Artificial Intelligence Stocks: The 10 Best AI Companies
Artificial intelligence, automation and robotics are disrupting virtually every industry. Remarkable advances in AI technology — including OpenAI’s ChatGPT AI chatbot, GitHub’s Copilot AI code generation software and Google’s Gemini AI model — are now familiar names for many.
[Sign up for stock news with our Invested newsletter.]
Whether it be machine learning, large language models, smart applications and appliances, digital assistants, synthetic media software, or autonomous vehicles, companies that aren’t investing in AI products and services risk becoming obsolete. Countless companies stand to benefit from AI, but a handful of stocks have AI and automation as a central part of their businesses. Here are 10 of the best AI stocks to buy, according to Argus:
Stock Implied upside over Aug. 8 closing price Microsoft Corp. (ticker: MSFT) 30.6% Alphabet Inc. (GOOG, GOOGL) 23.4% Amazon.com Inc. (AMZN) 23.6% Nvidia Corp. (NVDA) 42.9% Meta Platforms Inc. (META) 17.7% Taiwan Semiconductor Manufacturing Co. Ltd. (TSM) 21.5% Adobe Inc. (ADBE) 27.3% ASML Holding NV (ASML) 42.6% International Business Machines (IBM) 17.8% Arista Networks Inc. (ANET) 16.6%
Microsoft Corp. (MSFT)
Microsoft has invested $13 billion in OpenAI and has integrated ChatGPT into its Bing search engine. Microsoft has also combined all its AI copilots into a single AI experience called Microsoft Copilot. In May, the company published its inaugural Responsible AI Transparency Report, publicly detailing the company’s AI practices, spelling out its AI goals and highlighting its accountability initiatives. Analyst Joseph Bonner says Microsoft is investing heavily in AI via both internal development and outside stakes in AI startups. Microsoft CEO Satya Nadella aims to prioritize generative AI opportunities. Argus has a “buy” rating and $526 price target for MSFT stock, which closed at $402.69 on Aug. 8.
Alphabet Inc. (GOOG, GOOGL)
Google and YouTube parent company Alphabet uses AI and automation in virtually every facet of its business, from ad pricing to content promotion to Gmail spam filters. Google launched its Bard AI chatbot in March 2023. In December 2023, Google announced Gemini, its most capable and expansive AI model ever. In May, Google launched AI Overview, a service that provides AI-generated summaries on the top of Google search results. Bonner says Google is working to integrate its Gemini advanced AI model throughout its tech stack. Argus has a “buy” rating and $200 price target for GOOGL stock, which closed at $162.03 on Aug. 8.
Amazon.com Inc. (AMZN)
Amazon has integrated AI into every aspect of its business, including targeted advertisements, marketplace search and recommendation algorithms, and Amazon Web Services (AWS). Amazon offers a wide range of AI and machine learning services to its AWS cloud customers, including advanced text analytics, automated code reviews and chatbots. Amazon is reportedly investing $100 billion over the next decade in building a network of AWS data centers that can handle the tremendous AI workload. Analyst Jim Kelleher says the push for AI cloud services has reinvigorated AWS. Argus has a “buy” rating and $205 price target for AMZN stock, which closed at $165.80 on Aug. 8.
Nvidia Corp. (NVDA)
High-end chipmaker Nvidia provides the massive processing power needed to run advanced AI applications. Nvidia has been one of the best-performing stocks in the entire market in recent years, and it’s largely due to the company’s AI exposure. CEO Jensen Huang recently announced Nvidia will begin designing and rolling out new AI chips on an annual basis rather than the two-year chip refresh cycles it has used in the past. Kelleher says Nvidia’s Blackwell platform enables generative AI on trillion-parameter large language models. Argus has a “buy” rating and $150 price target for NVDA stock, which closed at $104.97 on Aug. 8.
Meta Platforms Inc. (META)
Meta Platforms is a market leader in social media and online advertising and is the parent company of Facebook, Instagram and other platforms. Meta is reportedly planning to release free AI customer-relations chatbots for businesses on its WhatsApp messaging platform. The move will be a test of CEO Mark Zuckerberg’s bold strategy to make Meta’s AI technology free and open to the public in an effort to gain market share and drive down competitors’ prices. Bonner says Zuckerberg has repeatedly built large customer bases and then effectively monetized them. Argus has a “buy” rating and $600 price target for META stock, which closed at $509.63 on Aug. 8.
