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How artificial intelligence can deliver real value to companies

ARTIFICIAL INTELLIGENCE McK REPORT 2017 COVER

Companies new to the space can learn a great deal from early adopters who have invested billions into AI and are now beginning to reap a range of benefits.

After decades of extravagant promises and frustrating disappointments, artificial intelligence (AI) is finally starting to deliver real-life benefits to early-adopting companies. Retailers on the digital frontier rely on AI-powered robots to run their warehouses—and even to automatically order stock when inventory runs low. Utilities use AI to forecast electricity demand. Automakers harness the technology in self-driving cars.

A confluence of developments is driving this new wave of AI development. Computer power is growing, algorithms and AI models are becoming more sophisticated, and, perhaps most important of all, the world is generating once-unimaginable volumes of the fuel that powers AI—data. Billions of gigabytes every day, collected by networked devices ranging from web browsers to turbine sensors.

The entrepreneurial activity unleashed by these developments drew three times as much investment in 2016—between $26 billion and $39 billion—as it did three years earlier. Most of the investment in AI consists of internal R&D spending by large, cash-rich digital-native companies like Amazon, Baidu, and Google.

For all of that investment, much of the AI adoption outside of the tech sector is at an early, experimental stage. Few firms have deployed it at scale. In a McKinsey Global Institute discussion paper, Artificial intelligence: The next digital frontier?, which includes a survey of more than 3,000 AI-aware companies around the world, we find early AI adopters tend to be closer to the digital frontier, are among the larger firms within sectors, deploy AI across the technology groups, use AI in the most core part of the value chain, adopt AI to increase revenue as well as reduce costs, and have the full support of the executive leadership. Companies that have not yet adopted AI technology at scale or in a core part of their business are unsure of a business case for AI or of the returns they can expect on an AI investment.

However, early evidence suggests that there is a business case to be made, and that AI can deliver real value to companies willing to use it across operations and within their core functions. In our survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the next three years.

This adoption pattern is widening a gap between digitized early adopters and others. Sectors at the top of MGI’s Industry Digitization Index, such as high tech and telecoms or financial services, are also leading AI adopters and have the most ambitious AI investment plans. These leaders use multiple technologies across multiple functions or deploy AI at the core of their business. Automakers, for example, use AI to improve their operations as well as develop self-driving vehicles, while financial-services companies use it in customer-experience functions. As these firms expand AI adoption and acquire more data, laggards will find it harder to catch up.

Governments also must get ahead of this change, by adopting regulations to encourage fairness without inhibiting innovation and proactively identifying the jobs that are most likely to be automated and ensuring that retraining programs are available to people whose livelihoods are at risk from AI-powered automation. These individuals need to acquire skills that work with, not compete against, machines.

 

The future of AI will be innovative, but may not be shared equally. Companies based in the United States absorbed 66 percent of all external investments into AI companies in 2016, according to our global review; China was second, at 17 percent, and is growing fast. Both countries have grown AI “ecosystems”—clusters of entrepreneurs, financiers, and AI users—and have issued national strategic plans in the past 18 months with significant AI dimensions, in some cases backed up by billions of dollars of AI-funding initiatives. South Korea and the United Kingdom have issued similar strategic plans. Other countries that desire to become significant players in AI would be wise to emulate these leaders.

Significant gains are there for the taking. For many companies, this means accelerating the digital-transformation journey. AI is not going to allow companies to leapfrog getting the digital basics right. They will have to get the right digital assets and skills in place to be able to effectively deploy AI.

ARTIFICIAL INTELLIGENCE McK REPORT 2017 1 ARTIFICIAL INTELLIGENCE McK REPORT 2017 2 ARTIFICIAL INTELLIGENCE McK REPORT 2017 3

