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For over two years, protein structure prediction has been changed by machine learning. On Sept. 15, two science related research talk about a similar idea in the revolution of protein design.

The findings show how machine learning can create protein molecules that are more accurate and made quicker than before.

With these new software tools, we should be able to find solutions to long-standing challenges in medicine, energy, and technology, said senior author David Baker, professor of biochemistry at the University of Washington School of Medicine.

The algorithm used in machine learning which includes RoseTTAFold have been trained to predict the smaller detailed shapes if natural proteins based on their amino acid sequences.

Machine learning is a type of artificial intelligence that allows computers to learn from data without having to be programmed.

A.I. has the ability to generate protein in two ways. One being akin to DALL-E or other A.I. tools that produce an output from simple prompts. The second is the autocomplete feature we can find in a search bar.

As a way of making things go by faster the A.I. team created a new algorithm that creates amino acid sequences. This tool, called ProteinMPNN, creates the sequence in one second. That's over 200 minutes faster than previous best software.

The Baker Lab also says combining new machine learning tools could reliably generate new proteins that functioned in the laboratory. Among those were the nanoscale ring that could make up part of a custom nanomachines.

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University of Washington graduates use artificial intelligence to create new proteins - NBC Right Now

DUBLIN, Sept. 14, 2022 /PRNewswire/ --The "Artificial Intelligence Market Size, Share & Trends Analysis Report by Solution, by Technology (Deep Learning, Machine Learning, Natural Language Processing, Machine Vision), by End Use, by Region, and Segment Forecasts, 2022-2030" report has been added to ResearchAndMarkets.com's offering.

The global artificial intelligence market size is expected to reach USD 1,811.8 billion by 2030. The market is anticipated to expand at a CAGR of 38.1% from 2022 to 2030.

Artificial Intelligence (AI) denotes the concept and development of computing systems capable of performing tasks customarily requiring human assistance, such as decision-making, speech recognition, visual perception, and language translation. AI uses algorithms to understand human speech, visually recognize objects, and process information. These algorithms are used for data processing, calculation, and automated reasoning.

Artificial intelligence researchers continuously improve algorithms for various aspects, as conventional algorithms have drawbacks regarding accuracy and efficiency. These advancements have led manufacturers and technology developers to focus on developing standard algorithms. Recently, several developments have been carried out for enhancing artificial intelligence algorithms. For instance, in May 2020, International Business Machines Corporation announced a wide range of new AI-powered services and capabilities, namely IBM Watson AIOps, for enterprise automation. These services are designed to help automate the IT infrastructures and make them more resilient and cost reduction.

Various companies are implementing AI-based solutions such as RPA (Robotic Process Automation) to enhance the process workflows to handle and automate repetitive tasks. AI-based solutions are also being coupled with the IoT (Internet of Things) to provide robust results for various business processes. For Instance, Microsoft announced to invest USD 1 billion in OpenAI, a San Francisco-based company. The two businesses teamed up to create AI supercomputing technology on Microsoft's Azure cloud.

The COVID-19 pandemic has emerged as an opportunity for AI-enabled computer systems to fight against the epidemic as several tech companies are working on preventing, mitigating, and containing the virus. For instance, LeewayHertz, a U.S.-based custom software development company, offers technology solutions using AI tools and techniques, including the Face Mask Detection System to identify individuals without a mask and the Human Presence System to monitor patients remotely. Besides, Voxel51 Inc., a U.S.-based artificial intelligence start-up, has developed Voxel51 PDI (Physical Distancing Index) to measure the impact of the global pandemic on social behavior across the world.

AI-powered computer platforms or solutions are being used to fight against COVID - 19 in numerous applications, such as early alerts, tracking and prediction, data dashboards, diagnosis and prognosis, treatments and cures, and maintaining social control. Data dashboards that can visualize the pandemic have emerged with the need for coronavirus tracking and prediction. For instance, Microsoft Corporation's Bing's AI tracker gives a global overview of the pandemic's current statistics.