[READ: Are We in an AI Bubble?]
Taiwan Semiconductor Manufacturing Co. Ltd. (TSM)
Taiwan Semiconductor Manufacturing is the world’s largest pure-play semiconductor foundry. TSM manufactures all the advanced AI semiconductors for Nvidia and other AI chipmakers. In June, CEO C.C. Wei said AI-driven demand makes him “very optimistic” about Taiwan Semiconductor’s outlook for the next several years. Kelleher says AI technology moving into the mainstream, coupled with lower inflation and a rebound in electronic device demand, will support solid revenue growth for TSM. The company expects global semiconductor market demand will grow 10% overall in 2024. Argus has a “buy” rating and $200 price target for TSM stock, which closed at $164.55 on Aug. 8.
Adobe Inc. (ADBE)
Adobe produces creative content software and other applications used for marketing and e-commerce. The company’s Firefly generative machine learning model is generating customer interest across Photoshop, Illustrator and other platforms. Adobe has also applied its Sensei AI and machine learning technology to its Adobe Analytics, Campaign and Target products. Adobe recently said it will not train its AI models on users’ content after artists accused the company of selling AI imitations of their work. Bonner says Adobe will continue to integrate additional AI features across its product set. Argus has a “buy” rating and $675 price target for ADBE stock, which closed at $530.24 on Aug. 8.
ASML Holding NV (ASML)
ASML produces photolithography systems and other processing equipment used in semiconductor fabrication. ASML is the only major producer of the extreme ultraviolet lithography equipment necessary to produce advanced AI chips. Taiwan Semiconductor and Samsung Electronics Co. Ltd. (OTC: SSNLF) are two of ASML’s largest customers. Nvidia relies on Samsung and TSM to manufacture the AI chips that Microsoft and Google are buying in massive quantities for their AI-capable data centers. Kelleher says generative AI applications and premium-tier edge devices will continue to support demand for ASML products. Argus has a “buy” rating and $1,250 price target for ASML stock, which closed at $876.65 on Aug. 8.
International Business Machines (IBM)
For years, IBM has been developing ways to adapt its AI supercomputer Watson to revolutionize health care, finance, law and academia. IBM’s portfolio of Watson AI solutions includes applications to improve customer service, automate workflow processes and predict outcomes. IBM’s Watson Studio even helps enterprise customers build proprietary AI applications. In June, IBM launched several new IBM watsonx AI assistant enhancements. Kelleher says AI and hybrid cloud sales have helped offset weakness in IBM’s consulting business. He says AI will play a central role in IBM’s future. Argus has a “buy” rating and $225 price target for IBM stock, which closed at $190.94 on Aug. 8.
Arista Networks Inc. (ANET)
Arista Networks supplies cloud networking solutions to internet companies, cloud service providers and enterprise data centers. Arista’s high-performance cloud networking solutions and high-throughput data center switches provide the processing power required for intensive AI workloads. Arista credited demand for networking gear from AI applications and cloud computing companies for its recent sales growth guidance that exceeded Wall Street’s expectations. Kelleher says Arista is the leader in enterprise and data center cloud networking and is uniquely positioned to benefit from the AI cloud services boom. Argus has a “buy” rating and $390 price target for ANET stock, which closed at $334.50 on Aug. 8.
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Artificial Intelligence Stocks: The 10 Best AI Companies originally appeared on usnews.com
Update 08/09/24: This story was previously published at an earlier date and has been updated with new information.
Artificial Intelligence Stocks: The 10 Best AI Companies
Artificial intelligence, automation and robotics are disrupting virtually every industry. Remarkable advances in AI technology — including OpenAI’s ChatGPT AI chatbot, GitHub’s Copilot AI code generation software and Google’s Gemini AI model — are now familiar names for many.
[Sign up for stock news with our Invested newsletter.]
