Informatyka w Firmie Archive


Notes from the AI frontier: Applications and value of deep learning

Artificial intelligence (AI) stands out as a transformational technology of our digital age—and its practical application throughout the economy is growing apace. For this briefing, Notes from the AI frontier: Insights from hundreds of use cases (PDF–446KB), we mapped both traditional analytics and newer “deep learning” techniques and the problems they can solve to more than 400 specific use cases in companies and organizations. Drawing on McKinsey Global Institute research and the applied experience with AI of McKinsey Analytics, we assess both the practical applications and the economic potential of advanced AI techniques across industries and business functions. Our findings highlight the substantial potential of applying deep learning techniques to use cases across the economy, but we also see some continuing limitations and obstacles—along with future opportunities as the technologies continue their advance. Ultimately, the value of AI is not to be found in the models themselves, but in companies’ abilities to harness them.

It is important to highlight that, even as we see economic potential in the use of AI techniques, the use of data must always take into account concerns including data security, privacy, and potential issues of bias.

  1. Mapping AI techniques to problem types
  2. Insights from use cases
  3. Sizing the potential value of AI
  4. The road to impact and value


Implications for stakeholders

As we have seen, it is a company’s ability to execute against AI models that creates value, rather than the models themselves. In this final section, we sketch out some of the high-level implications of our study of AI use cases for providers of AI technology, appliers of AI technology, and policy makers, who set the context for both.

  • For AI technology provider companies: Many companies that develop or provide AI to others have considerable strength in the technology itself and the data scientists needed to make it work, but they can lack a deep understanding of end markets. Understanding the value potential of AI across sectors and functions can help shape the portfolios of these AI technology companies. That said, they shouldn’t necessarily only prioritize the areas of highest potential value. Instead, they can combine that data with complementary analyses of the competitor landscape, of their own existing strengths, sector or function knowledge, and customer relationships, to shape their investment portfolios. On the technical side, the mapping of problem types and techniques to sectors and functions of potential value can guide a company with specific areas of expertise on where to focus.
  • Many companies seeking to adopt AI in their operations have started machine learning and AI experiments across their business. Before launching more pilots or testing solutions, it is useful to step back and take a holistic approach to the issue, moving to create a prioritized portfolio of initiatives across the enterprise, including AI and the wider analytic and digital techniques available. For a business leader to create an appropriate portfolio, it is important to develop an understanding about which use cases and domains have the potential to drive the most value for a company, as well as which AI and other analytical techniques will need to be deployed to capture that value. This portfolio ought to be informed not only by where the theoretical value can be captured, but by the question of how the techniques can be deployed at scale across the enterprise. The question of how analytical techniques are scaling is driven less by the techniques themselves and more by a company’s skills, capabilities, and data. Companies will need to consider efforts on the “first mile,” that is, how to acquire and organize data and efforts, as well as on the “last mile,” or how to integrate the output of AI models into work flows ranging from clinical trial managers and sales force managers to procurement officers. Previous MGI research suggests that AI leaders invest heavily in these first- and last-mile efforts.
  • Policy makers will need to strike a balance between supporting the development of AI technologies and managing any risks from bad actors. They have an interest in supporting broad adoption, since AI can lead to higher labor productivity, economic growth, and societal prosperity. Their tools include public investments in research and development as well as support for a variety of training programs, which can help nurture AI talent. On the issue of data, governments can spur the development of training data directly through open data initiatives. Opening up public-sector data can spur private-sector innovation. Setting common data standards can also help. AI is also raising new questions for policy makers to grapple with for which historical tools and frameworks may not be adequate. Therefore, some policy innovations will likely be needed to cope with these rapidly evolving technologies. But given the scale of the beneficial impact on business the economy and society, the goal should not be to constrain the adoption and application of AI, but rather to encourage its beneficial and safe use.

About the author(s) : Michael Chui is a partner of the McKinsey Global Institute, where James Manyika is chairman and a director; Mehdi Miremadi is a partner in McKinsey’s Chicago office; Nicolaus Henke is a senior partner in the London office; Rita Chung is a consultant in the Silicon Valley office; Pieter Nel is a specialist in the New York office, where Sankalp Malhotra is a consultant.



