McKinsey and Cohere Collaborate to Transform Clients with Enterprise Generative AI

At the McKinsey Blog

McKinsey and Cohere collaborate to transform clients with enterprise generative AI

AI & Analytics

July 18, 2023Today, McKinsey announced a strategic collaboration with Cohere, the leading developer of enterprise AI platforms and state-of-the-art large language models (LLMs). McKinsey and Cohere will harness the power of generative AI—the ability of machines to create and use human language—to drive clients’ business performance through tailored end-to-end solutions. The collaboration will be led by QuantumBlack, AI by McKinsey, the firm’s industry-leading AI arm, with thousands of practitioners including data engineers, data scientists, product managers, designers, and software engineers.

Inside the McKinsey and Cohere collaboration.

McKinsey and Cohere will help organizations integrate generative AI into their operations, redefine business processes, train and upskill workforces, and use this emerging technology to tackle some of the toughest current challenges.

“Every client context, use case, and organization is unique, but they are all looking for the right generative AI solution tailored for their needs to address privacy, IP protection, and cost,” says Ben Ellencweig, a McKinsey senior partner and global leader of alliances and acquisitions for QuantumBlack. “Together with Cohere, we are excited to launch secure, enterprise-grade generative AI solutions for our clients, moving from discussing productivity and growth opportunities to capturing value on the ground, day to day.”

McKinsey and Cohere collaborate to transform clients with enterprise generative AI

From left, Aidan Gomez, cofounder and CEO of Cohere; Ben Ellencweig, McKinsey senior partner and global leader of alliances and acquisitions for QuantumBlack; Martin Kon, president and COO of Cohere

McKinsey and Cohere collaborate to transform clients with enterprise generative AI

With headquarters in San Francisco and Toronto, and a key research center in London, Cohere employs hundreds of experts, including AI machine learning, and software engineers, as well as data scientists and researchers who have made formative contributions to the development of generative AI. Cofounded by Aidan Gomez, a Google Brain alum and coauthor of the seminal transformer research paper, Cohere describes itself as being “on a mission to transform enterprises and their products with AI to unlock a more intuitive way to generate, search, and summarize information than ever before.” One key element of Cohere’s approach is its focus on data protection, deploying its models inside enterprises’ secure data environment. .... '

Economic Potential of AI

 From McKinsey: The economic potential of generative AI: The next productivity frontier

The economic potential of generative AI: The next productivity frontier

Generative AI’s impact on productivity could add trillions of dollars in value to the global economy—and the era is just beginning.

Sent from McKinsey Insights, available in the App Store and Play Store. ... '

The Economic Potential of Generative AI: The next Productivity Frontier

McKinsey takes an always useful look at the future of technology I follow

The economic potential of generative AI: The next productivity frontier   by Mckinsey

June 14, 2023 | Report

Generative AI is poised to unleash the next wave of productivity. We take a first look at where business value could accrue and the potential impacts on the workforce.

Special Report

The economic potential of generative AI: The next productivity frontier

Full Report (68 pages)

AI has permeated our lives incrementally, through everything from the tech powering our smartphones to autonomous-driving features on cars to the tools retailers use to surprise and delight consumers. As a result, its progress has been almost imperceptible. Clear milestones, such as when AlphaGo, an AI-based program developed by DeepMind, defeated a world champion Go player in 2016, were celebrated but then quickly faded from the public’s consciousness.

Generative AI applications such as ChatGPT, GitHub Copilot, Stable Diffusion, and others have captured the imagination of people around the world in a way AlphaGo did not, thanks to their broad utility—almost anyone can use them to communicate and create—and preternatural ability to have a conversation with a user. The latest generative AI applications can perform a range of routine tasks, such as the reorganization and classification of data. But it is their ability to write text, compose music, and create digital art that has garnered headlines and persuaded consumers and households to experiment on their own. As a result, a broader set of stakeholders are grappling with generative AI’s impact on business and society but without much context to help them make sense of it.