Whether it be machine learning, large language models, smart applications and appliances, digital assistants, synthetic media software, or autonomous vehicles, companies that aren’t investing in AI products and services risk becoming obsolete. Countless companies stand to benefit from AI, but a handful of stocks have AI and automation as a central part of their businesses. Here are 10 of the best AI stocks to buy, according to Argus:
Stock Implied upside over Aug. 8 closing price Microsoft Corp. (ticker: MSFT) 30.6% Alphabet Inc. (GOOG, GOOGL) 23.4% Amazon.com Inc. (AMZN) 23.6% Nvidia Corp. (NVDA) 42.9% Meta Platforms Inc. (META) 17.7% Taiwan Semiconductor Manufacturing Co. Ltd. (TSM) 21.5% Adobe Inc. (ADBE) 27.3% ASML Holding NV (ASML) 42.6% International Business Machines (IBM) 17.8% Arista Networks Inc. (ANET) 16.6%
Microsoft Corp. (MSFT)
Microsoft has invested $13 billion in OpenAI and has integrated ChatGPT into its Bing search engine. Microsoft has also combined all its AI copilots into a single AI experience called Microsoft Copilot. In May, the company published its inaugural Responsible AI Transparency Report, publicly detailing the company’s AI practices, spelling out its AI goals and highlighting its accountability initiatives. Analyst Joseph Bonner says Microsoft is investing heavily in AI via both internal development and outside stakes in AI startups. Microsoft CEO Satya Nadella aims to prioritize generative AI opportunities. Argus has a “buy” rating and $526 price target for MSFT stock, which closed at $402.69 on Aug. 8.
Alphabet Inc. (GOOG, GOOGL)
Google and YouTube parent company Alphabet uses AI and automation in virtually every facet of its business, from ad pricing to content promotion to Gmail spam filters. Google launched its Bard AI chatbot in March 2023. In December 2023, Google announced Gemini, its most capable and expansive AI model ever. In May, Google launched AI Overview, a service that provides AI-generated summaries on the top of Google search results. Bonner says Google is working to integrate its Gemini advanced AI model throughout its tech stack. Argus has a “buy” rating and $200 price target for GOOGL stock, which closed at $162.03 on Aug. 8.
Amazon.com Inc. (AMZN)
Amazon has integrated AI into every aspect of its business, including targeted advertisements, marketplace search and recommendation algorithms, and Amazon Web Services (AWS). Amazon offers a wide range of AI and machine learning services to its AWS cloud customers, including advanced text analytics, automated code reviews and chatbots. Amazon is reportedly investing $100 billion over the next decade in building a network of AWS data centers that can handle the tremendous AI workload. Analyst Jim Kelleher says the push for AI cloud services has reinvigorated AWS. Argus has a “buy” rating and $205 price target for AMZN stock, which closed at $165.80 on Aug. 8.
Nvidia Corp. (NVDA)
High-end chipmaker Nvidia provides the massive processing power needed to run advanced AI applications. Nvidia has been one of the best-performing stocks in the entire market in recent years, and it’s largely due to the company’s AI exposure. CEO Jensen Huang recently announced Nvidia will begin designing and rolling out new AI chips on an annual basis rather than the two-year chip refresh cycles it has used in the past. Kelleher says Nvidia’s Blackwell platform enables generative AI on trillion-parameter large language models. Argus has a “buy” rating and $150 price target for NVDA stock, which closed at $104.97 on Aug. 8.
Meta Platforms Inc. (META)
Meta Platforms is a market leader in social media and online advertising and is the parent company of Facebook, Instagram and other platforms. Meta is reportedly planning to release free AI customer-relations chatbots for businesses on its WhatsApp messaging platform. The move will be a test of CEO Mark Zuckerberg’s bold strategy to make Meta’s AI technology free and open to the public in an effort to gain market share and drive down competitors’ prices. Bonner says Zuckerberg has repeatedly built large customer bases and then effectively monetized them. Argus has a “buy” rating and $600 price target for META stock, which closed at $509.63 on Aug. 8.
[READ: Are We in an AI Bubble?]
Taiwan Semiconductor Manufacturing Co. Ltd. (TSM)
Taiwan Semiconductor Manufacturing is the world’s largest pure-play semiconductor foundry. TSM manufactures all the advanced AI semiconductors for Nvidia and other AI chipmakers. In June, CEO C.C. Wei said AI-driven demand makes him “very optimistic” about Taiwan Semiconductor’s outlook for the next several years. Kelleher says AI technology moving into the mainstream, coupled with lower inflation and a rebound in electronic device demand, will support solid revenue growth for TSM. The company expects global semiconductor market demand will grow 10% overall in 2024. Argus has a “buy” rating and $200 price target for TSM stock, which closed at $164.55 on Aug. 8.