Smart Homes 2020

Thanks to internet of things (IoT) devices, voice assistants and high-speed networking, smart homes are on the cusp of mainstream adoption. As sophisticated networks of door locks, vacuum cleaners and baby monitors become more common, brands see a gold mine of user data. But the rules of marketing engagement are changing. Privacy-conscious consumers don’t want interruptive advertising in their personal spaces. They’ll be more likely to roll out the welcome mat for brands that ask permission and help them solve their problems.

What are the most popular smart-home products, and why are people buying them?

Connected TVs, smart speakers, security systems and cameras, door locks, lighting and thermostats are among the top smart-home products. Consumers purchase these products—and related services—to make their lives easier, save time and money, improve energy efficiency and stay healthy and safe.

Who are the major players in the smart-home ecosystem?

Amazon, Google, Apple and Samsung have created some of the largest IoT and smart-home platforms in the West, while Baidu, Alibaba and Xiaomi are among top providers in China. Other players—including hardware manufacturers, security and telecom providers, utilities, software firms and startups—are also jockeying for position. The market is consolidating and more products are becoming cross-compatible.

Why should marketers be excited about smart homes?

Smart homes, cars and other interconnected IoT environments present new paradigms for human-computer interaction and opportunities for marketers to gain deeper insights about their audiences. They will enable responsible marketers to engage with consumers in more immediate, meaningful and personalized ways.

What will marketing within smart homes look like?

There is no blueprint for marketing or advertising on smart-home devices and no major ecosystems that support it. While some advertisers are serving ads on addressable TVs and within audio streams on voice-controlled devices, this interruptive messaging will give way to permission-based engagements that fit seamlessly into daily routines.

WHAT’S IN THIS REPORT? This report provides an overview of the state of smart homes. It also explains four forces that are guiding this market and how they will change traditional marketing models. More: eMarketer


Deloitte TMT Predictions 2020

Deloitte TMT Predictions 2020: Edge AI Chips, Private 5G, Robots Become Ever More Interconnected; Previously Hyped Innovations Become a Reality

More than 750 million edge AI chips will be sold in 2020

More than 100 companies worldwide will begin testing private 5G deployments by the end of 2020

Professional service robots will pass industrial robots in terms of units in 2020 and revenue in 2021

Ad-supported video services will reach an estimated US$32 billion in global revenue

Antenna TV will thrive in 2020 with at least 1.6 billion people worldwide, representing 450 million households, getting some of their TV from an antenna

Deloitte today released the 19th edition of its “Technology, Media & Telecommunications Predictions,” which looks at three overarching themes: individual technologies are becoming ever more interconnected and interdependent, increasing their impact and value as a result; smartphones, computers, TVs, enterprise data centers and software, and IoT will drive most of the TMT industry’s revenue; and lastly many previously hyped services and products will finally become a reality in 2020.

“In 2020, we will start to see a canopy effect where industry players will work more closely together as individual technologies like edge AI chips, robots and private 5G become better connected, and promising innovations like low-earth orbit satellites finally come to life,” says Paul Sallomi, vice chairman, Deloitte LLP, global TMT industry leader and U.S. technology sector leader. “This year’s predictions are a helpful guide for TMT business leaders to break through the clutter and understand what to do next in order to be successful in 2020 and beyond.”

AI has the edge

A new generation of edge artificial intelligence (AI) chips will reduce frustrations caused by lack of internet connection on smartphones by bringing AI to the device. Deloitte predicts that in 2020, more than 750 million edge AI chips—chips or parts of chips that perform or accelerate machine learning tasks on-device, rather than in a remote data center—will be sold, and that the edge AI chip market will continue to grow much more quickly than the overall chip market.

Private 5G: Enterprise untethered

Deloitte predicts that more than 100 companies worldwide will begin testing private 5G deployments by the end of 2020, collectively investing a few hundred million dollars in labor and equipment. For many of the world’s largest businesses, private 5G will likely become the preferred choice, especially for industrial environments such as manufacturing plants, logistics centers and ports.