The speed at which generative AI technology is developing isn’t making this task any easier. ChatGPT was released in November 2022. Four months later, OpenAI released a new large language model, or LLM, called GPT-4 with markedly improved capabilities.1 Similarly, by May 2023, Anthropic’s generative AI, Claude, was able to process 100,000 tokens of text, equal to about 75,000 words in a minute—the length of the average novel—compared with roughly 9,000 tokens when it was introduced in March 2023.2 And in May 2023, Google announced several new features powered by generative AI, including Search Generative Experience and a new LLM called PaLM 2 that will power its Bard chatbot, among other Google products.3  ... '  (much more) 

Generative AI Could Add $4.4 Trillion a Year to the Global Economy, McKinsey Finds

 Generative AI Could Add $4.4 Trillion a Year to the Global Economy, McKinsey Finds

Vanessa Bates Ramirez in SigularityHub

There’s been concern about artificial intelligence taking away jobs for years, and with the recent boom in generative AI, those fears have grown. The ability to generate realistic and accurate text, images, or audio based on a prompt could make plenty of jobs obsolete (including, ahem, journalism and writing). But a new study says the doomsday predictions are misguided, because generative AI is far more likely to do just the opposite of canceling out jobs.

Last week, McKinsey published a report called The Economic Potential of Generative AI: The Next Productivity Frontier. It’s the result of a study involving 850 different job roles and 2,100 tasks across occupations in 47 countries. Researchers considered what portion of each existing job or task can be taken over by generative AI, as well as new occupations and responsibilities likely to be created by the technology. Their conclusion? Generative AI has the potential to create up to $4.4 trillion worth of annual value in the global economy.

$4.4 trillion is the high end of a range, with the lower bound sitting at $2.6 trillion. Even if the value created were to fall on the low end, it would still approximate the GDP of the United Kingdom, which was $3.1 trillion in 2021.  ... ' 

McKinsey’s A.I. Chief Discusses ChatGPT’s Impact on Consulting Jobs

Job impact seen.

McKinsey’s A.I. Chief Discusses ChatGPT’s Impact on Consulting Jobs

McKinsey's A.I. chief Alex Singla: 'Problem-solving, creativity and change management' aren't replaced by technology.

By Sissi Cao • 06/07/23 1:36pm

Artificial intelligence is taking human jobs. Just last month, A.I. eliminated about 4,000 jobs in the U.S., according to a June 1 report by Challenger, Gray & Christmas. As the generative A.I. phenomenon spreads, it is only a matter of time before the technology replaces management consultants, the archetypal white-collar job of data analysis, information summarizing and PowerPoint-making. The things that A.I. tools like ChatGPT can do.

Large consulting firms are embracing the technology and adjusting their expectations for talent in the post-ChatGPT era. At McKinsey & Company, one of the world’s largest management consulting firms, about half of its 30,000 employees now use ChatGPT or similar tools in their work, said Ben Ellencweig, a senior partner at McKinsey, at a company event yesterday (June 6) in New York.

Generative A.I. is drastically changing the day-to-day activities of management consultants, especially at the entry-level. At McKinsey, a junior consultant’s first day typically entails what the firm calls “know,” or reading pages and pages of non-confidential information to learn about a certain industry or sector the firm serves.

“When I started at the firm, I’d spend an entire weekend just getting swamped reading document after document. Now A.I. models can synthesize the 10 key things you need to know within minutes. That’s a major, major shift,” Alex Singla, a senior partner at McKinsey and the global leader of QuantumBlack, the firm’s A.I. consulting branch, told Observer in an interview at yesterday’s event. Singla has been with the firm since 2000. He currently oversees more than 1,300 analytics experts across McKinsey under the QuantumBlack umbrella. ... .'    (read more at the link)

AI Being Used

Its here, AI being being used by McKinsey

 McKinsey says ‘about half’ of its employees are using generative AI   By Carl Franzen @carlfranzen,  June 6, 2023 9:45 AM

Join top executives in San Francisco on July 11-12, to hear how leaders are integrating and optimizing AI investments for success. Learn More

McKinsey and Company, the global consulting firm with more than 30,000 employees in 67 countries, is embracing new generative AI tools in a major way: Nearly 50% of the firm’s workforce is using ChatGPT and similar technology.

“About half of [our employees] are using those services with McKinsey’s permission,” said Ben Ellencweig, senior partner and global leader of QuantumBlack, the firm’s artificial intelligence consulting arm, during a media event at McKinsey’s New York Experience Studio on Tuesday.

