Category Archives: Artificial Intelligence

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The global economy is at a critical crossroads with a number of interlocking challenges and crises running in parallel. The uncertainty around how Russia`s war on Ukraine will play out this year and the war`s role in creating global instability means that the trouble on the inflation front is not over yet.

New York, April 19, 2023 (GLOBE NEWSWIRE) -- Reportlinker.com announces the release of the report "Global Artificial Intelligence (AI) Platform Industry" - https://www.reportlinker.com/p06030752/?utm_source=GNW Food and fuel inflation will remain a persistent economic problem. Higher retail inflation will impact consumer confidence and spending. As governments combat inflation by raising interest rates, new job creation will slowdown and impact economic activity and growth. Lower capital expenditure is in the offing as companies go slow on investments, held back by inflation worries and weaker demand. With slower growth and high inflation, developed markets seem primed to enter into a recession. Fears of new COVID outbreaks and Chinas already uncertain post-pandemic path poses a real risk of the world experiencing more acute supply chain pain and manufacturing disruptions this year. Volatile financial markets, growing trade tensions, stricter regulatory environment and pressure to mainstream climate change into economic decisions will compound the complexity of challenges faced. Year 2023 is expected to be tough year for most markets, investors and consumers. Nevertheless, there is always opportunity for businesses and their leaders who can chart a path forward with resilience and adaptability.

Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030

In the changed post COVID-19 business landscape, the global market for Artificial Intelligence (AI) Platform estimated at US$17.8 Billion in the year 2022, is projected to reach a revised size of US$120.7 Billion by 2030, growing at aCAGR of 27.1% over the period 2022-2030. Cloud, one of the segments analyzed in the report, is projected to record 28.8% CAGR and reach US$84 Billion by the end of the analysis period. Taking into account the ongoing post pandemic recovery, growth in the On-Premise segment is readjusted to a revised 23.8% CAGR for the next 8-year period.

The U.S. Market is Estimated at $5.3 Billion, While China is Forecast to Grow at 25.8% CAGR

The Artificial Intelligence (AI) Platform market in the U.S. is estimated at US$5.3 Billion in the year 2022. China, the world`s second largest economy, is forecast to reach a projected market size of US$20 Billion by the year 2030 trailing a CAGR of 25.8% over the analysis period 2022 to 2030. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 23.3% and 21.9% respectively over the 2022-2030 period. Within Europe, Germany is forecast to grow at approximately 16.8% CAGR.

Select Competitors (Total 240 Featured)- Absolutdata- Amazon Web Services- Apple inc.- Ayasdi- Enlitic, inc.- Facebook inc.- General Electric- General vision, inc.- Google LLC- Hewlett Packard Enterprise Development LP- IBM Corporation- icarbonX- Infosys- Intel Corporation- Micro Technology inc.- Microsoft Corporation- Next It Corporation- Qualcomm Technologies- Salesforce.com, inc.- SAMSUNG- SAP- Siemens AG- Wipro

Read the full report: https://www.reportlinker.com/p06030752/?utm_source=GNW

I. METHODOLOGY

II. EXECUTIVE SUMMARY

1. MARKET OVERVIEWInfluencer Market InsightsWorld Market TrajectoriesImpact of Covid-19 and a Looming Global RecessionArtificial Intelligence (AI) Platform - Global Key CompetitorsPercentage Market Share in 2022 (E)Competitive Market Presence - Strong/Active/Niche/Trivial forPlayers Worldwide in 2022 (E)

2. FOCUS ON SELECT PLAYERS

3. MARKET TRENDS & DRIVERS

4. GLOBAL MARKET PERSPECTIVETable 1: World Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -USA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld Markets - Independent Analysis of Annual Sales in US$Million for Years 2022 through 2030 and % CAGR

Table 2: World 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for USA, Canada, Japan, China, Europe, Asia-Pacificand Rest of World Markets for Years 2023 & 2030

