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.  ... ' 

Value Creation

Good piece.   Take care to carefully measure the value.

The Value of Value creation
By Marc Goedhart and Tim Koller, McKinsey Quarterly  ( link to PDF)

Challenges such as globalization, climate change, income inequality, and the growing power of technology titans have shaken public confidence in large corporations. In an annual Gallup poll, more than one in three of those surveyed express little or no confidence in big business—seven percentage points worse than two decades ago.1 Politicians and commentators push for more regulation and fundamental changes in corporate governance. Some have gone so far as to argue that “capitalism is destroying the earth.”2

This is hardly the first time that the system in which value creation takes place has come under fire. At the turn of the 20th century in the United States, fears about the growing power of business combinations raised questions that led to more rigorous enforcement of antitrust laws. The Great Depression of the 1930s was another such moment, when prolonged unemployment undermined confidence in the ability of the capitalist system to mobilize resources, leading to a range of new policies in democracies around the world.

Today’s critique includes a call on companies to include a broader set of stakeholders in their decision making, beyond just their shareholders. It’s a view that has long been influential in continental Europe, where it is frequently embedded in corporate-governance structures. The approach is gaining traction in the United States, as well, with the emergence of public-benefit corporations, which explicitly empower directors to take into account the interests of constituencies other than shareholders. .... ' 

Data Valuation Perspectives

Have had several journeys into the valuation of data and its treatment as an asset (or liability).  Another article on the topic has come up in The Berkeley Artificial Intelligence Research Blog that is worth looking at, in particular from a machine learning perspective.   Technical but of value to look at.    What is My Data Worth? –  in Berkeley AI Blog   By Ruoxi Jia 

Data as Value Asset

Have now addressed this problem for some time,  its how the data gets used, including the risk of its use in context.

Managing data as an asset: An interview with the CEO of Informatica  in McKinsey

Anil Chakravarthy draws on his experience leading a data-management business to discuss new technical and organizational approaches that help companies create value with data. .... " 

When does Blockchain get the Simplest Value?

Thought of this myself.    When first hearing first about blockchain.  Isn't there a simpler way to do the same thing?  You know, with a suitably encrypted and protected database?  But doing what?  What are the specific goals you are trying to achieve. Each goal.  Better, faster, cheaper?   Or at all.  Without all the hashing, mining, hacking and coinage.  Yes, we want value, the best way.  Thoughtful piece:

Blockchain’s Occam problem

By Matt Higginson, Marie-Claude Nadeau, and Kausik Rajgopal   in McKinsey

Blockchain has yet to become the game-changer some expected. A key to finding the value is to apply the technology only when it is the simplest solution available.

Blockchain over recent years has been extolled as a revolution in business technology. In the nine years since its launch, companies, regulators, and financial technologists have spent countless hours exploring its potential. The resulting innovations have started to reshape business processes, particularly in accounting and transactions.

Amid intense experimentation, industries from financial services to healthcare and the arts have identified more than 100 blockchain use cases. These range from new land registries, to KYC applications and smart contracts that enable actions from product processing to share trading. The most impressive results have seen blockchains used to store information, cut out intermediaries, and enable greater coordination between companies, for example in relation to data standards.

One sign of blockchain’s perceived potential is the large investments being made. Venture-capital funding for blockchain startups reached $1 billion in 2017. IBM has invested more than $200 million in a blockchain-powered data-sharing solution for the Internet of Things, and Google has reportedly been working with blockchains since 2016. The financial industry spends around $1.7 billion annually on experimentation.

There is a clear sense that blockchain is a potential game-changer. However, there are also emerging doubts. A particular concern, given the amount of money and time spent, is that little of substance has been achieved. Of the many use cases, a large number are still at the idea stage, while others are in development but with no output. The bottom line is that despite billions of dollars of investment, and nearly as many headlines, evidence for a practical scalable use for blockchain is thin on the ground.   ...... " 

Business Value of Design

Useful piece and Podcast by McKinsey, link to business value.