Ellencweig emphasized that McKinsey had guardrails for employees using generative AI, including “guidelines and principles” about what information the workers could input into these services. ...'

Exploring Opportunities in the Generative AI Value Chain

 Just gave a university talk on my work in this area, just reading this. Below just an intro.  Read the whole thing.

Exploring opportunities in the generative AI value chain

This article is a collaborative effort by Tobias Härlin, Gardar Björnsson Rova, Alex Singla, Oleg Sokolov, and Alex Sukharevsky, representing views from McKinsey Digital.

April 26, 2023 | Article

Generative AI is giving rise to an entire ecosystem, from hardware providers to application builders, that will help bring its potential for business to fruition.

Over the course of 2022 and early 2023, tech innovators unleashed generative AI en masse, dazzling business leaders, investors, and society at large with the technology’s ability to create entirely new and seemingly human-made text and images.

The response was unprecedented.

In just five days, one million users flocked to ChatGPT, OpenAI’s generative AI language model that creates original content in response to user prompts. It took Apple more than two months to reach the same level of adoption for its iPhone. Facebook had to wait ten months and Netflix more than three years to build the same user base.

And ChatGPT isn’t alone in the generative AI industry. Stability AI’s Stable Diffusion, which can generate images based on text descriptions, garnered more than 30,000 stars on GitHub within 90 days of its release—eight times faster than any previous package.1

This flurry of excitement isn’t just organizations kicking the tires. Generative AI use cases are already taking flight across industries. Financial services giant Morgan Stanley is testing the technology to help its financial advisers better leverage insights from the firm’s more than 100,000 research reports.2 The government of Iceland has partnered with OpenAI in its efforts to preserve the endangered Icelandic language.3 Salesforce has integrated the technology into its popular customer-relationship-management (CRM) platform.4   .... ' 

How to Ace Collaborative Problem Solving.

Often played with this problem.  Built complex and expensive methods  to address. Some good thoughts here.

How to Ace Collaborative Problem Solving. in McKinsey,   Podcast

April 30, 2023They say two heads are better than one, but is that true when it comes to solving problems in the workplace? To solve any problem—whether personal (eg, deciding where to live), business-related (eg, raising product prices), or societal (eg, reversing the obesity epidemic)—it’s crucial to first define the problem. In a team setting, that translates to establishing a collective understanding of the problem, awareness of context, and alignment of stakeholders. “Both good strategy and good problem solving involve getting clarity about the problem at hand, being able to disaggregate it in some way, and setting priorities,” Rob McLean, McKinsey director emeritus, told McKinsey senior partner Chris Bradley in an Inside the Strategy Room podcast episode. Check out these insights to uncover how your team can come up with the best solutions for the most complex challenges by adopting a methodical and collaborative approach. .. 

On the Age of AI

 Interview on the Age of  AI

Author Talks: In the ‘age of AI,’ what does it mean to be smart?  in McKinsey

March 16, 2023 | Interview

As artificial intelligence gets better at predicting human behavior, a business psychologist encourages people to strengthen the uniquely human skills that machine learning has yet to tap.

McKinsey Global Private Markets Review 2023: Private markets turn down the volume

In this edition of Author Talks, McKinsey Global Publishing’s Raju Narisetti chats with Tomas Chamorro-Premuzic about his new book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique (Harvard Business Review Press, February 2023). Chamorro-Premuzic explains why some AI algorithms model humanity as a simple species, how attention has become commoditized, and why the right questions are now more valuable than the right answers. An edited version of the conversation follows.

Why did you write this, your 12th book, now?

I’m a professor of business psychology at Columbia University and UCL [University College London] and the chief innovation officer at ManpowerGroup. I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique is a book about the behavioral consequences or impact of artificial intelligence, including the dark side of human behavior and what we should do to upgrade ourselves as a species.

The book is written at a time that, in my view, could only be described as the AI age. Humans have always relied on technological inventiveness and innovation to shape their cultural and social evolution, and I think there can be very little doubt that the definitive technology of today is artificial intelligence, or AI.