Table 3: World Recent Past, Current & Future Analysis for Cloudby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 4: World 8-Year Perspective for Cloud by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 5: World Recent Past, Current & Future Analysis forOn-Premise by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 6: World 8-Year Perspective for On-Premise by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 7: World Recent Past, Current & Future Analysis forHealthcare by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 8: World 8-Year Perspective for Healthcare by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 9: World Recent Past, Current & Future Analysis forResearch & Academia by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 10: World 8-Year Perspective for Research & Academia byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 11: World Recent Past, Current & Future Analysis forTransportation by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 12: World 8-Year Perspective for Transportation byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 13: World Recent Past, Current & Future Analysis forRetail & eCommerce by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 14: World 8-Year Perspective for Retail & eCommerce byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 15: World Recent Past, Current & Future Analysis forOther End-Uses by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 16: World 8-Year Perspective for Other End-Uses byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 17: World Recent Past, Current & Future Analysis for BFSIby Geographic Region - USA, Canada, Japan, China, Europe,Asia-Pacific and Rest of World Markets - Independent Analysisof Annual Sales in US$ Million for Years 2022 through 2030 and% CAGR

Table 18: World 8-Year Perspective for BFSI by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 19: World Recent Past, Current & Future Analysis forManufacturing by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 20: World 8-Year Perspective for Manufacturing byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 21: World Recent Past, Current & Future Analysis forForecasts & Prescriptive Models by Geographic Region - USA,Canada, Japan, China, Europe, Asia-Pacific and Rest of WorldMarkets - Independent Analysis of Annual Sales in US$ Millionfor Years 2022 through 2030 and % CAGR

Table 22: World 8-Year Perspective for Forecasts & PrescriptiveModels by Geographic Region - Percentage Breakdown of ValueSales for USA, Canada, Japan, China, Europe, Asia-Pacific andRest of World for Years 2023 & 2030

Table 23: World Recent Past, Current & Future Analysis forChatbots by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 24: World 8-Year Perspective for Chatbots by GeographicRegion - Percentage Breakdown of Value Sales for USA, Canada,Japan, China, Europe, Asia-Pacific and Rest of World for Years2023 & 2030

Table 25: World Recent Past, Current & Future Analysis forSpeech Recognition by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 26: World 8-Year Perspective for Speech Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 27: World Recent Past, Current & Future Analysis for TextRecognition by Geographic Region - USA, Canada, Japan, China,Europe, Asia-Pacific and Rest of World Markets - IndependentAnalysis of Annual Sales in US$ Million for Years 2022 through2030 and % CAGR

Table 28: World 8-Year Perspective for Text Recognition byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 29: World Recent Past, Current & Future Analysis forOther Applications by Geographic Region - USA, Canada, Japan,China, Europe, Asia-Pacific and Rest of World Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 30: World 8-Year Perspective for Other Applications byGeographic Region - Percentage Breakdown of Value Sales forUSA, Canada, Japan, China, Europe, Asia-Pacific and Rest ofWorld for Years 2023 & 2030

Table 31: World Artificial Intelligence (AI) Platform MarketAnalysis of Annual Sales in US$ Million for Years 2014 through2030

III. MARKET ANALYSIS

UNITED STATESArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Statesfor 2023 (E)Table 32: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 33: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 34: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 35: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 36: USA Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 37: USA 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CANADATable 38: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 39: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 40: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 41: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 42: Canada Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 43: Canada 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

JAPANArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Japan for 2023 (E)Table 44: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 45: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 46: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 47: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 48: Japan Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 49: Japan 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

CHINAArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in China for 2023 (E)Table 50: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 51: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 52: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 53: China 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 54: China Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 55: China 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

EUROPEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Europe for 2023 (E)Table 56: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Geographic Region -France, Germany, Italy, UK and Rest of Europe Markets -Independent Analysis of Annual Sales in US$ Million for Years2022 through 2030 and % CAGR

Table 57: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Geographic Region - Percentage Breakdown ofValue Sales for France, Germany, Italy, UK and Rest of EuropeMarkets for Years 2023 & 2030

Table 58: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 59: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 60: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 61: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 62: Europe Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 63: Europe 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

FRANCEArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in France for 2023 (E)Table 64: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 65: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 66: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 67: France 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 68: France Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 69: France 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

GERMANYArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in Germany for 2023(E)Table 70: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 71: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Deployment - Percentage Breakdownof Value Sales for Cloud and On-Premise for the Years 2023 &2030