The business value of design
By Benedict Sheppard, Hugo Sarrazin, Garen Kouyoumjian, and Fabricio Dore in McKinsey

How do the best design performers increase their revenues and shareholder returns at nearly twice the rate of their industry counterparts?

We all know examples of bad product and service design. The USB plug (always lucky on the third try). The experience of rushing to make your connecting flight at many airports. The exhaust port on the Death Star in Star Wars.

 Podcast:
The business value of design
We also all know iconic designs, such as the Swiss Army Knife, the humble Google home page, or the Disneyland visitor experience. All of these are constant reminders of the way strong design can be at the heart of both disruptive and sustained commercial success in physical, service, and digital settings.

Despite the obvious commercial benefits of designing great products and services, consistently realizing this goal is notoriously hard—and getting harder. Only the very best designs now stand out from the crowd, given the rapid rise in consumer expectations driven by the likes of Amazon; instant access to global information and reviews; and the blurring of lines between hardware, software, and services. Companies need stronger design capabilities than ever before.  .... " 

VDMbee a Value Management Platform

Some time ago I wrote about VDML, the Value Delivery Modeling Language.   Just today got a note from  Theodoor Von Donge  about how they are using and extending it.  Below I bought his comment to the top, so its gets more exposure.  Like to think about ways we can more directly link modeling directly to business value.  Here is an example.  Any thoughts on this?    Will be exploring, be glad to collaborate on exploration ...

Hello Franz,   From: Theodoor Von Donge:

Great to see your blog post. As VDMbee we are building our Value Management Platform based on the VDML specification. Are are also actively involved in the OMG in the surrounding areas of VDML.

Right now working on a major update of VMP. We are adding the following "value discovery" designers:
- Dashboard to present Value impact with unique views for all individual stakeholders
- Strategy Map (based on Kaplan Norton)
- Value Stream Map (based on VDML and BA Guild priciples)
- Capability Library (based on VDML)
- Capability Map (based on VDML)
- BA Guild reference model import
- Process Designer (BPMN2.0)
- Case Designer (CMMN1.1)

Here a link: https://vdmbee.com/home-new/vdmbee-value-management-platform/

We have also enhanced our User eXperience to support better the notion of the Discovery milestones, Protoype and Adopt phases in making the Business Model plan.   ... "

BlockChain Strategic Business Value

Good, considerable piece in McKinsey.  A number of useful but general industry postionings and examples.  Just a bare mention of definition of smart contracts and their current limitations. 

Blockchain beyond the hype: What is the strategic business value?  in McKinsey   By Brant Carson, Giulio Romanelli, Patricia Walsh, and Askhat Zhumaev

Companies can determine whether they should invest in blockchain by focusing on specific use cases and their market position. .... "

Gartner on the Value of AI: $1.2 Trillion

Such valuations are always difficult.  But it can be expected to be high if it truly augments human effort.

Artificial intelligence will be worth $1.2 trillion to the enterprise in 2018
Gartner says that AI-based customer experience technologies are boosting market value.  By Charlie Osborne for Between the Lines

The artificial intelligence (AI) industry will be worth $1.2 trillion in 2018, with customer experience solutions creating the most business value.

On Wednesday, Gartner released estimates on the projected value of AI over the course of this year. According to the research firm, the global enterprise value derived from AI will total $1.2 trillion this year, a 70 percent increase from 2017.

AI-derived business value is projected to reach up to $3.9 trillion by 2022.

"AI promises to be the most disruptive class of technologies during the next 10 years due to advances in computational power, volume, velocity and variety of data, as well as advances in deep neural networks (DNNs)," said John-David Lovelock, research vice president at Gartner. "One of the biggest aggregate sources for AI-enhanced products and services acquired by organizations between 2017 and 2022 will be niche solutions that address one need very well."

These sort of needs may include methods to improve customer experiences, ways to drive new revenue streams, and means to reduce costs, whether operational or in serving existing products. .... "

More on Location Analysis

They may differ on the value, but its almost always done and reviewed closely.  Sure there are differences in its use among different kinds of retailers.  Consider at very least the capital investment involved.