Now, even the wider public is talking about things like ChatGPT and other conversational interfaces, and the tech giants are described mostly as data companies and as algorithmic prediction businesses.

The book was very much written in the midst of the AI age, or under the influence of AI, because I wrote the bulk of this at the height of the pandemic when we had very little physical interaction or contact with other people outside of our nuclear families. This means I was heavily influenced by hyperconnectedness and the datafication of me. Everything I did was being datafied and subjected to the predictive powers of AI during 2020 and 2021.

I can’t say that there won’t be a better era to read the book, but it certainly wouldn’t have had the same connotation and impact if we had published it five or ten years ago.

Haven’t humans always blamed technology for every problem they face?

There is a common tendency for people to overreact to things that are novel, whether in a good way or in a bad way, and technologies are a very good example of this.

Perhaps the best example is how, when the written newspaper first scaled up and productized, people feared that humans would never meet in person ever again because there would be no information or even gossip to exchange if all the news was in written form. Also, from the 1950s onward, people showed concern that television would lead to less intellectual activities, but I don’t think they were wrong because reading habits went down since mass TV was introduced.

What I tried to do with this book is not be at one extreme or the other. What’s important to me is to not miss the opportunity to highlight the behavioral impact and consequences that we have already seen artificial intelligence have on us. This is not a book about AI, but about humans in the AI age.

Although a lot of what I highlight is about the dark side of behaviors that AI has unleashed, there are also some great opportunities that have had very positive effects on us—on both an individual and collective level.

What is the ‘crisis of distractibility’?  ( Edited at Authors Request,  read more at link)  

Book: In the Age of AI, 'What Does it Mean to be Smart?'

 Here an intro to McKinsey's 'Author Talks', which interviews Tomas Chamorro-Premuzic on his new book on AI and Automation.   Plan to Read it. 

Author Talks: In the ‘age of AI,’ what does it mean to be smart?

March 16, 2023 | Interview

As artificial intelligence gets better at predicting human behavior, a business psychologist encourages people to strengthen the uniquely human skills that machine learning has yet to tap.

In this edition of Author Talks, McKinsey Global Publishing’s Raju Narisetti chats with Tomas Chamorro-Premuzic about his new book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique (Harvard Business Review Press, February 2023). Chamorro-Premuzic explains why some AI algorithms model humanity as a simple species, how attention has become commoditized, and why the right questions are now more valuable than the right answers. An edited version of the conversation follows.

Why did you write this, your 12th book, now?

I’m a professor of business psychology at Columbia University and UCL [University College London] and the chief innovation officer at ManpowerGroup. I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique is a book about the behavioral consequences or impact of artificial intelligence, including the dark side of human behavior and what we should do to upgrade ourselves as a species.

The book is written at a time that, in my view, could only be described as the AI age. Humans have always relied on technological inventiveness and innovation to shape their cultural and social evolution, and I think there can be very little doubt that the definitive technology of today is artificial intelligence, or AI.

Now, even the wider public is talking about things like ChatGPT and other conversational interfaces, and the tech giants are described mostly as data companies and as algorithmic prediction businesses.

The book was very much written in the midst of the AI age, or under the influence of AI, because I wrote the bulk of this at the height of the pandemic when we had very little physical interaction or contact with other people outside of our nuclear families. This means I was heavily influenced by hyperconnectedness and the datafication of me. Everything I did was being datafied and subjected to the predictive powers of AI during 2020 and 2021.

I can’t say that there won’t be a better era to read the book, but it certainly wouldn’t have had the same connotation and impact if we had published it five or ten years ago.

Haven’t humans always blamed technology for every problem they face?

There is a common tendency for people to overreact to things that are novel, whether in a good way or in a bad way, and technologies are a very good example of this.

Perhaps the best example is how, when the written newspaper first scaled up and productized, people feared that humans would never meet in person ever again because there would be no information or even gossip to exchange if all the news was in written form. Also, from the 1950s onward, people showed concern that television would lead to less intellectual activities, but I don’t think they were wrong because reading habits went down since mass TV was introduced.