Adobe Inc. (ADBE)
Adobe produces creative content software and other applications used for marketing and e-commerce. The company’s Firefly generative machine learning model is generating customer interest across Photoshop, Illustrator and other platforms. Adobe has also applied its Sensei AI and machine learning technology to its Adobe Analytics, Campaign and Target products. Adobe recently said it will not train its AI models on users’ content after artists accused the company of selling AI imitations of their work. Bonner says Adobe will continue to integrate additional AI features across its product set. Argus has a “buy” rating and $675 price target for ADBE stock, which closed at $530.24 on Aug. 8.
ASML Holding NV (ASML)
ASML produces photolithography systems and other processing equipment used in semiconductor fabrication. ASML is the only major producer of the extreme ultraviolet lithography equipment necessary to produce advanced AI chips. Taiwan Semiconductor and Samsung Electronics Co. Ltd. (OTC: SSNLF) are two of ASML’s largest customers. Nvidia relies on Samsung and TSM to manufacture the AI chips that Microsoft and Google are buying in massive quantities for their AI-capable data centers. Kelleher says generative AI applications and premium-tier edge devices will continue to support demand for ASML products. Argus has a “buy” rating and $1,250 price target for ASML stock, which closed at $876.65 on Aug. 8.
International Business Machines (IBM)
For years, IBM has been developing ways to adapt its AI supercomputer Watson to revolutionize health care, finance, law and academia. IBM’s portfolio of Watson AI solutions includes applications to improve customer service, automate workflow processes and predict outcomes. IBM’s Watson Studio even helps enterprise customers build proprietary AI applications. In June, IBM launched several new IBM watsonx AI assistant enhancements. Kelleher says AI and hybrid cloud sales have helped offset weakness in IBM’s consulting business. He says AI will play a central role in IBM’s future. Argus has a “buy” rating and $225 price target for IBM stock, which closed at $190.94 on Aug. 8.
Arista Networks Inc. (ANET)
Arista Networks supplies cloud networking solutions to internet companies, cloud service providers and enterprise data centers. Arista’s high-performance cloud networking solutions and high-throughput data center switches provide the processing power required for intensive AI workloads. Arista credited demand for networking gear from AI applications and cloud computing companies for its recent sales growth guidance that exceeded Wall Street’s expectations. Kelleher says Arista is the leader in enterprise and data center cloud networking and is uniquely positioned to benefit from the AI cloud services boom. Argus has a “buy” rating and $390 price target for ANET stock, which closed at $334.50 on Aug. 8.
More from U.S. News
9 of the Best REITs to Buy for 2024
8 Best Defense Stocks to Buy Now
Recession 2024: What to Watch and How to Prepare
Artificial Intelligence Stocks: The 10 Best AI Companies originally appeared on usnews.com
Update 08/09/24: This story was previously published at an earlier date and has been updated with new information.
Transforming Your Organization with the Power of Business Intelligence
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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.
Understanding Business Intelligence
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.
The Four Pillars of Business Intelligence
Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.
Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.
Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.
Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.
The Transformative Impact of Business Intelligence Improved Decision Making
BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.
Operational Efficiency
The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.
Improved Bottom Line
Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.
Competitive Advantage
Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.
The Future of Business Intelligence
Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.
Conclusion
Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.
repeating the info from intro [SD1]
This doesn’t fit right here… please change the placement [SD2]
Intuit’s Growth and Pricing Power Fuel Buy Rating Amid Strong Small Business and Credit Karma Outlook
Analyst Daniel Jester of BMO Capital maintained a Buy rating on Intuit (INTU – Research Report), retaining the price target of $700.00.
