to be an early adopter, fast follower or follower? Is your strategic objective for AI to transform your business or to disrupt your sector?

![](/gx/en/issues/data-and-analytics/assets/tab-ai-2.png)

Talent, culture and technology

![](https://www.pwc.co.uk/economic-services/assets/ai-hero.jpg)

### Make sure you have the right talent and culture, as well as technology

While investment in AI may seem expensive now, PwC subject matter specialists anticipate that the costs will decline over the next ten years as the software becomes more commoditised. Eventually, we’ll move towards a free (or ‘freemium’ model) for simple activities, and a premium model for business-differentiating services. While the enabling technology is likely to be increasingly commoditised, the supply of data and how it’s used are set to become the primary asset.

![](/gx/en/issues/data-and-analytics/assets/tab-ai-4.png)

Governance and control

![](/gx/en/industries/healthcare/publications/ai-robotics-new-health/ai-robotics-new-health-hero-thumb.png)

### Build in appropriate governance and control

Trust and transparency are critical. In relation to autonomous vehicles, for example, AI requires people to trust their lives to a machine – that’s a huge leap of faith for both passengers and public policymakers. Anything that goes wrong, be it a malfunction or a crash, is headline news. And this reputational risk applies to all forms of AI, not just autonomous vehicles. Customer engagement robots have been known to acquire biases through training or even manipulation, for example.

[![](/content/dam/pwc/network/icons/webtile/icon_download.png)\
\
Download our report (PDF, 13.3mb)\
\
PwC’s Global Artificial Intelligence Study: Sizing the prize](https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report.pdf)

## Related content

[**Accelerating innovation through responsible AI** \
Artificial intelligence (AI) is emerging as the defining technology of our age, with many industries already utilising AI in some form. Unleash the full...](https://www.pwc.co.uk/services/risk/insights/accelerating-innovation-through-responsible-ai.html)

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Global AI and Innovation Technology Leader, PwC United States

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