ARTIFICIAL INTELLIGENCE

Artificial intelligence is poised to unleash the next wave of digital disruption, and companies should prepare for it now. We already see real-life benefits for a few earlyadopting firms, making it more urgent than ever for others to accelerate their digital transformations. Our findings focus on five AI technology systems: robotics and autonomous vehicles, computer vision, language, virtual agents, and machine learning, which includes deep  learning and  underpins many recent advances in the other AI technologies.  AI investment is growing fast, dominated by digital giants such as Google and Baidu. Globally, we estimate tech giants spent $20 billion to $30 billion on AI in 2016, with 90 percent of this spent on R&D and deployment, and 10 percent on AI acquisitions. VC and PE financing, grants, and seed investments also grew rapidly, albeit from a small base, to a combined total of $6 billion to $9 billion. Machine learning, as an enabling technology, received the largest share of both internal and external investment.  AI adoption outside of the tech sector is at an early, often experimental stage. Few firms have deployed it at scale. In our survey of 3,000 AI-aware C-level executives, across 10 countries and 14 sectors, only 20 percent said they currently use any AIrelated technology at scale or in a core part of their businesses. Many firms say they are uncertain of the business case or return on investment. A review of more than 160 use cases shows that AI was deployed commercially in only 12 percent of cases.

Adoption patterns illustrate a growing gap between digitized early AI adopters and others. Sectors at the top of MGI’s Industry Digitization Index, such as high tech and telecom or financial services, are also leading adopters of AI. They also have the most aggressive AI investment intentions. Leaders’ adoption is both broad and deep: using multiple technologies across multiple functions, with deployment at the core of their business. Automakers use AI to develop self-driving vehicles and improve operations, for example, while financial services firms are more likely to use it in customer experience–related functions.   Early evidence suggests that AI can deliver real value to serious adopters and can be a powerful force for disruption. In our survey, early AI adopters that combine strong digital capability with proactive strategies have higher profit margins and expect the performance gap with other firms to widen in the future. Our case studies in retail, electric utilities, manufacturing, health care, and education highlight AI’s potential to improve forecasting and sourcing, optimize and automate operations, develop targeted marketing and pricing, and enhance the user experience.

AI’s dependence on a digital foundation and the fact that it often must be trained on unique data mean that there are no shortcuts for firms. Companies cannot delay advancing their digital journeys, including AI. Early adopters are already creating competitive advantages, and the gap with the laggards looks set to grow. A successful program requires firms to address many elements of a digital and analytics transformation: identify the business case, set up the right data ecosystem, build or buy appropriate AI tools, and adapt workflow processes, capabilities, and culture. In particular, our survey shows that leadership from the top, management and technical capabilities, and seamless data access are key enablers. ƒ. AI promises benefits, but also poses urgent challenges that cut across firms,  developers, government, and workers. The workforce needs to be reskilled to exploit AI rather than compete with it; and countries serious about establishing themselves as a global hub for AI development will need to join the global competition to attract AI talent and investment; and progress will need to be made on the ethical, legal and regulatory challenges that could otherwise hold back AI.

ARTIFICIAL INTELLIGENCE McK REPORT 2017 REPORT COVER

More in the discussion paper: Artificial intelligence: The next digital frontier?

About the authors:Jacques Bughin is a director of the McKinsey Global Institute, Michael Chui is an MGI partner, and Tera Allas is an MGI visiting fellow; Eric Hazan is a senior partner in the Paris office; Sree Ramaswamy is a partner in the Washington, DC, office; Peter Dahlström and Nicolaus Henke are senior partners in the London office, where Monica Trench is a consultant.

 

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The Five Mys KPMG

The Five Mys Figure 1

The multidimensional customer

In an era defined by uncertainty, the companies that get closest to their customers will emerge ahead of the pack. This begins with an “outside-in” view, building new ways of understanding how and why people make decisions.

You already know that customer behavior is changing. Power has shifted from companies to consumers, the mobile phone has become the remote control of our lives, trust in institutions and traditional advertising has diminished. Customer trade-offs and decisions are more opaque and moving faster. You’re already aware that the structure and composition of industry has changed. New entrants with radically new business models are enacting disruption across the value chain, reshaping ecosystems from sector to sector. Meanwhile, company lifespans are shrinking and the paths to billion-dollar valuations are accelerating. All these challenges are well documented across business media, research reports and conference presentations. But how should you use this information to understand not only where your customers are today but where they’ll be tomorrow? How can you rethink the basis of competition and pivot your operations and business models to win in the battle for growth? It’s time for a new approach. One that employs a multidimensional framework to engage what is now a multidimensional consumer.