Table 72: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 73: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by End-Use - Percentage Breakdown ofValue Sales for Healthcare, Research & Academia,Transportation, Retail & eCommerce, Other End-Uses, BFSI andManufacturing for the Years 2023 & 2030

Table 74: Germany Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 75: Germany 8-Year Perspective for ArtificialIntelligence (AI) Platform by Application - PercentageBreakdown of Value Sales for Forecasts & Prescriptive Models,Chatbots, Speech Recognition, Text Recognition and OtherApplications for the Years 2023 & 2030

ITALYTable 76: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 77: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 78: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 79: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

Table 80: Italy Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Application -Forecasts & Prescriptive Models, Chatbots, Speech Recognition,Text Recognition and Other Applications - Independent Analysisof Annual Sales in US$ Million for the Years 2022 through 2030and % CAGR

Table 81: Italy 8-Year Perspective for Artificial Intelligence(AI) Platform by Application - Percentage Breakdown of ValueSales for Forecasts & Prescriptive Models, Chatbots, SpeechRecognition, Text Recognition and Other Applications for theYears 2023 & 2030

UNITED KINGDOMArtificial Intelligence (AI) Platform Market Presence - Strong/Active/Niche/Trivial - Key Competitors in the United Kingdomfor 2023 (E)Table 82: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by Deployment - Cloud andOn-Premise - Independent Analysis of Annual Sales in US$Million for the Years 2022 through 2030 and % CAGR

Table 83: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by Deployment - Percentage Breakdown of ValueSales for Cloud and On-Premise for the Years 2023 & 2030

Table 84: UK Recent Past, Current & Future Analysis forArtificial Intelligence (AI) Platform by End-Use - Healthcare,Research & Academia, Transportation, Retail & eCommerce, OtherEnd-Uses, BFSI and Manufacturing - Independent Analysis ofAnnual Sales in US$ Million for the Years 2022 through 2030 and% CAGR

Table 85: UK 8-Year Perspective for Artificial Intelligence(AI) Platform by End-Use - Percentage Breakdown of Value Salesfor Healthcare, Research & Academia, Transportation, Retail &eCommerce, Other End-Uses, BFSI and Manufacturing for the Years2023 & 2030

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Global Artificial Intelligence (AI) Platform Market to Reach $120.7 Billion by 2030 - Yahoo Finance

In a report by MIT, a student explains what AI is. He says, its kind of like a baby or a human brain because it has to learn, and it stores and uses that information to figure things out.

For a 10 yr old to give such an explanation on a vast phenomenon like AI, means that we have come a long way. AI has always been there and whether we know it or not we use it everyday. The place of artificial intelligence (AI) in the future of education is the subject of intense discussion. Fans of the technology argue that schools must adopt it and use it to deliver a more effective educational experience, while critics fear that its adoption will have a number of negative side consequences.

There is no clear consensus regarding which point of view is correct. AI does not have to be a one-size-fits-all solution. As with most technologies, implementing it safely and successfully necessitates a complete comprehension of the advantages and disadvantages. To give us more insights on this we had our monthly Roundtable session.

The session was moderated by Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne along with our experienced panelists, Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i, Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance, Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion, Parikshit Nag, Head of Data & Analytics at Indus OS and Anand K Sundaram, Head Retail Analytics at IDFC First Bank.

AI has been here since the machine was invented. Nothing has changed. The fundamentals have never been changed and it will never be changed in itself. The challenge is that the academic body, especially in emerging countries like India, never paced up with AI, because the last 25 years has always been about software development. Because everybody was focusing on Java. Now, everything can be done by generative AI or ChatGPT.

Thats when you require logic and require data. Thats where the premise comes into picture. The economic institutions, especially in emerging countries, had never been ready to do it. We see a lot of things where academics and corporate need to be together. But it actually has never been due to the diversity we have today. We are the largest, biggest population in India. We dont even know how deep and diverse the number of people who are passing out are.