“The emergence of 5G will offer unprecedented opportunities for companies to grow and achieve new levels of productivity,” says Craig Wigginton, Partner, Deloitte & Touche LLP and Global Telecommunications Leader. “In conjunction with other ecosystem technologies, such as IoT, 5G will enable a connected future that will continue to dramatically transform enterprises worldwide.”

Meet your new colleague, a robot

Of the almost one million robots Deloitte expects to be sold for enterprise use in 2020, just over half of them will be professional service robots, generating more than US$16 billion in revenue—30 percent more than in 2019. Professional service robots will pass industrial robots in terms of units in 2020 and revenue in 2021.

Can I have an ad with my content?

Deloitte predicts that global revenue from ad-supported video services will reach an estimated US$32 billion in 2020. Asia, including China and India, will lead with US$15.5 billion in revenue in 2020, nearly half of the global total. In China, India, and throughout the Asia-Pacific region, ad-supported video is the dominant model of delivering streaming video to consumers. By contrast, in the United States, most direct-to-consumer video offerings are pursuing an ad-free subscription model.

“This year’s Predictions report encompasses a range of topics that will have a profound and positive effect on the future of media,” says Mark Casey, Partner, Deloitte Netherlands and Global Leader, Telecom, Media & Entertainment. “As more companies across industries seek to reach and influence consumers with content, the technologies covered in Predictions will provide exciting new growth and partnership opportunities for businesses—from sports franchises to streaming companies to social networks.”

Terrestrial TV’s surprising staying power

Antenna TV will thrive in 2020 with at least 1.6 billion people worldwide, representing 450 million households, enjoying some of their TV viewing via an antenna. Antenna TV will help the global TV industry to keep growing even in the face of falling TV viewing minutes and, in some markets, increasing numbers of consumers cutting the pay-TV cord.

More insight from Deloitte’s 2020 TMT predictions:

  • Low-earth orbit satellites soar: By the end of 2020, there will be over 700 satellites in low-earth orbit (LEO) seeking to offer global broadband internet, up from roughly 200 at the end of 2019. These new “mega-constellations” of orbiting broadband stations will potentially add more than 16,000 individual satellites to that count over the coming years.
  • Give a listen: In 2020, the global audiobook market will grow by 25 percent to US$3.5 billion and the global podcasting market will increase by 30 percent from 2019 to reach US$1.1 billion in 2020, surpassing the US$1 billion mark for the first time.
  • A smarter smartphone: The smartphone multiplier market (hardware, content, services) will drive US$459 billion of revenue in 2020 alone and will grow between five to 10 percent annually through 2023, lifted by continued robust growth in its largest components. This means that in 2023, the smartphone multiplier market is likely to generate revenues of more than a half-trillion dollars per year.
  • The workhorse of the internet: Deloitte also predicts the global Content Delivery Network (CDN) market will reach US$14 billion in 2020, up more than 25 percent from 2019’s estimated US$11 billion. The market will double to US$30 billion by 2025, a compound annual growth rate of more than 16 percent.
  • Roll to work: Tens of billions of additional bicycle trips per year will take place in 2022. The increase in bicycling will double the number of regular bicycle users in many major cities around the world where cycling to work is still uncommon. Deloitte predicts a 1 percentage point rise in the proportion of people who bike to work during the three years from 2019 to 2022. Between 2020 and 2023, more than 130 million e-bikes (using all battery technologies) are expected to be sold.

Now in its 19th year, Deloitte’s annual TMT Predictions provides an outlook on key trends in the technology, media and telecommunications industry sectors worldwide. Visit to learn more and connect with us on Twitter: @DeloitteTMT, @Deloitte, @PaulSallomi, @MarkAntonyCasey, @CraigWigginton, @Jeff_Loucks, @pjvlee, @dunstewart, @dajarvis and #DeloittePredicts.