Artificial Intelligence Market Report Highlights

Key Topics Covered:

Chapter 1 Methodology and Scope

Chapter 2 Executive Summary

Chapter 3 Market Variables, Trends & Scope3.1 Market Trends & Outlook3.2 Market Segmentation & Scope3.3 Artificial Intelligence Size and Growth Prospects3.4 Artificial Intelligence-Value Chain Analysis3.5 Artificial Intelligence Market Dynamics3.5.1 Market Drivers3.5.1.1 Economical parallel processing set-up3.5.1.2 Potential R&D in artificial intelligence systems3.5.1.3 Big data fueling AI and Machine Learning profoundly3.5.1.4 Increasing Cross-Industry Partnerships and Collaborations3.5.1.5 AI to counter unmet clinical demand3.5.2 Market Restraint3.5.2.1 Vast demonstrative data requirement3.6 Penetration & Growth Prospect Mapping3.7 Industry Analysis-Porter's3.7.1 Supplier Power3.7.2 Buyer Power3.7.3 Substitution Threat3.7.4 Threat From New Entrant3.7.5 Competitive Rivalry3.8 Company Market Share Analysis, 20213.9 Artificial Intelligence-PEST Analysis3.9.1 Political3.9.2 Economic3.9.3 Social3.9.4 Technology3.10 Artificial Intelligence-COVID-19 Impact Analysis

Chapter 4 Artificial Intelligence Market: Solution Estimates & Trend Analysis4.1 Artificial Intelligence Market: Solution Movement Analysis4.1.1 Hardware4.1.1.1. Hardware Artificial Intelligence Market, by Region, 2017-20304.1.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)4.1.2 Software4.1.2.1. Software Artificial Intelligence Market, by Region, 2017-20304.1.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)4.1.3 Services4.1.3.1. Services Artificial Intelligence Market, by Region, 2017-20304.1.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 5 Artificial Intelligence Market: Technology Estimates & Trend Analysis5.1 Artificial Intelligence Market: Technology Movement Analysis5.1.1 Deep Learning5.1.1.1. Deep Learning Artificial Intelligence System Market, by Region, 2017-20305.1.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.2 Machine Learning5.1.2.1. Machine Learning Artificial Intelligence System Market, by Region, 2017-20305.1.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.3 Nlp5.1.3.1. Nlp Artificial Intelligence System Market, by Region, 2017-20305.1.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)5.1.4 Machine Vision 5.1.4.1. Machine Vision Artificial Intelligence System Market, by Region, 2017-20305.1.4.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 6 Artificial Intelligence Market: End-Use Estimates & Trend Analysis6.1 Artificial Intelligence Market: End-Use Movement Analysis6.2 Artificial Intelligence Market: End-Use Trends6.2.1 Healthcare6.2.1.1. Healthcare Artificial Intelligence Market, by Region, 2017-20306.2.1.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.1.2. Healthcare by Use Case6.2.1.2.1. Global Ai Healthcare Market, by Use Case, 2017-2030 (USD Billion)6.2.2 Bfsi6.2.2.1. Bfsi Artificial Intelligence Market, by Region, 2017-20306.2.2.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.2.2. Bfsi by End Use6.2.2.2.1. Global Ai Bfsi Market, by End Use, 2017-2030 (USD Billion)6.2.3 Law6.2.3.1. Law Artificial Intelligence Market, by Region, 2017-20306.2.3.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.4 Retail6.2.4.1. Retail Artificial Intelligence Market, by Region, 2017-20306.2.4.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.5 Advertising & Media6.2.5.1. Advertising & Media Artificial Intelligence Market, by Region, 2017-20306.2.5.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.6 Automotive & Transportation6.2.6.1. Automotive & Transportation Artificial Intelligence Market, by Region, 2017-20306.2.6.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.7 Agriculture6.2.7.1. Agriculture Artificial Intelligence Market, by Region, 2017-20306.2.7.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.8 Manufacturing6.2.8.1. Manufacturing Artificial Intelligence Market, by Region, 2017-20306.2.8.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)6.2.9 Others6.2.9.1. Others Artificial Intelligence Market, by Region, 2017-20306.2.9.1.1. Market Estimates and Forecasts, 2017-2030 (USD Billion)