Chiranjiv Roy, Vice President Industry 4.0, Applied AI at Course5i

Its fantastic how far we have moved, from the information being restricted to the elite part of the society. This relates to whether we will have information based education or transformational education. We are used to having information based education which is generated by 10% of the society, the rest 90% of that information is replicated, duplicated and consumed. But now we are entering into the transformation way of learning things.

The section of society, which was restricted from getting exposed to the new way of learning new things and new trends, is easily accessible now. I dont see any boundaries or any socio economic conditions. Some people may not have access to some quality education, because we do get an education, but the quality of education also matters and the networking matters, exposure matters. But theres a different set of challenges to deal with.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

Any transformation does not come easy. And its not done on an immediate basis, it takes a certain time to establish. In recent years there is too much excitement in the institutes and academies. Kids learn mobile apps at the age of eight but know nothing. Its a transformation stage. And sometimes in transformation, it takes a while to get the right things in place. For every person its like a dual ceiling.

Anand K Sundaram, Head Retail Analytics at IDFC First Bank

Analytics is all about predictive modeling. Everybody is fencing that some models will run and theyll change the world but Analytics is a mix of business plus math plus statistics. These are the basic combinations a person needs to know. From an academy perspective, I think they need to blend all of it together. In case they want to keep a pace, the first thing is to get your basics right for every kid who you are coaching.

Online courses are a little boring, because many times, you dont have a live instructor. Its more of a recorded session and if I have a question, I dont have anybody to talk to. Similarly, it goes with Academia right now in India, its not really a knowledge gaining kind of institution. Analytics is an upcoming area, if you get certified you get a job, and people come to the job and they struggle. We dont really look at knowledge, we dont really teach people how to survive in our environment. Especially when you have to deliver outcomes, because we are in the business of doing so.

Deepika Kaushal, Deputy Vice President at Piramal Capital & Housing Finance

Companies come in and tell you that if you learn to code, as a six year old, you will become the next Steve Jobs, but you probably wont. And even if you do become the next Steve Jobs, its probably not going to be because he picked up a course as a six year old. The rate at which AI is evolving, I think for any student who actually has exposure to all of these three subjects(math, stats and business) to begin with, and formed a strong base there is way more critical as compared to learning about NLP or large language model, some course or learning about decision trees and fitting them in the Titanic data set.

Institutions use some of the open source datasets which are available, and that doesnt make sense because they come back and talk about what they have done. But if you ask them how the decision tree works, theyll just falter. If you think about putting AI as a course right now, its evolving very fast. Standardising it into the curriculum doesnt make sense at this point in time. One thing, which we tremendously lack in India, is industry exposure. And there is a gap on both sides. If you look at Academia, they dont have enough industrial projects going for them.

In the real world scenario, if you look at most of the corporations, they dont have a strong AI or r&d division, which basically only focuses on research. Most of the AI teams, in corporates, have some business goals, which they need to achieve. And they need to deliver on that within a particular timeline. Because AI is expensive. I think that gap needs to be bridged really fast.

Parikshit Nag, Head of Data & Analytics at Indus OS

There are two aspects to it, one is the creation of it, and then governing it. Education is not just about technology itself. I dont think we are there yet. None of the institutes are really wrapping their heads around. What do we teach our kids? How do you make it easily accessible and easily comprehensible by our school kids or college kids? More than creation, the biggest challenge, the academy still needs to think about, is to educate or create awareness about how we govern this.

Some people refer to it as the curse of magic. So technology is not something that happened yesterday, it is just that awareness is exploding. So the technology itself is not really that complicated. We can train our people, we can put them through and grind them out. But how do we harness the power that needs to be educated along with creation of it? None of the institutes are ready for it yet.

Shan Duggatimatad, Data & AI leader- Sr Director at Ascendion

There is no standardized framework, yet in India, or even globally, per se, but it has started to seep into the ecosystem. These kinds of regulations are quite exhausted and have started seeping into the culture of individuals and institutes as well. The second thing is around data literacy. Why do we actually need to classify data? The thing is, its very easy to store data somewhere in a data lake and make it accessible to everyone.