What I tried to do with this book is not be at one extreme or the other. What’s important to me is to not miss the opportunity to highlight the behavioral impact and consequences that we have already seen artificial intelligence have on us. This is not a book about AI, but about humans in the AI age.  .. .. ' 

What Does it Mean to be Smart in an Age of AI

Excerpt from McKinsey  Complete video at the link.

Author Talks: In the ‘age of AI,’ what does it mean to be smart?

March 16, 2023 | Interview

As artificial intelligence gets better at predicting human behavior, a business psychologist encourages people to strengthen the uniquely human skills that machine learning has yet to tap.

In this edition of Author Talks, McKinsey Global Publishing’s Raju Narisetti chats with Tomas Chamorro-Premuzic about his new book, I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique (Harvard Business Review Press, February 2023). Chamorro-Premuzic explains why some AI algorithms model humanity as a simple species, how attention has become commoditized, and why the right questions are now more valuable than the right answers. An edited version of the conversation follows.

Why did you write this, your 12th book, now?

An unanticipated problem was encountered, check back soon and try again

Video

I’m a professor of business psychology at Columbia University and UCL [University College London] and the chief innovation officer at ManpowerGroup. I, Human: AI, Automation, and the Quest to Reclaim What Makes Us Unique is a book about the behavioral consequences or impact of artificial intelligence, including the dark side of human behavior and what we should do to upgrade ourselves as a species.

The book is written at a time that, in my view, could only be described as the AI age. Humans have always relied on technological inventiveness and innovation to shape their cultural and social evolution, and I think there can be very little doubt that the definitive technology of today is artificial intelligence, or AI.

Now, even the wider public is talking about things like ChatGPT and other conversational interfaces, and the tech giants are described mostly as data companies and as algorithmic prediction businesses.

The book was very much written in the midst of the AI age, or under the influence of AI, because I wrote the bulk of this at the height of the pandemic when we had very little physical interaction or contact with other people outside of our nuclear families. This means I was heavily influenced by hyperconnectedness and the datafication of me. Everything I did was being datafied and subjected to the predictive powers of AI during 2020 and 2021.

I can’t say that there won’t be a better era to read the book, but it certainly wouldn’t have had the same connotation and impact if we had published it five or ten years ago.

Haven’t humans always blamed technology for every problem they face?

There is a common tendency for people to overreact to things that are novel, whether in a good way or in a bad way, and technologies are a very good example of this.

Perhaps the best example is how, when the written newspaper first scaled up and productized, people feared that humans would never meet in person ever again because there would be no information or even gossip to exchange if all the news was in written form. Also, from the 1950s onward, people showed concern that television would lead to less intellectual activities, but I don’t think they were wrong because reading habits went down since mass TV was introduced.

What I tried to do with this book is not be at one extreme or the other. What’s important to me is to not miss the opportunity to highlight the behavioral impact and consequences that we have already seen artificial intelligence have on us. This is not a book about AI, but about humans in the AI age.  ... ' 

EU Digital Strategy

 So many directions to regulate.    Note considering the influence US Law

The EU digital strategy: The impact of data privacy on global business

McKinseu:  March 1, 2023 | Commentary

By  Daniel Mikkelsen, Sebastian Scheurle,   Henning Soller , and Malin Strandell-Jansson

New data regulations from the European Union require organizational attention, and three key steps can help navigate the data privacy landscape.

The data regulations in the European Union (EU) have recently received significant attention specifically due to the advent of the General Data Protection Regulation and the rulings around Schrems II—whereby the Court of Justice of the European Union found that the protection of personal data had limitations due to domestic law in the United States—as well as the access and use by US public authorities of personal data transferred from the EU, and recent developments such as e-privacy.

While these developments have led to major changes in data privacy, one of the other goals of the regulation—to establish a market for data and facilitate data exchange between companies—has not been reached to date.

This lack of action has led to the potential for further regulatory activity to define an agenda for how to uplift the data capabilities of European companies, create a market for data, and regulate activities around AI. These activities are typically summarized as the EU digital strategy. While regulation adds further requirements and obligations to any data-enabled business, it also creates an opportunity for competitive advantages for those that best derisk their data transformations.