Chapter 7 Artificial Intelligence Market: Regional Estimates & Trend Analysis

Chapter 8 Competitive Landscape8.1 Company Profiles8.1.1 Advanced Micro Devices8.1.1.1 Company overview8.1.1.2 Financial performance8.1.1.3 Product benchmarking8.1.1.4 Strategic Initiatives8.1.2 AiCure8.1.2.1 Company overview8.1.2.2 Product benchmarking8.1.2.3 Strategic Initiatives8.1.3 Arm Limited8.1.3.1 Company overview8.1.3.2 Product benchmarking8.1.3.3 Strategic Initiatives8.1.4 Atomwise, Inc.8.1.4.1 Company overview8.1.4.2 Product benchmarking8.1.4.3 Strategic Initiatives8.1.5 Ayasdi AI LLC8.1.5.1 Company overview8.1.5.2 Product benchmarking8.1.5.3 Strategic Initiatives8.1.6 Baidu, Inc.8.1.6.1 Company overview8.1.6.2 Financial performance8.1.6.3 Product benchmarking8.1.6.4 Strategic Initiatives8.1.7 Clarifai, Inc8.1.7.1 Company overview8.1.7.2 Product benchmarking8.1.7.3 Strategic Initiatives8.1.8 Cyrcadia Health8.1.8.1 Company overview8.1.8.2 Product benchmarking8.1.8.3 Strategic Initiatives8.1.9 Enlitic, Inc.8.1.9.1 Company overview8.1.9.2 Product benchmarking8.1.9.3 Strategic Initiatives8.1.10 Google LLC8.1.10.1 Company overview8.1.10.2 Financial performance8.1.10.3 Product benchmarking8.1.10.4 Strategic Initiatives8.1.11 H2O.ai.8.1.11.1 Company overview8.1.11.2 Product benchmarking8.1.11.3 Strategic Initiatives8.1.12 HyperVerge, Inc.8.1.12.1 Company overview8.1.12.2 Product benchmarking8.1.12.3 Strategic Initiatives8.1.13 International Business Machines Corporation8.1.13.1 Company overview8.1.13.2 Financial performance8.1.13.3 Product benchmarking8.1.13.4 Strategic Initiatives8.1.14 IBM Watson Health8.1.14.1 Company overview8.1.14.2 Financial performance8.1.14.3 Product benchmarking8.1.14.4 Strategic Initiatives8.1.15 Intel Corporation8.1.15.1 Company overview8.1.15.2 Financial performance8.1.15.3 Product benchmarking8.1.15.4 Strategic Initiatives8.1.16 Iris.ai AS.8.1.16.1 Company overview8.1.16.2 Product benchmarking8.1.16.3 Strategic Initiatives8.1.17 Lifegraph8.1.17.1 Company overview8.1.17.2 Product benchmarking8.1.17.3 Strategic Initiatives8.1.18 Microsoft8.1.18.1 Company overview8.1.18.2 Financial performance8.1.18.3 Product benchmarking8.1.18.4 Strategic Initiatives8.1.19 NVIDIA Corporation8.1.19.1 Company overview8.1.19.2 Financial performance8.1.19.3 Product benchmarking8.1.14.4 Strategic Initiatives8.1.20 Sensely, Inc.8.1.20.1 Company overview8.1.20.2 Product benchmarking8.1.20.3 Strategic Initiatives8.1.21 Zebra Medical Vision, Inc.8.1.21.1 Company overview8.1.21.2 Product benchmarking8.1.21.3 Strategic Initiatives

For more information about this report visit https://www.researchandmarkets.com/r/nr5za

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Insights on the Artificial Intelligence Global Market to 2030 - Featuring Baidu, Clarifai and Google Among Others - PR Newswire

In the Top Gun, HAL 9000, and Jobs of the Future podcast (September 15, 2022), WBC director Robert J. Marks discusses whether AI is sucking up all our jobs with talk show host Mark Hahn, who can be heard on KSCJ in Sioux City, Iowa. Dr. Marks, author of Non-Computable You is a professor of computer engineering at Baylor University and a pioneer of AI swarm intelligence. This is the second half of the podcast.

A partial transcript, notes, and Additional Resources follow.

Mark Hahn: Dr. Marks, artificial intelligence is something that many people have fantasized on a science fiction level; many shows have been about that. Of course, in Space Odyssey 2001, HAL took over, and thats what scared people about artificial intelligence. Are we going to be making computers that are smarter than us?

Robert J. Marks: No. Absolutely not. And I dont know if HAL 2000 was smarter than the people. I think it was just programmed incorrectly. It was programmed to put the mission before human life. And I dont know if it was actually took over in any sense.