But should the data thats available be accessible? Or should everyone be able to access, is a very critical question. The point is around data classification, ensuring that PII data is masked and kept separately, its not accessible to everyone, people who actually have permission, and its all time bound to ensure that they delete the data after a certain point in time. Its a good practice, but it will take time to actually standardize this into a particular bill. I think it will take some time for it to standardize, but I think it will come out more around ethical AI.

Its going to be more of an individual responsibility to say that lets not breach privacy, lets ensure that were doing things and it will be the responsibility of organizations and institutes who actually inculcate this kind of thinking.

Parikshit Nag, Head of Data & Analytics at Indus OS

Its exciting to see how the two industries can combine and what opportunities they bring out.

To conclude, the only thing better than learning from your own mistakes is asking a machine learning algorithm to do it for you. Rathnakumar Udayakumar, Product Lead Cloud and AI at Netradyne

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Council Post: Exploring Pros and Cons of Artificial Intelligence in ... - Analytics India Magazine

invest in ai

Artificial intelligence has become one of the most talked about technologies over the past few years. Many see AI with large dollar signs in their eyes. However, every new technology has a lag between invention and commodification and just as every new technology has the risk that it wont pan out. For investors, this poses a challenge. While the risks are real so, too, are the opportunities. So, for a technology that is still effective in the drumroll phase, how can you invest? Here are a few ideas. For more personalized investment advice, consider working with a financial advisor.

Artificial Intelligence Industry

Artificial intelligence has not yet been truly monetized. Now, theres a lot to unpack in that statement. For starters, tech companies have been integrating AI into their software for a generation and making tons of money off it. From autocorrect to playlists to the monsters in World of Warcraft, companies have been profiting off software decision-making for a long time.

The new AI, however, is a different thing entirely. The news-making artificial intelligence has come in the form of predictive algorithms like ChatGPTs chatbot software and DALL-Es image generator. These tools remain experimental. They are inventions and innovations but, at the time of writing, not yet products. Part of that is because engineers still arent quite sure what they are yet.

Advocates say that current AI software represents a fundamentally new tool, one that will change the way we interact with information and each other. Critics argue that they are just high-volume autocorrects, machines best suited for reorganizing existing work at best and stealing it at worst, but incapable of creating new value.

In both cases, monetization is a challenge. If tools like ChatGPT represent a true leap forward, then companies will need some time to figure out their commercial use. If, instead, they fundamentally rely on copying and pasting the work of others, then they may be more novelty than revolution.

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However, that doesnt mean that there arent opportunities to invest and profit yourself. Here are some of the best ways you can benefit financially from the early stages of AI development.

If youre ready to be matched with local advisors that can help you achieve your financial goals, get started now.

Invest In Individual Stocks Like Google and Microsoft

Alphabet (GOOG), or Google, and Microsoft (MSFT), which kept its maiden name, are some of the earliest companies racing for commercial AI applications. In both cases, their goal is to search. Both companies want to turn their search engines into a conversational source of inquiry, analysis and advice.

Instead of searching for information by a string of keywords, you would just ask the search engine questions and it would pop out the answer based on whats out there on the web. In this way, AIs best and worst qualities align with the business model of search. The goal is to paraphrase articles like this onto Google/Microsoft sites, so those companies can collect the ad revenue without having to pay for the work.

Googles Bard AI remains experimental and, true to the products core design, Bings AI search remains underwhelming. However, both companies hope to make this a major product at some point in the future.

This is a theme that applies broadly: Invest in companies that are will use AI in their products. As currently designed, AI will most likely be a backend feature in an enormous range of technology products. So, for example, while your phone is the front-end product, meaning the product you directly interact with, AI will become part of the back-end, meaning one of the many moving pieces that make your phone work.

Look for companies that can use AI in their products. Invest in them directly, so that you can collect their gains from this new technology.

Use Robo-Traders

invest in ai

Robo-traders have emerged as a major section of the market and for a good reason.

A robo-trader is a company that offers algorithmically managed portfolios. In essence, you invest your money according to a series of goals or conditions that you establish, then the brokerage manages that portfolio based on its own software model. These have shown particularly good results for investors because they tend to seek long-term investments, which tend to outperform short-term and high-volume trading.