Retailers Differ on Value of Location Analysis
by Brian Kilcourse in Retailwire.

Through a special arrangement, what follows is a summary of an article from Retail Paradox, RSR Research’s weekly analysis on emerging issues facing retailers, presented here for discussion.

RSR’s first benchmark on location analytics in retail showed there are significant differences in focus depending on what kind of products a retailer sells, and some of the differences are counter-intuitive.

Retailers across the different verticals, performance and size all agree that “more targeted marketing” is essential to their future well-being.

But why, for example, would almost twice as many fashion retailers as fast-moving-consumer-goods (FMCG) and general merchandisers (GM) rank “improved merchandising plan localization” as a high-priority? Fashion retailers introduce new collections every season and typically execute relatively few replenishments after the initial allocation is delivered to the stores. Grocers, drug stores and big box merchants, on the other hand, have many more SKUs in their standardized assortments and replenish very frequently. The payback from assortment localization based on customer-centered analytics are far greater.  ... " 

Data as Feature

Good approach, start with and feature the data as it exists in value producing context.

“Data as a feature” is coming. Are product managers ready?

By packaging and delivering actionable data in applications, product managers can help users achieve their goals.      ...By Alice LaPlante in O'Reilly

 More and more, apps are capable of delivering more than a service, such as access to a bank account or the ability to order a pizza. Apps can offer users data—and not just a dump of data that has little value, but data specifically designed to be of value to the user.

This is called “data as a feature”—it is the act and process of treating data as a core feature of a software product in a way that delivers value to the user. Taking this definition a step further, a product with data as a feature delivers that data in a way that helps the user meet a goal. ... "

HBR: Getting Value from Machine Learning

Makes a very obvious case.    That has existed since the beginning of computing.  Yet still a good one to repeat.  Systems must be easy enough to use.  And then actually used, to make them valuable.  Of course when you add in some level of autonomy, with a clearly measurable value, that helps.   One way to do that is to plug them into a known and measurable business process.   You can show the value of it being better, faster, or cheaper, directly.  Augmentation of people and processes is best.  Making the method automatically considered and even applied.  We did it many times.  Good example of project management below. 

Getting Value from Machine Learning Isn’t About Fancier Algorithms — It’s About Making It Easier to Use    By Ben Schreck, Max Kanter, Kalyan Veeramachaneni, Sanjeev Vohra, Rajendra Prasad  in the HBR

Machine learning can drive tangible business value for a wide range of industries — but only if it is actually put to use. Despite the many machine learning discoveries being made by academics, new research papers showing what is possible, and an increasing amount of data available, companies are struggling to deploy machine learning to solve real business problems. In short, the gap for most companies isn’t that machine learning doesn’t work, but that they struggle to actually use it.

How can companies close this execution gap? In a recent project we illustrated the principles of how to do it. We used machine learning to augment the power of seasoned professionals — in this case, project managers — by allowing them to make data-driven business decisions well in advance. And in doing so, we demonstrated that getting value from machine learning is less about cutting-edge models, and more about making deployment easier.  .... " 

IBM Institute for Business Value

Stating to follow the writing of:

IBM Institute for Business Value
Discover emerging trends, business innovations and success patterns

Access our latest thought leadership through the IBV app ...

Benchmarking:

Evaluate business process performance using open standards for benchmarking

Our benchmarking data is built around a common, cross-industry Process Classification 

Framework, which means that business performance can be objectively evaluated. ... "

Customer Experience Value Creation

Some basic questions ...

What is Customer Experience Value Creation? Featured Column by CustomerThink Advisor
By Lynn Hunsaker  

  Customer experience value is seldom quantified from the customer’s viewpoint. We explore it through customer journey mapping, customer advisory boards, surveys, user experience testing, and so forth. Even so, we still may not be sizing it up from their perspective.

Customer experience value creation occurs when you empower customers to achieve their goals with greater satisfaction in a win-win approach.