Note: HAL 9000 was an incredibly knowledgeable AI system that was given one simple order: to make sure that the ship reached its destination at Jupiter. (VillainsWiki) As Dr. Marks notes, AI has no natural ethical system so HAL did not hesitate to plot the deaths of crew members in order to guide the ship to its destination: At one point on the trip from Earth to Jupiter, HAL becomes suspicious that the crew might be sabotaging the mission. HAL then purposely tries to kill all the crew. The most logical explanation for this act is a coding error. HAL was programmed to operate on the basis that the mission took priority over human life. By contrast, science fiction writer Isaac Asimov did not allow his AI to kill. In his work, I, Robot, Asimov proposes three laws for robotics. The first is:

A robot may not injure a human being or, through inaction, allow a human being to come to harm.

If HAL were constrained by this or a similar instruction, there would be no attempts at killing, and 2001: A Space Odyssey would be a much less interesting movie. Could HAL 9000 ever be built? (Mind Matters News)

Mark Hahn: Well, thereve been other books too, along the same line, where man makes a computer, he keeps improving the computer; finally, he wants to have it have a little bit of intelligence on its own, based on, of course, the information that you put into it. And thats what computers are: garbage in, garbage out. If you put good things in there and you build the formats properly for what you want to do, it stays within those parameters. It doesnt go outside, just as you just discussed.

Robert J. Marks: Thats a very good illustration. The idea is that computers and artificial intelligence can take their training data and they can interpolate. They can look inside the box, but they dont have the creative ability to think outside the box.

Mark Hahn: Are future humans doomed to be replaced by artificial intelligence? And of course you said emphatically, No. But what will it replace? Will it replace travel agents? Right now, you certainly have online travel sites that are set up. And you can book in your own travel; you dont need an agent.

Robert J. Marks: You have to ask yourself, can a certain job be described by an algorithm, meaning a step-by-step procedure for doing something? Thats certainly true for travel agents. They go through step-by-step procedures. You hear other things: toll booth operators, for example. Theyre totally gone because they just did a simple algorithm.

Robert J. Marks: So, if your task could be defined by an algorithm, your job is in danger of being replaced by artificial intelligence. But if your position requires sentience, if it requires creativity, if it requires understanding, youre probably in less danger of artificial intelligence taking over.

What is going to happen eventually is, artificial intelligence is going to be a tool. And thats all artificial intelligence is. Its a tool. Its a tool which can be used by different professions to do a better job. But it isnt going to replace them

I would also say that artificial intelligence is going to introduce new jobs. Today we have all of these people that make their living on TikTok or some of these other social media. And we have people that work for Google that do all the censoring of the content. Not a good job. But nevertheless, these are jobs created by artificial intelligence and technology. So, I guess Im a big believer in free enterprise. And it might be painful, but I think that were going to adapt

Note: The Employment Situation Summary compiled by the U.S. Bureau of Labor Statistics for September 2, 2022, reports that Total nonfarm payroll employment increased by 315,000 in August, and the unemployment rate rose to 3.7 percent Notable job gains occurred in professional and business services, health care, and retail trade. 3.7% is not at high unemployment rate, especially if we factor in job changes, etc. If AI is indeed taking all our jobs, it is rather slow about it.

Robert J. Marks: When I was a boy and you made a long distance call, if you went to a payphone, you had to put nickels and quarters in it. And today, I can do FaceTime. Ive done this simultaneously with somebody in Sweden and another person in Colombia. Its just like were in the same room. AI does incredible things.

But as I mentioned in the beginning, theres certain walls that its never going to go through. And I think some of those walls are things like The Terminator and The Matrix. Those things are never going to happen.

Mark Hahn: Well, thats true. Are we ever going to have AI campaign managers in political campaigns? Here we are, coming up to the midterms

Robert J. Marks: I think AI is going to be a tool in this sort of thing. But one of the things that AI doesnt have is creativity. And you can talk about not only campaign managers but, say, a commander in the field.

Now, campaign managers and a commander in the military field are going to face scenarios that theyve never seen before. CEOs of companies do the same thing too. Now, the AI has to be trained in that scenario. If it sees a scenario that it hasnt seen before and its outside the box, if you will, it doesnt know what to do. But people, campaign managers and commanders in the field in the military field are going to have to react and assess situations that theyve never seen before and adapt to them. And no, I dont think artificial intelligence will ever do that. Now, AI might be used as a tool by these people that can give them forecast and suggestions of things to do. But the final decision will always lie with the human.