The EU digital strategy offers organizations both challenges and opportunities, but these regulations will likely continue to evolve, so organizations should remain aligned with the regulatory process. ... ' 

A CEO’s guide to the Metaverse

 Fairly general overview

McKinsey Quarterly

A CEO’s guide to the metaverse

January 24, 2023 | Article  By  Homayoun Hatami, Eric Hazan, Hamza Khan,   and Kim Rants

It’s too big to ignore—yet its future is far from certain. Companies need to dip a toe in the water and plan to take the plunge should developments warrant.

Suddenly, the metaverse is in the zeitgeist, for better or worse. Investment more than doubled in 2022 powered by big moves (such as Microsoft’s $69 billion acquisition of Activision Blizzard, now under antitrust review) and small ones (about $12 billion to $14 billion of venture capital and private equity investment). Everyone has heard about the successes racked up by some big gaming companies: Roblox reported more than 58 million daily active users in 2022,1 while Fortnite had more than 20 million in 2020 and generated more than $9 billion in sales between 2018 and 2019.2 And others are investing; Meta continues to spend at least $10 billion annually on metaverse development. Yet investors are asking questions of metaverse companies about when they can expect tangible, near-term results from these companies’ investments.3

How should CEOs view the metaverse? Is it a big opportunity or a big risk? Our answer: the opportunity is enormous—and the risk is not what you think it is. The companies that are building the metaverse see it as the next iteration of the internet (see this McKinsey Explainer for more). And as with any technology so vast and all-encompassing (it’s similar to AI in its scope), the potential is enormous. We estimate that the metaverse could generate $4 trillion to $5 trillion in value by 2030; see our report for all the details.

On the other hand, there are clear risks. Don’t be distracted by the debacles in crypto and nonfungible tokens (NFTs); those are Web3 technologies that are related but not exactly the same as the metaverse. Rather, the biggest risk is missing the wave of change that breakthrough technologies such as the original internet, AI, and the metaverse can unleash. In our April 2022 survey, some 95 percent of business leaders expect the metaverse to have a positive impact on their industry within five to ten years, and 61 percent expect it to change the way their industry operates.

In this article, we’ll briefly summarize the reasons for optimism and the factors that suggest the metaverse is truly a CEO issue. We’ll also look at the significant obstacles that will have to be overcome if the metaverse is to realize its full potential. We’ll conclude with a suggestion of three steps that CEOs in several sectors—both consumer and enterprise—could consider to make sure the metaverse train, if and when it gets going, does not leave the station without them.

The case for optimism

When we estimated the market value of metaverse activity in June 2022, we calculated that it was between $200 billion and $300 billion. It’s larger now, and in eight years or so, it could be $4 trillion to $5 trillion (exhibit), which is roughly the size of Japan’s economy, the third largest in the world. Exponential growth is possible because of an alignment of several forces: the metaverse’s appeal spans genders, geographies, and generations; consumers have already shown they are ready to spend on metaverse assets; they are open to adopting new technologies; companies are investing heavily in the required infrastructure; and brands experimenting in the metaverse are finding that customers are delighted. ... ' 

AI in Strategy Podcast

Thoughtful piece here, full podcast below

Artificial intelligence in strategy

McKinsey,  January 11, 2023 | Podcast, By , Yuval Atsmon

AI tools can help executives avoid biases in decisions, pull insights out of oceans of data, and make strategic choices more quickly. And that’s just the beginning.

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform.

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?  ... ' 

Unlocking the Industrial Potential of Robotics and Automation

 From McKinsey Global Robotics Survey.

Unlocking the industrial potential of robotics and automation

January 6, 2023 | Article   in McKinsey

Results from the 2022 McKinsey Global Industrial Robotics Survey reveal that industrial companies are set to spend heavily on robotics and automation. However, many will need help to complete the journey.

Across the industrial world, companies are betting big on robotics and automation. For many, automated systems will account for 25 percent of capital spending over the next five years, results from the 2022 McKinsey Global Industrial Robotics Survey show.1 Industrial-company executives expect to see benefits in output quality, efficiency, and uptime. However, many remain wary of the challenge, with the cost of hardware and a lack of internal experience at the top of their list of concerns.

About the authors:  

Femi Ajewole is a consultant in McKinsey’s New York office; Ani Kelkar is an associate partner in the Houston office; Dylan Moore is a consultant in the Bay Area office, where Emily Shao is a partner; and Manju Thirtha is a consultant in the Dallas office ..... 