Artificial intelligence has the potential to improve this further. Investors are already experimenting with AI-built portfolios and investment strategies. This trend will only continue to grow and the companies that build their portfolios with AI from the ground up will stand to benefit significantly.

Invest In AI Funds

As with all industries, an excellent way to invest in AI is through relevant funds. In fact, theres something of a gold rush on artificial intelligence ETFs right now. The market is filled with companies that are looking to capitalize on companies that operate in or around this technology.

For an investor, this is both an opportunity and a problem. The opportunities are out there, but how do you identify good investments? One good approach is to start by deciding how you want to invest in AI. There are ETFs, for example, such as Global X Robotics & Artificial Intelligence ETF (BOTZ) and ROBO Global Robotics and Automation Index ETF (ROBO), among others that let you invest in this market.

These funds invest in stocks and assets that support AI, such as companies that make the chips and hardware that AI companies depend on. Other funds will try to invest directly, buying into companies that are developing AI software itself, while others will invest in the companies that will use AI in their own products.

The best place to start with an AI-related fund is to look at how it invests. That will help you figure out if this is something youre interested in.

The Bottom Line

invest in ai

Artificial intelligence could very well be the next big boom. However, it can be difficult to determine the right areas that could make strong investments. Both directly and indirectly, AI might present plenty of opportunities that you can profit from. Finding the right one for you will depend on a number of factors including your expectation of risk.

Technology Investment Tips

Investing in any new technology is a risk. When it pays off, it can pay off big, but there are no guarantees. A financial advisor can help you determine the best investment plan for you when it comes to AI. Finding a financial advisor doesnt have to be hard.SmartAssets free tool matches you with up to three vetted financial advisors who serve your area, and you can interview your advisor matches at no cost to decide which one is right for you. If youre ready to find an advisor who can help you achieve your financial goals, get started now.

Finance and technology go hand-in-hand and the industry dedicated to that idea is called fintech. Its important to fully understand how the industry operates if youre wanting to invest.

Photo credit: iStock.com/Thai Liang Lim, iStock.com/Laurence Dutton, iStock.com/imaginima

The post How to Invest in Artificial Intelligence appeared first on SmartAsset Blog.

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Smart Ways to Invest in Artificial Intelligence - Yahoo Finance

"Until meaningful government safeguards are in place to protect the public from the harms of generative AI, we need a pause."

So says a report on the dangers of artificial intelligence (AI) published Tuesday by Public Citizen. Titled Sorry in Advance! Rapid Rush to Deploy Generative AI Risks a Wide Array of Automated Harms, the analysis by researchers Rick Claypool and Cheyenne Hunt aims to "reframe the conversation around generative AI to ensure that the public and policymakers have a say in how these new technologies might upend our lives."

Following the November release of OpenAI's ChatGPT, generative AI tools have been receiving "a huge amount of buzzespecially among the Big Tech corporations best positioned to profit from them," the report notes. "The most enthusiastic boosters say AI will change the world in ways that make everyone richand some detractors say it could kill us all. Separate from frightening threats that may materialize as the technology evolves are real-world harms the rush to release and monetize these tools can causeand, in many cases, is already causing."

Claypool and Hunt categorized these harms into "five broad areas of concern":

In a statement, Public Citizen warned that "businesses are deploying potentially dangerous AI tools faster than their harms can be understood or mitigated."

"History offers no reason to believe that corporations can self-regulate away the known risksespecially since many of these risks are as much a part of generative AI as they are of corporate greed," the statement continues. "Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

On Thursday, April 27, Public Citizen is hosting a hybrid in-person/Zoom conference in Washington, D.C., during which U.S. Rep. Ted Lieu (D-Calif.) and 10 other panelists will discuss the threats posed by AI and how to rein in the rapidly growing yet virtually unregulated industry. People interested in participating must register by this Friday.

"Businesses rushing to introduce these new technologies are gambling with peoples' lives and livelihoods, and arguably with the very foundations of a free society and livable world."

Demands to regulate AI are mounting. Last month, Geoffrey Hinton, considered the "godfather of artificial intelligence," compared the quickly advancing technology's potential impacts to "the Industrial Revolution, or electricity, or maybe the wheel."