Heres the first part of the podcast: Marks tells Medved: Top Gun (2022) is way out of date Computer science prof Robert J. Marks argues in Non-Computable You, that in the 21st century, drones offer significant advantages over fighter pilots. But he also warns talk show host Michael Medved, AI is brittle and the ethics factor must be built in. It takes human intelligence to do that.

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AI Is Not Taking Away Our Jobs Because It Can't Do Them - Walter Bradley Center for Natural and Artificial Intelligence

In three to five years, 80% of what marketers do will be dependent on artificial intelligence.

MSP SUMMIT/CHANNEL PARTNERS LEADERSHIP SUMMIT Allison Bergamo knows the power of artificial intelligence (AI) for marketing. Bergamo, principal at Bergamo Marketing Group, uses that kind of AI at her firm because, she said, she wants to be ahead of the curve. Bergamo wouldnt be wrong. As statistics go, in three to five years, 80% of what marketers do will be dependent on this type of technology.

Bergamo Marketing Groups Allison Bergamo

However, its not plug and play, said Bergamo, who added that marketers will have to use clean, unstructured data with some of the technology.

Bergamo was part of a panel of marketing experts who spoke at the MSP Summit/Channel Partners Leadership Summit in Orlando on Thursday. Their advice to the audience spanned from using artificial intelligence technology, to how to master relationships, to learning ways to market on a budget. The latter couldnt be more relevant for MSPs, they said.

Even though many MSPs are small and have finite resources, that doesnt mean they should neglect marketing.

You can find money in your budget to allocate toward this. Its important, said Marcial Velez (pictured right, above), CEO at Xperteks Computer Consultancy. Historically MSPs grow about 10% [annually]. If you want to outperform that rate, youve got to invest in this.

And the investment doesnt have to be expensive, the panelists said. One can be technologically savvy about marketing without spending a lot of money. Velez said digital business cards are a great example because they can share information beyond someones name and company affiliation. Social media and blog posts can also be exchanged with this tool.

You can now start connecting to the content that you want your customers to see right away. You can now show your story, he said.

Charlene Ignacio, CEO (pictured middle, above) at The CMO Guru, HireXPro, also agreed that simplicity goes a long way. She likened it to the difference between buying an expensive Mercedes (a euphemism for a pricey marketing program) and buying a Honda. Everyone thinks they need the Mercedes, she said, even though a Honda can get you where you need to go.

A Honda works perfectly. It will last you 20 years longer, and the maintenance is lower, Ignacio said. When it comes to marketing, I like to do simple things because marketing can become like a black hole (of costs).

However, knowing whether to use cost-effective AI and digital business card tools presumes a certain baseline knowledge by a companys team. If a firm doesnt have that knowledge and needs a marketing program to attain those kind of resources, where do they begin?

Finding a company to outsource ones marketing may be a good first step. And a firm might have luck initially finding marketers who understand its business model. However, the panelists said the likely scenario is that ones first choice of marketers will not work out. Be prepared to fail, they said. But fail fast.

Take Reggie Stevens (pictured left, above), CEO at Iris Solutions, for example. In 2018, Stevens acquired Iris Solutions and set out to find a marketing team.

I didnt know what I was doing, he said.

It turns out neither did the marketers. Yet Stevens didnt spend his time begrudging the fact that he didnt get the professionals he needed to promote his company.

The pandemic made life even more complicated. Stevens knew he needed to keep his community of customers engaged differently because many people were working remotely.

He was steadfast and found another marketing firm.

You know, we had this freak-out moment and we just went back to the basics and started experimenting, he said about his work with the new marketing team. We began differently.

And he started to see results, but it took a year. This is not unusual for marketing initiatives.

Establishing reasonable expectations around how much time it takes to generate a marketing pipeline is critical, he said. It takes a commitment.

However, its even more granular than that. Its a 24/7 process, Velez said.

I think the modern marketer today is someone who looks at marketing more than just an activity, he said. You should automate these systems so that youre continually outreaching and doing things for your existing customers and prospecting for any of your clients.

He added: It takes someone with a really holistic view.