Daniel Jester has given his Buy rating due to a combination of factors that suggest Intuit’s solid growth prospects and pricing power. He foresees potential revenue increases in the Small Business and Credit Karma divisions, which could provide support during a traditionally slower fourth quarter. The projections for Intuit’s fiscal year 2025 include approximately 12% year-over-year revenue growth and a 13% increase in earnings per share, reflecting the impact of price adjustments in the Small Business segment and benefits from prior restructuring. Furthermore, he acknowledges Intuit’s strong core business and the expansive opportunities for leveraging artificial intelligence and machine learning across its product range, underpinning an attractive long-term growth outlook. In particular, the Small Business segment is expected to continue its trend of robust growth, estimated at around 18% year-over-year, partly due to price increases within the QuickBooks ecosystem. These increases, ranging from high single digits to high teens, are set to take effect from the first quarter of the fiscal year and could contribute to growth even with slower unit sales. Additionally, despite the seasonal insignificance of the fourth quarter for the Consumer segment, which includes TurboTax, Jester anticipates that consensus estimates for the fiscal year 2025 may underestimate the impact of seasonality on revenue growth. Credit Karma is also expected to experience moderate upside in the quarter, with trends in personal loan applications indicating potential improvements in user activity. These analyses, coupled with Intuit’s leadership in its market segments and the recent underperformance of its shares relative to peers, present an attractive entry point, leading to the Buy rating.
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Intuit (INTU) Company Description:
Incorporated in 1983, California-based Intuit, Inc., a software company, provides financial management solutions and compliance products and services for small businesses, accountants, and individuals. It operates through the following segments: Small Business and Self-Employed Group; Consumer Group; ProConnect Group and Credit Karma.
Transforming Your Organization with the Power of Business Intelligence
Share
Share
Share
With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.
Understanding Business Intelligence
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.
The Four Pillars of Business Intelligence
Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.
Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.
Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.
Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.
The Transformative Impact of Business Intelligence Improved Decision Making
BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.
Operational Efficiency
The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.
Improved Bottom Line
Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.
Competitive Advantage
Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.
Ethical Considerations in BI
The Future of Business Intelligence
Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.
Conclusion
Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.
repeating the info from intro [SD1]
This doesn’t fit right here… please change the placement [SD2]
Welcome to the AI revolution: From horsepower to manpower to machine-power gremlin/Getty images
Before the invention of the internal combustion engine and the harnessing of electricity, humans weren’t the only members of the global workforce. Until the mid-20th century, horses were employed in the tens of millions across industries. In the USA alone their numbers reached 24 million, about as many as there are humans currently working in healthcare.
Also: How your business can best exploit AI: Tell your board these 4 things
“The draft animal population — the vast majority of which were horses and mules — grew six-fold between 1840 and 1900, from four to twenty-four million. This outpaced the growth in human population, which merely tripled during those same decades. By 1900, there was one horse or mule for every three humans in the United States. The majority of work animals lived and worked in cities and their surrounding hinterlands. The greatest uses of animal power were in agriculture and transportation,” from Animal Power by Anne Norton Greene.
Within cities, horses had provided most travel and transportation options for centuries. Apart from horseback riding itself, options included public transport by horse-drawn omnibuses, private coaches and carriages, and even ride-for-hire taxi services dating back as early as 1605 in London, provided by hackney carriages (four-wheeled) and later by hansom cabs (two-wheeled cabriolet carriages).
A shift from horsepower
However, with the advent of the internal combustion engine, the number of literal workhorses in the US had fallen to six million by 1960. That figure has since fallen further to only about 1.5 million, of a total US horse population of about 10 million, most of whom are owned as pets or used in competition.
The story is similar in Europe. In England, for example, just over three million horses were working at the beginning of the 20th century. That number had fallen below two million within a quarter of a century, despite the loss of human laborers to the First World War and the flu pandemic of 1918 to 1920 that took some 25 million to 50 million lives globally.
A century later, in 2020, it is estimated that there are less than a tenth of that figure, around 160,000 horses, some 70% of which are pets and the rest are mostly engaged in racing and in some niche areas like mounted police and brewery dray horses. There are, in short, nearly no horses today in regular employment from a heyday of tens of millions fully employed.
Also: Time for businesses to move past generative AI hype and find real value
So, what happened? Automated movement happened. Until the internal combustion engine, we did not have reliable technology capable of carrying and pulling loads from one place to another, except by rail. We used horses and, for a while, the greatest existential threat to city living was the rapidly accumulating piles of horse dung. We switched to mobile technology, via the automobile, as soon as possible.
And now we’ve taken the next step. We are creating a whole suite of technologies that enable the automobile to live up to its name even more fully. “Auto” means self, and it originally implied a carriage (hence the word “car”) freed from the power of the horse.
Now “auto” means being freed from the control of humans. It is technology by itself, autonomous, “under its own steam” so to speak. And in that sense, transport is starting to become something new. And the implications will be felt far beyond travel and transportation.