About Deloitte

Deloitte provides industry-leading audit, consulting, tax and advisory services to many of the world’s most admired brands, including nearly 90% of the Fortune 500® and more than 5,000 private and middle market companies. Our people work across the industry sectors that drive and shape today’s marketplace — delivering measurable and lasting results that help reinforce public trust in our capital markets, inspire clients to see challenges as opportunities to transform and thrive, and help lead the way toward a stronger economy and a healthy society. Deloitte is proud to be part of the largest global professional services network serving our clients in the markets that are most important to them. Our network of member firms spans more than 150 countries and territories. Learn how Deloitte’s more than 312,000 people worldwide make an impact that matters at

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as “Deloitte Global”) does not provide services to clients. In the United States, Deloitte refers to one or more of the US member firms of DTTL, their related entities that operate using the “Deloitte” name in the United States and their respective affiliates. Certain services may not be available to attest clients under the rules and regulations of public accounting. Please see to learn more about our global network of member firms.

Key contacts: Paul Sallomi, Global Tech, Media, & Telecom Industry Leader; Craig Wigginton, Vice Chairman, Deloitte LLP US; Mark Casey, Global Leader, Telecom, Media & Entertainment


EY płatności kartowe mogą być przeszłością

Ankietowani przez EY uważają, że wkrótce nie tylko płatności gotówkowe, ale nawet kartowe mogą być przeszłością

Jak wynika z ankiety przeprowadzonej przez EY wśród uczestniczących w konferencji Sibos liderów instytucji finansowych, regulatorów i dostawców technologii z całego świata, za dziesięć lat urządzenia mobilne zdominują rynek płatności. Wśród najbardziej popularnych form płatności w 2030 roku nie wskazano gotówki, a karty płatnicze znalazły się na ostatnim miejscu.

59% ankietowanych przez EY podczas Sibos (coroczna międzynarodowa konferencja poświęcona tematyce usług płatniczych) przewiduje, że urządzenia mobilne oraz ubieralne (zegarki, bransoletki czy okulary) w ciągu najbliższych 10 lat zdominują rynek płatności. Niespełna jedna trzecia badanych oczekuje, że w 2030 roku płatności będą wykonywane przy wykorzystaniu narzędzi biometrycznych, a tylko 4% ankietowanych wskazuje, że w użyciu wciąż będą karty płatnicze. Ankietowani zapytani o najbardziej popularne metody płatności, nie wymienili natomiast gotówki.

Postępujący w szybkim tempie rozwój technologiczny zmienia handel i usługi. To z kolei w naturalny sposób wymusza zmiany na rynku płatności. Czy można jednak mówić o końcu gotówki? To bardzo złożone zagadnienie, bo rezygnacja z obrotu gotówkowego niesie za sobą korzyści, ale i ryzyka. Trzeba bowiem pamiętać, że mimo szybkiego postępu technologicznego, część konsumentów jest przywiązana do gotówki ze względów kulturowych. Przykładem mogą być Stany Zjednoczone, które – choć są rynkiem, z którego wywodzą się jedne z najbardziej innowacyjnych technologii – to jedna na trzy płatności dokonywana jest tu gotówką, a czeków używa się niemal tak często, jak płatności cyfrowych. Nawet w Szwecji – uznawanej za najbardziej bezgotówkowy kraj, wycofywanie banknotów i monet z obiegu wzbudziło dyskusję o wykluczeniu społecznym osób starszych, czy z niepełnosprawnościami – mówi Paweł Preuss, Partner EY, Financial Services Industry Leader.

Wśród oczywistych korzyści płynących z rozwoju transakcji bezgotówkowych, ankietowani przez EY wskazali wygodę (40%), zredukowanie liczby przestępstw finansowych i działalności w szarej strefie, co rocznie kosztuje światową gospodarkę nawet 3,5 biliona dolarów (34%). Wśród ryzyk, 36% badanych  wymieniono natomiast wykluczenie społeczne. Szczególnie niepokoi ono ankietowanych z Azji, Bliskiego Wschodu, Afryki, Ameryki Łacińskiej i Australazji. Niepokój ten podziela również 38% Europejczyków i 33% przedstawicieli branży z Ameryki Północnej.