Asked by CBS News' Brook Silva-Braga about the possibility of the technology "wiping out humanity," Hinton warned that "it's not inconceivable."

That frightening potential doesn't necessarily lie with existing AI tools such as ChatGPT, but rather with what is called "artificial general intelligence" (AGI), through which computers develop and act on their own ideas.

"Until quite recently, I thought it was going to be like 20 to 50 years before we have general-purpose AI," Hinton told CBS News. "Now I think it may be 20 years or less." Eventually, Hinton admitted that he wouldn't rule out the possibility of AGI arriving within five yearsa major departure from a few years ago when he "would have said, 'No way.'"

"We have to think hard about how to control that," said Hinton. Asked by Silva-Braga if that's possible, Hinton said, "We don't know, we haven't been there yet, but we can try."

The AI pioneer is far from alone. In February, OpenAI CEO Sam Altman wrote in a company blog post: "The risks could be extraordinary. A misaligned superintelligent AGI could cause grievous harm to the world."

More than 26,000 people have signed a recently published open letter that calls for a six-month moratorium on training AI systems beyond the level of OpenAI's latest chatbot, GPT-4, although Altman is not among them.

"Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable," says the letter.

While AGI may still be a few years away, Public Citizen's new report makes clear that existing AI toolsincluding chatbots spewing lies, face-swapping apps generating fake videos, and cloned voices committing fraudare already causing or threatening to cause serious harm, including intensifying inequality, undermining democracy, displacing workers, preying on consumers, and exacerbating the climate crisis.

These threats "are all very real and highly likely to occur if corporations are permitted to deploy generative AI without enforceable guardrails," Claypool and Hunt wrote. "But there is nothing inevitable about them."

They continued:

Amid "growing regulatory interest" in an AI "accountability mechanism," the Biden administration announced last week that it is seeking public input on measures that could be implemented to ensure that "AI systems are legal, effective, ethical, safe, and otherwise trustworthy."

According toAxios, Senate Majority Leader Chuck Schumer (D-N.Y.) is "taking early steps toward legislation to regulate artificial intelligence technology."

In the words of Claypool and Hunt: "We need strong safeguards and government regulationand we need them in place before corporations disseminate AI technology widely. Until then, we need a pause."

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Experts Demand 'Pause' on Spread of Artificial Intelligence Until ... - Common Dreams

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SACRAMENTO The California Department of Financial Protection and Innovation (DFPI) announced today it has issued desist and refrain orders against five entities to stop fraudulent investment schemes tied to artificial intelligence (AI).

Todays enforcement actions continue the DFPIs crack down on investor fraud. Scammers are taking advantage of the recent buzz around artificial intelligence to entice investors into bogus schemes, said DFPI Commissioner Clothilde Hewlett. We will continue our efforts to protect California consumers and investors by going after these unscrupulous actors.

The orders find that the named entities and individuals violated California securities laws by offering and selling unqualified securities and making material misrepresentations and omissions to investors. The entities solicited funds from investors by claiming to offer high yield investment programs (HYIP) that generate incredible returns by using AI to trade crypto assets. As part of their solicitations, they used multi-level marketing schemes that reward investors for recruiting new investors.

The subjects of todays desist and refrain orders are the following entities and individuals:

The Anatomy of the Scams

Taking advantage of the hype around AI, these entities claimed to use AI to conduct the purported crypto trading. The pitch was simple: investors were told that if they invested funds, these entities would use their knowledge, skill, experience, and AI to trade crypto assets and generate incredible profits for investors. In each case, these claims are false.

Each of these entities went to great lengths to appear as if they were legitimate businesses. They created professional websites, maintained social media accounts, and were promoted on social media by influencers and investors that shared stories of the money they were supposedly making.

For investors, these schemes may seem as if they are operating as promised for a certain amount of time. For weeks, months, or even years, investors see their account balances steadily increase. In the early stages, HYIPs will process investors withdrawal requests to gain investors trust and encourage them to recruit others. However, a time will come when the scheme stops processing withdrawals and then the website goes dark, leaving investors without a way to access their funds. By then its too late and the scammers have disappeared with investors money.