From manpower to machine-power
Until very recently, technology was first and foremost a tool. It was something humans built and then used to do a job — and to do it better, faster, and easier than we could without it. But still, we used technology.
What’s new with artificial intelligence (AI) is that we are not creating new tools to help us do a job. We are creating a new workforce to do the job for us. This trend is not absolute of course and we can always point to older technologies that may have done part of our job for us (factory automation began at least 200 years ago). However, we are now creating a cheaper, faster, better, scalable workforce, not a cheaper, faster, better, scalable toolset.
This new workforce is not going to replace us all any time soon. There are two main reasons for this fact. The first is that the hype of AI far exceeds its current capabilities, except in some narrow, rules-based scenarios (e.g. games, in which it can far outperform even the greatest human players).
Generative AI in particular appears almost magical in its ability to render text, images and even video. Yet its inability to understand any of its output, along with the volume of data and the power needed to train its models, surely limits it from replacing human workers.
Also: When’s the right time to invest in AI? 4 ways to help you decide
That said, AI-powered capabilities are growing in orders of magnitude annually. By leveraging AI’s predictive and analytical capabilities, companies make informed decisions that benefit their bottom line, society, and the environment.
However, new research shows only 30% of C-suite leaders feel confident in their change capabilities. Even fewer believe their teams are ready to embrace change. Lastly, 90% of IT leaders say it’s tough to integrate AI with other systems, citing two biggest challenges for AI adoption are data silos and application integrations.
The second reason AIs will not replace humans any time soon is the time it takes our institutions to understand and embrace the capabilities of proven technology. We saw this most clearly in 2020 when school districts and businesses had to cease operations during the coronavirus pandemic because they had not yet implemented full online operations despite the capabilities being in existence for 15 years or more.
We can expect late adopters to wait again until they’re presented with an existential threat before embracing AI and this lag will affect the whole. According to Accenture research, only 16% of the 1,000 organizations the consultant studied stand out as leaders capable of successfully managing the change necessary for adopting AI in business.
Also: 4 ways to help your organization overcome AI inertia
Given those two major caveats, we can track the gradual integration of AI into the workforce and the eventual, inevitable reduction in the number of human employees as AI becomes cheaper, more efficient, and more accurate than us at performing a wide range of functions.
It may be true that AI will create new opportunities that we can’t yet imagine, but they won’t be opportunities for more of us humans. In the short term, we may see more jobs, as not all technologies will develop at the same speed and will need our help to work effectively.
The machine-powered ecosystem
However, one day — and we expect that the real watershed moment will once again be fully autonomous mobility, from the vehicle to the android robot — the measure of manpower will become as figurative as horsepower is now.
We will likely be startled by the manpower of the average robot. And we’ll start to see the emergence of a new measure of productivity — “machine power” or similar. This measure will be needed to represent how machines will no longer just do “human” jobs faster, more accurately, and cheaply. They’ll also be doing jobs that we can’t and are far more complex, with more inputs to handle, more moving parts to orchestrate, and less time to solve.
Managing robotaxi fleets — the latest innovation in the centuries-old ride-for-hire service that no longer employs human drivers or horse “engines” — will be an early example of this new machine power. Managing fully autonomous companies will be another.
Also: Agile development can unlock the power of generative AI – here’s how
This transition will have large-scale societal implications, far beyond the scope of this piece. But to follow our logic to its conclusion, we humans will eventually go the way of the horse. There’ll likely be fewer of us, but we’ll live relatively healthier and happier lives. And once employment no longer sets our course, we’ll need to take seriously our one “job” of finding a new sense of purpose and joy.
Henry King, co-author of Boundless, and I are developing a framework for the different levels of capability that AI will need to demonstrate on its way to full autonomy in the workplace. In addition to the existing framework for autonomous driving, we were inspired by the SUDA operating model (Sense, Understand, Decide, Act) featured in our best-selling book “Boundless” and are incorporating this model into each level. We’ll be publishing that work on ZDNET soon.
This article was co-authored by Henry King, business innovation and transformation strategy leader and co-author of Boundless: A New Mindset for Unlimited Business Success.