Dla nieco ponad jednej piątej ankietowanych ryzykiem jest również odpowiednia ochrona danych. Taki sam odsetek badanych (21%) wskazał na ryzyka związane z wrażliwością scentralizowanej cyfrowej gospodarki. Niespełna jedna szósta ankietowanych przez EY dostrzega ryzyko w zwiększonej kontroli rządów nad indywidualnymi decyzjami, a 8% wskazuje na dodatkowe koszty, które płatności bezgotówkowe generują dla biznesu.

Jak pokazują wyniki przeprowadzonej podczas Sibos ankiety EY, głównym czynnikiem napędzającym rozwój płatności bezgotówkowych będą zmieniające się potrzeby klientów. Na ten aspekt wskazało 36% badanych. Istotne będą również zachęty płynące z branży i od rządów (na ten element wskazuje 25% badanych), a także rozwój rozwiązań przygotowywanych przez FinTechy (24%) oraz odpowiednie regulacje (16%).

– Obowiązująca od września ubiegłego roku dyrektywa PSD2 oprócz usprawnienia płatności i ich lepszego zabezpieczenia wprowadza również możliwość, by były one realizowane przez dostawców zewnętrznych – tzw. Third Party Provider. Mogą być nimi między innymi właśnie FinTechy specjalizujące się w nowoczesnych rozwiązaniach dla rynku płatności. Wciąż jednak zaufanie jest jednym z głównych warunków umożliwiających rozwój niebankowych usług finansowych. Jak pokazało inne badanie EY przeprowadzone w ubiegłym roku (FinTech Adoption Index 2019), powodem niekorzystania z rozwiązań FinTechów jest brak wiedzy o nich, bądź brak zaufania do świadczonych przez nie usług. Wciąż więc przed nami pozostaje w tej kwestii jeszcze wiele do zrobienia – dodaje Paweł Preuss.

Ankieta EY została przeprowadzona wśród uczestników ubiegłorocznej konferencji usług płatniczych Sibos w Londynie. W badaniu wzięło udział 129 osób reprezentujących instytucje finansowe, regulatorów, dostawców technologii i ekspertów z całego świata. 

Tomasz Bogusławski


The Power of Algorithmic Forecasting

This is the first in a series of articles by Boston Consulting Group and Daimler Mobility discussing the concept of forward-looking financial steering. Here, we introduce the concept and explain how companies can use it. Subsequent articles will address implementation challenges related to people and technology. The insights are derived from Daimler Mobility’s successful deployment, with BCG’s support, of forward-looking steering in its global operations.

People don’t steer their cars solely on the basis of what they see in the rearview mirror, yet that is essentially how most business leaders steer their companies: they look backward to decide how to move forward. This method makes it hard for companies to cope with the ever-increasing levels of uncertainty in today’s business environment. To keep up to speed, companies need an approach to financial steering that permits rapid and effective course corrections in anticipation of future developments. Companies should spend far less time developing detailed plans and far more time taking action to counter threats and capture opportunities.

To make that happen, the paradigm for steering must fully shift its focus from backward looking to forward looking. Backward-­looking steering entails analyzing deviations between plan targets and actual performance. Forward-­looking steering entails comparing targets with forecasts of how KPIs will evolve over specific time horizons. To truly adopt forward-looking steering (as described in this article), a company must use algorithmically derived forecasts.

Although it is common for companies to produce forecasts manually, few companies use algorithms. Algorithmically derived forecasts allow the focus to shift from periodically reporting results to accurately forecasting the development of KPIs—faster and with less effort. Armed with foresight into how conditions will change, companies can take action to preempt unfavorable outcomes and promote competitive advantage.

Adopting algorithm-based, forward-looking steering is not easy, however. A company must enrich its traditional manual processes with a data-driven, automated approach to generating forecasts and performance reports. Among the many challenges are assembling a team that has statistical capabilities, setting up a new technical infrastructure, and building people’s trust in technology.

“To master the digital transformation, a company must take a comprehensive approach to algorithm-based forward-looking steering,” says Stephan Unger, Daimler Mobility’s Chief Financial Officer (CFO). “This includes not only advanced analytical methods, new technologies, and the right expertise, but also an engaging approach to change management.”

By Gerhard Unger and Marc Rodt