Among the industrial sectors surveyed, the biggest spender on automation over the next five years is set to be retail and consumer goods, with 23 percent of respondents from that sector planning to spent more than $500 million (Exhibit 1). That compares with 15 percent in food and beverage and 8 percent in automotive. For logistics and fulfillment players, automation will represent 30 percent or more of their capital spending in the next five years—the highest share among industrial segments surveyed. .... ' 

McKinsey on ChatGPT

McKinsey comments on this, with more at the link.  I say we are about to get a big new flow of such products, and will have to quickly adapt. 

Generative AI is here: How tools like ChatGPT could change your business

December 20, 2022 | Commentary

By  Michael Chui  ,  Roger Roberts , and  Lareina Yee

Generative AI and other foundation models are changing the AI game, taking assistive technology to a new level, reducing application development time, and bringing powerful capabilities to nontechnical users.

In the spirit of this article’s topic, we asked ChatGPT—a generative AI language model that can create original content in response to a user prompt—how it would set the context. Our prompt to the system:

Write the opening paragraph for an article about how transformative generative AI will be for business, in the style of McKinsey & Company.

ChatGPT’s response:

The rise of generative AI has the potential to be a major game-changer for businesses. This technology, which allows for the creation of original content by learning from existing data, has the power to revolutionize industries and transform the way companies operate. By enabling the automation of many tasks that were previously done by humans, generative AI has the potential to increase efficiency and productivity, reduce costs, and open up new opportunities for growth. As such, businesses that are able to effectively leverage the technology are likely to gain a significant competitive advantage.

Not perfect but overwhelmingly impressive.

For us and many executives we’ve spoken to recently, entering one prompt into ChatGPT, developed by OpenAI, was all it took to see the power of generative AI. In the first five days of its release, more than a million users logged into the platform to experience it for themselves. OpenAI’s servers can barely keep up with demand, regularly flashing a message that users need to return later when server capacity frees up.

Products like ChatGPT and GitHub Copilot, as well as the underlying AI models that power such systems (Stable Diffusion, DALL·E 2, GPT-3, to name a few), are taking technology into realms once thought to be reserved for humans. With generative AI, computers can now arguably exhibit creativity. They can produce original content in response to queries, drawing from data they’ve ingested and interactions with users. They can develop blogs, sketch package designs, write computer code, or even theorize on the reason for a production error.

This latest class of generative AI systems has emerged from foundation models—large-scale, deep learning models trained on massive, broad, unstructured data sets (such as text and images) that cover many topics. Developers can adapt the models for a wide range of use cases, with little fine-tuning required for each task. For example, GPT-3.5, the foundation model underlying ChatGPT, has also been used to translate text, and scientists used an earlier version of GPT to create novel protein sequences. In this way, the power of these capabilities is accessible to all, including developers who lack specialized machine learning skills and, in some cases, people with no technical background. Using foundation models can also reduce the time for developing new AI applications to a level rarely possible before.   ;;;' 

Every Company Uses Software, but are they a Software Company?

Even more so now that we have things like ChatGPT,   but we still need to understand increasingly deeper context when using the algorithms involved.   Caution is needed all around.  

Every company is a software company: Six ‘must dos’ to succeed

December 13, 2022 | Article  in McKinsey    By  Chandra Gnanasambandam, Janaki Palaniappan, and Jeremy Schneider

As software transforms every industry, leaders must turn to a new playbook.

Marc Andreessen’s observation from more than ten years ago that “software is eating the world”1 needs an update: software is the world. The software industry continues to grow at a massive clip. More and more traditional companies are realizing that to compete and grow in a digital world, they must look, think, and act like software companies themselves.

Per McKinsey research from June 2022, nearly 70 percent of the top economic performers, compared with just half of their peers, are using their own software to differentiate themselves from their competitors.2 Fully one-third of those top performers monetize software directly.