DFPIs Crackdown on High Yield Investment Programs

These orders continue the DFPIs crackdown on HYIPs. These programs use social media and influencers to quickly raise hype about the promised returns and low risk of the investment, then the operators quickly disappear leaving investors with no recourse to retrieve their money. Learn more about HYIPs:

The DFPI expects any person offering securities, lending, or other financial services in California to comply with our financial laws. Investors may file a complaint directly with the DFPI if they suspect a company of using unlawful, unfair, deceptive, or abusive practice online (dfpi.ca.gov/file-a-complaint) or call toll-free at (866) 275-2677.

About DFPI

The DFPI protects consumers, regulates financial services, and fosters responsible innovation. The DFPI protects consumers by establishing and enforcing financial regulations that promote transparency and accountability. We empower all Californians to access a fair and equitable financial marketplace through education and preventing potential risks, fraud, and abuse. Learn more atdfpi.ca.gov.

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DFPI Launches Sweep of Investment Fraud Claiming Ties to ... - California Department of Financial Protection and Innovation

SUMMARY

Illinois and other jurisdictions have adopted, or are considering, laws establishing parameters for employer use of AI during the hiring process.

The current attention being given to ChatGPT and other technologies using artificial intelligence (AI) is prompting companies to consider (or take another look) at how AI can and/or should play a role in their operations. From an employment law perspective, employers in Illinois and elsewhere should be aware of existing laws and guidance, and also should keep an eye out for the additional restrictions that will undoubtedly come as the use of AI becomes more prevalent.

In 2020, Illinois adopted the Artificial Intelligence Video Interview Act (820 ILCS 42/1), which establishes parameters for employer use of AI during the hiring process. If an employer intends to ask applicants to record video interviews so that it can use an AI analysis of such videos as part of the evaluation process, the employer must:

Sharing of such videos is limited to those with the expertise or technology necessary to evaluate the applicants fitness for a position. The videos (including all copies) must be destroyed within 30 days of a request by the applicant. These restrictions presumably apply to both new hires and employees who are seeking new positions within a company.

Illinois is not the only jurisdiction with AI restrictions on the books or under consideration. Bryan Cave Leighton Paisners Data Privacy group has prepared a summary of current and pending AI legislation around the United States.

California is among the jurisdictions currently reviewing proposed laws and regulations on the subject of the use of AI when making employment decisions, while Maryland enacted a law similar to Illinois in 2020, placing restrictions on the use of facial recognition services during pre-employment interviews until the applicant provides consent.

A more extensive law will be enforced in New York City beginning July 5, 2023: The New York City Automated Employment Decision Tools Law (AEDTL) which, among other things, requires employers to (a) conduct an audit for potential bias before using any artificial intelligence tools that screen candidates for hire or promotion, (b) give advance notice to candidates concerning the use of such tools, and (c) provide information on their websites about the tools and data collected. More information on the AEDTL is available here.

The potential for bias in the use of artificial intelligence tools is a key concern of the federal Equal Employment Opportunity Commission (EEOC) as well. The EEOC launched an agency-wide initiative on the subject in 2021, with a goal of ensuring that, the use of software, including artificial intelligence (AI), machine learning, and other emerging technologies used in hiring and other employment decisions comply with the federal civil rights laws that the EEOC enforces.

In May 2022, the EEOC issued guidance on the subject of, The Americans with Disabilities Act and the Use of Software, Algorithms, and Artificial Intelligence to Assess Job Applicants and Employees. This guidance provides definitions of key terms and explains how the use of algorithmic decision-making tools may violate the Americans with Disabilities Act (ADA), and notes that the use of a third-party vendor to develop and/or administer such a tool is not likely to insulate the employer from liability in connection with the results of using that tool. The EEOC held a public hearing on the issue of employment discrimination and the use of AI in January 2023, and is likely to continue its focus on this developing area.

As the use of AI in the hiring and selection process continues to evolve, employers should: (1) become familiar with artificial intelligence concepts; (2) examine, understand, be able to explain, and monitor their automated recruiting tools and practices; and (3) take steps to avoid bias and comply with applicable law.

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Reminder For Illinois (And Other) Employers: Restrictions Apply ... - JD Supra