Customer experience value creation is creating mutual value for your whole customer base in any part of the end-to-end customer experience, across the full customer life cycle, spanning customers’ entire dealings with your organization, products, services, channels and affiliations. It’s value as seen by the customer, relative to their alternatives, relative to all the costs they endure, and relative to the outcomes they’re pursuing.  .... "

AI is Marketing Hype?

My team and I were involved in the last big hype cycle of AI.  We lost a large chunk of investment in the space.   So the question is a reasonable one.   What should we do?  How should we invest?

  There have been very big advances that we need to take note of, and use, but these have not launched us into an era of general artificial intelligence.  That remains in the future.   The applications of today are still narrow,  but clearly very valuable.    You cannot ignore them.  I am applying them now.  But it will need another jump forward to get real AI.  When?  I believe still decades away.

Is A.I. Just Marketing Hype?
Why are the big breakthroughs always five to 20 years in the future?   By Geoffrey James in Inc ....   "

Global Value Chains

Internalizing Global Value Chains: A Firm-Level Analysis  in HBS
by Laura Alfaro, Pol Antràs, Davin Chor and Paola Conconi

In recent decades, advances in information and communication technology and falling trade barriers have led firms to retain within their boundaries and in their domestic economies only a subset of their production stages. A key decision facing firms worldwide is the extent of control to exert over the different segments of their production processes. We describe a property-rights model of firm boundary choices along the value chain that generalizes Antràs and Chor (2013). To assess the evidence, we construct firm-level measures of the upstreamness of integrated and nonintegrated inputs by combining information on the production activities of firms operating in more than 100 countries with input-output tables. In line with the model's predictions, we find that whether a firm integrates upstream or downstream suppliers depends crucially on the elasticity of demand for its final product. Moreover, a firm's propensity to integrate a given stage of the value chain is shaped by the relative contractibility of the stages located upstream versus downstream from that stage, as well as by the firm's productivity. Our results suggest that contractual frictions play an important role in shaping the integration choices of firms around the world.    ... " 

Is Data the New Oil?

Interesting idea.  But we ingest in a different way than we do fuels.   While the chemistry of petroleum is well known and constant, the chemistry of required data is infinitely variable and constantly changing, so their general use is challenging,  which would lead to better understand data as an asset. Article and discussion in Linkedin.

Talking Tom Reaps Eyeballs

A stark reminder that the most desirable aspect of the Web is still getting eyeballs in the door, and then playing videos.  'Talking Tom'  seemingly trivial, with some interactive botlike aspects, has gotten some 10.3 billion video views.  How might we use these designs?

Talking Tom maker Outfit7 confirms it has been sold to United Luck Consortium for $1 billion   by  Dean TakaHashi in Venturebeat: ... " 

Improving the Value of Data Science

Of interest, taught aspects of this at my recent Columbia Course.  The PDF below is very visual and largely non-technical.   Worth a look.

Optimizing the Effectiveness of Data Science Teams
Data science efforts are only as good as the results they deliver. In this Big Data world, executives are relying on data scientists to help them move their company forward. Here are five ways companies can improve the value of data science

From Appuri    Bob E. Hayes, PhD, Chief Research Officer

Process Innovation with Data in a Digital World

Have always thought in terms of process.  By doing that you can think not only what a process produces in terms of value, but also in terms of data that can be used for further examination and improvement of how things get done.    Even just mapping the process generally can provide  actionable value ....

This Bain article By Chris Brahm and Peter Guarraiais is insightful about an overview of the approach, and makes my  point.  Good complete read:

" ... Remember when the typical reengineering approach boiled down to eliminating, simplifying and automating processes? Seems quaint at a time when digital technology allows companies to transform how they operate, from one end of the value chain to the other. Breakthroughs in areas such as communications technology, analytics, Big Data and the Internet of Things have ushered in an entirely new set of tools to generate more value for customers. The goal of reengineering hasn’t changed, but the means have become significantly more powerful.   ... "