The pressure to evolve is building thanks to three fundamental shifts. First, the accelerated adoption of digital products is driving an effort to embed software in the product and purchase experience through everything from personalization to seamless omnichannel delivery. Second, more of the value in more products and services from more industries is coming from software. For example, the average industrial company expects its share of revenue from software to double over the next three years. Finally, the growth of cloud computing, platform as a service, low- and no-code tools, and AI-based programming assistance are putting unprecedented power into the hands of billions of workers.

Yet while companies might already accept the importance of software (research shows that nearly two-thirds of companies have invested in software as a service or modern commercial software), they still tend to look at software as a capability that they can bolt onto their existing business. That just doesn’t work. Becoming a software business requires foundational change with different skill sets, practices, leadership, and organizational structures.

Three ‘switch to software’ models

It is hard to become a software company—less than 7 percent of all software revenue in the world accrues to nontech companies.3 But models for successful transformation do exist (see sidebar, “Three ‘switch to software’ models”). To understand what works, we analyzed more than 20 software transformations and spoke with a dozen senior executives who have led successful software transitions. The result: six principles that are at the core of any successful effort to become a software company.  ... 

Social Commerce: The f\Buture of How Consumers Interact with Brands

 McKinsey: Social commerce: The Future of how Consumers Interact with Brands

Authors:

  Camilo Becdach is a partner in McKinsey’s Southern California office, where Zachary Kubetz is a consultant; Marc Brodherson is a senior partner in the New York office, where James Nakajima is a consultant; Alex Gersovitz is a consultant in the Bay Area office; Daniel Glaser is a partner in the Munich office; and Max Magni is a senior partner in the New Jersey office.

October 19, 2022 | Article

Browsing and shopping directly on social media platforms is a core feature of e-commerce in China. Now, this dynamic new way of buying is poised for rapid growth in the United States.

A two-hour live shopping event on TikTok brings in more than a week’s worth of sales at a flagship store.1 An interactive, shoppable Instagram live stream garners 40,000 comments. Augmented-reality (AR) lenses let Snapchat users “try on” makeup and send the images to friends.

Welcome to the dynamic world of social commerce, where consumers explore products and complete transactions through social media and content creation platforms, all in an app. This emerging form of shopping removes friction from the buying process, creates a more engaging journey for the consumer, and presents new opportunities for brands to generate consumer interest.

Already enormously popular in markets such as China, social commerce remains a small but rapidly growing segment in the United States (Exhibit 1). In 2021, $37 billion in goods and services were purchased through social-commerce channels.2

Exhibit 1

Social commerce is a small but rapidly growing segment in the United States.

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By 2025, that figure is expected to swell to nearly $80 billion, or 5 percent of total US e-commerce.3 Globally, the social-commerce market is expected to grow to more than $2 trillion by 2025.4

Discover NeXT Commerce

Social commerce is more than just a new shopping experience. It represents a paradigm shift in how consumers interact with brands: where, when, and how they shop. For consumer brands, this creates opportunities for a much more interactive, entertaining, and experiential journey (see sidebar, “Discover NeXT Commerce”). For example, leading brands are working with platforms such as TikTok to forge new relationships with consumers, shifting from traditional advertising strategies to fun, engaging content that is less overtly promotional. This content can be used to highlight unique product features or explain product complexities simply. For example, rather than watching an ad for a new skin-care formula, your favorite celebrity can invite you behind the scenes into their daily skin-care routine, showing you how they use the branded product and why they love it. Consumers can then buy the product directly within the platform, whether it’s on Instagram or TikTok or through YouTube Shopping.

The winning ingredients for social commerce in China

The evolution of social commerce in China offers a glimpse of the possibilities.5 By forging partnerships with wildly popular social influencers and participating in live-stream shopping—an experience that combines instant purchasing of a featured product and audience participation through chat or reaction buttons—brands in China have achieved conversion rates of almost 30 percent on social platforms.6 This is up to ten times higher than conversion in conventional e-commerce. Last year, goods and services purchased through live-stream shopping in China represented $132 billion, or 5 percent of total e-commerce gross merchandise value (GMV).7 More broadly, Chinese consumers spent more than double that amount—$352 billion (or 13 percent of total e-commerce)—on all social commerce. ... .' 

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Mckinsey: The Path to Next Normal

Not sure I buy this, but an attempt, and then depends so much on WHAT is being done, expected:

Charting the path to the next normal

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