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Experts Speak to the Power of Artificial Intelligence for Effective Marketing - Channel Futures

LONDON, Sept. 14, 2022 (GLOBE NEWSWIRE) -- According to The Business Research Companys research report on the digital transformation market, the increasing adoption of machine learning and artificial intelligence is expected to drive the growth of the digital transformation market going forward. Digital transformation provides traditional businesses with solutions like cloud computing, big data & analytics, data management, and other advanced features such as artificial intelligence and machine learning, which help in the optimization of business operations, leading to reduced efforts in operations and increased efficiency. Thus, their usage increased in various sectors such as healthcare, banking, transportation, manufacturing, and others, increasing the demand in the digital transformation market.

For instance, according to the report published by Cloudmantra, an India-based technology services company, the usage of machine learning in the Indian manufacturing industry has increased manufacturing capacity by up to 20% while reducing material usage by 4% in 2021. It also gives manufacturers the ability to control Overall Equipment Effectiveness (OEE) at the plant level, increasing OEE performance from 65% to 85%. Furthermore, according to the MIT Technology Review Insights report in 2022, approximately 60% of manufacturers are using artificial intelligence to improve daily operations, design products, and plan their future operations. Therefore, the rising adoption of machine learning and AI drives the digital transformation market.

Request for a sample of the global digital transformation market report

The global digital transformation market size is expected to grow from $0.94 trillion in 2021 to $1.17 trillion in 2022 at a compound annual growth rate (CAGR) of 24.7%. The global digital transformation market share is expected to grow to $2.64 trillion in 2026 at a CAGR of 22.4%.

Technological advancement in digital solutions is gaining popularity among the digital transformation market trends. Major companies operating in the digital transformation market are focused on developing technologically advanced products to strengthen their market position. For instance, in April 2020, Oracle Corporation, a US-based computer technology corporation and software solutions provider, built a new cloud data storage service called GoldenGate, an oracles cloud infrastructure software that uses real-time data analytics for the analysis of data. Real-time data analysis provides a very quick analysis of data by using different logical and mathematical operations, which helps in understanding business requirements and implementing any decision instantly. GoldenGate provides clients with a highly automated and fully managed cloud service such as database replication, analyzing real-time data, and real-time data ingestion to the cloud, which will make daily business operations easy and analyzable.

Major players in the digital transformation market are Microsoft Corporation, IBM Corporation, Oracle Corporation, Google Inc., Cognizant, Accenture PLC, Dell EMC, Siemens AG, Hewlett-Packard Company, Adobe Systems Inc., Capgemini, Cognex Corporation, Deloitte, Marlabs Inc., Equinix Inc., PricewaterhouseCoopers, Apple Inc., Broadcom, CA Technologies, KELLTON TECH, International Business Machines Corporation, Hakuna Matata Solutions, ScienceSoft Inc., SumatoSoft, Space-O Technologies, HCL Technologies, and Tibco Software Inc.

The global digital transformation market analysis is segmented by technology into cloud computing, big data and analytics, artificial intelligence (AI), internet of things (IoT), blockchain; by deployment mode into cloud, on-premises; by organization size into large enterprises, small and medium-sized enterprises (SMEs); by end-user into BFSI, healthcare, telecom and IT, automotive, education, retail and consumer goods, media and entertainment manufacturing, government, others.

North America was the largest region in the digital transformation market in 2021. Asia-Pacific is expected to be the fastest-growing region in the global digital transformation market during the forecast period. The regions covered in the global digital transformation industry outlook are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa.

Digital Transformation Global Market Report 2022 Market Size, Trends, And Global Forecast 2022-2026 is one of a series of new reports from The Business Research Company that provide digital transformation market overviews, analyze and forecast market size and growth for the whole market, digital transformation market segments and geographies, digital transformation market trends, digital transformation market drivers, digital transformation market restraints, digital transformation market leading competitors revenues, profiles and market shares in over 1,000 industry reports, covering over 2,500 market segments and 60 geographies.

The report also gives in-depth analysis of the impact of COVID-19 on the market. The reports draw on 150,000 datasets, extensive secondary research, and exclusive insights from interviews with industry leaders. A highly experienced and expert team of analysts and modelers provides market analysis and forecasts. The reports identify top countries and segments for opportunities and strategies based on market trends and leading competitors approaches.

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The Increased Use Of Machine Learning And Artificial Intelligence Is Expected To Fuel The Digital Transformation Market As Per The Business Research...