Genesis of our findings For several years, we’ve worked shoulder to shoulder with clients to understand customer attitudes, behavior and expectations in our present era of disruption and uncertainty. Faint signals of change grew louder and bigger patterns began to emerge beyond one individual sector, building a sense of urgency and leading to our belief that we’re witnessing a structural change, not a temporal one. As our teams constructed a new way of thinking about a changing customer, we embarked on a multifaceted research program to validate our thinking and bring to bear the voice of the consumer. Combined with the extensive, worldwide experience of KPMG’s network of member firms, this has enabled us to identify how best to engage the 21st-century consumer, and our approach provides a tangible framework to help companies identify, understand and respond to today’s changing customer.

The Five Mys

Through a multi-dimensional lens called the Five Mys, businesses gain access to predictive insights that navigate the complexity of consumer decision making. The Five Mys include: My Motivation, My Attention, My Connection, My Watch and My Wallet. Each of the Five Mys in isolation tells only part of the story: together they provide companies with a clear picture of the collective influences on today’s consumer and how those affect decisions, preferences, choices and spending.

“For years, marketers have touted demographic segmentation for targeting customers. Looking at demographics alone, however, risks missing the multifaceted way in which people make decisions.”

My Motivation: Characteristics that drive behaviors and expectations

My Attention: Ways we direct our attention and focus

My Connection: How we connect to devices, information and each other

My Watch: How we balance the constraints of time and how that changes across life events

My Wallet: How we adjust our share of wallet across life events

More: KPMG Report. Me, my life, my wallet

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Biznes wymaga czasu i cierpliwości

Londyn fot. Grzybowski SAM_7436 Janusz Wysocki Londyn fot. Grzybowski

Rozmowa z: Janusz Wysocki, prezes i właściciel MIXER GROUP.

Internet Manager: Transport, usługi medyczne, szkoła i uczelnia, organizacja imprez, biuro księgowe, ezakupy, pomoc w załatwianiu rezydentur i obywatelstwa,  obrót nieruchomościami, wreszcie własne wydawnictwo i radio. Jak dochodzi się do tak  zróżnicowanej działalności?

Janusz Wysocki – Cierpliwością. Zaczynając kilkanaście lat temu działalność biznesową w Londynie skupiłem się na usługach transportowych, bo ten rynek znałem najlepiej. Zaprocentował o doświadczenie z Polski i angielskiej firmy transportowej, w której pracowałem po przyjeździe do Anglii. Ilość Polaków na Wyspach rosła systematycznie i wzrastał popyt na transport ludzi. Firma szybko się rozwijała.  Read the rest of this entry »

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Rekordowe finanse polskich klubów piłkarskich – Raport EY i Ekstraklasy S.A.

Raport EY i Ekstraklasy 2017-08-31 cover

Raport EY i Ekstraklasy S.A.: Rekordowy sezon dla finansów polskich klubów piłkarskich – najwyższe w historii przychody, napędzane przez transfery i Ligę Mistrzów

Ponad 700 milionów PLN przychodów, pierwszy w historii ligi dodatni wynik finansowy netto 16 klubów Ekstraklasy – 66 mln PLN, najwyższe wpływy z transferów – 117 mln PLN i rekordowe z praw mediowych – 260 mln PLN. Firma doradcza EY i spółka Ekstraklasa S.A. raportem „Ekstraklasa Piłkarskiego Biznesu” podsumowały sezon piłkarski 2016/2017 – sezon rekordów finansowych i sportowych. Zwycięzcą przygotowywanego od 9 lat rankingu biznesowego okazał się ubiegłoroczny Mistrz Polski – zespół Legii Warszawa, którego przychody wzrosły o 151 mln PLN, osiągając wysokość 281 mln PLN, co stanowiło 40% przychodów całej ligi. Drugie miejsce w rankingu EY i Ekstraklasy S.A. zajął Lech Poznań, na trzeciej pozycji uplasowała się Lechia Gdańsk. Po raz pierwszy w historii raport został opracowany na podstawie danych finansowych dotyczących sezonu ligowego, zamiast roku kalendarzowego. Read the rest of this entry »

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Mastering Complexity Through Simplification: Four Steps to Creating Competitive Advantage

BCG 2017-02 Mastering-Complexity 4 steps Ex 1

Businesses compete in a world that is growing ever more complex. Disruptive technologies emerge with increasing frequency. Customers’ needs and demands change at breakneck speed. New competitors are always entering the fray. Read the rest of this entry »