Transforming Your Organization with the Power of Business Intelligence
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With the ability to drive strategic initiatives, make educated decisions and extract valuable insights from raw data, business intelligence (BI) has become a key enabler for organizational success. BI has revolutionized the way businesses operate and plan for the future in this age of intense competition and rapid technological advancement. One of the most powerful business intelligence tools available, Intellicus has provided tailored solutions to over 17,000 small and large businesses, enabling them to make data-driven decisions.
Understanding Business Intelligence
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. It combines internal and external data sources into a logical framework that helps produce insights that can be put into action. Business intelligence is a valuable resource that facilitates managers, executives and stakeholders to make informed decisions.
Business Intelligence (BI) is a technology-driven process that analyzes business data to provide actionable information that informs strategic and operational decisions. It involves collecting, storing, analyzing, and visualizing data to uncover patterns, trends, and insights that drive business performance. Essentially, BI transforms raw data into meaningful information that empowers organizations to make data-driven decisions.
The Four Pillars of Business Intelligence
Data Collection and Integration: Business Intelligence starts with the compilation of information from various sources, such as social media interactions, market trends, consumer profiles and sales statistics. This data must be integrated into a single platform in order to provide a comprehensive view and analysis.
Data Visualization and Analysis: BI tools analyze trends, patterns, and connections using sophisticated analytics. Visualization tools like dashboards, charts, and graphs transform complex data into understandable insights for efficient decision-making.
Predictive Analytics: BI doesn’t merely focus on the present; it anticipates the future. To predict future trends, predictive analytics uses machine learning models and statistical algorithms. This makes it possible for companies to plan ahead and adapt proactively.
Actionable Insights: BI aims to generate actionable insights, not just reports. These insights help optimize operations, identify new opportunities, and enhance overall performance.
The Transformative Impact of Business Intelligence Improved Decision Making
BI tools give businesses access to real-time data, which is essential for making timely, well-informed decisions. This eliminates the need for guesswork and intuition-based decisions in favor of data-driven ones. Additionally, BI tools, like dashboards and visualizations, present data in an understandable format, making it easier for decision-makers to quickly comprehend complex information and react to changes that may have an impact on the business.
Operational Efficiency
The operational efficiency of an organization can be greatly improved using business intelligence. By automating repetitive operations, BI solutions allow employees to concentrate on more important facets of the company. Furthermore, by highlighting areas in the business process that require improvement, BI tools enable firms to get rid of bottlenecks, simplify procedures and cut expenses. Customer satisfaction and service delivery are enhanced as a result.
Improved Bottom Line
Business Intelligence can assist companies in increasing revenue and sales by offering insightful information about consumer behavior. With the use of BI technologies, marketers can better focus their campaigns and boost sales by analyzing customer data to find trends, buying patterns and preferences. Additionally, organizations can use business intelligence to pinpoint successful consumer categories and concentrate their marketing efforts on them. Revenue growth and improved conversion rates are possible outcomes of this focused strategy.
Competitive Advantage
Business Intelligence provides a competitive edge in today’s data-driven world. Through the utilization of BI tools, companies can acquire comprehensive insights into the tactics, advantages and disadvantages of their rivals and utilize this data to formulate strategic plans. Similarly, it facilitates prompt market adaptation and can assist companies in recognizing customer behavior shifts and market trends.
Ethical Considerations in BI
The Future of Business Intelligence
Advancing technology promises a bright future for BI. AI and machine learning will enhance predictive analytics, enabling businesses to foresee trends and adapt quickly. Integrating BI with emerging technologies like IoT and blockchain will unlock new dimensions of data analysis and decision-making.
Conclusion
Business Intelligence has evolved from being a mere buzzword to a transformative force shaping the future of businesses. It empowers organizations to navigate complexities, capitalize on opportunities, and drive growth in an increasingly data-centric world. Embracing BI isn’t just an option; it’s a necessity for businesses aspiring to thrive in today’s competitive landscape.
repeating the info from intro [SD1]
This doesn’t fit right here… please change the placement [SD2]
Artificial Intelligence Stocks: The 10 Best AI Companies
Artificial intelligence, automation and robotics are disrupting virtually every industry. Remarkable advances in AI technology — including OpenAI’s ChatGPT AI chatbot, GitHub’s Copilot AI code generation software and Google’s Gemini AI model — are now familiar names for many.
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Whether it be machine learning, large language models, smart applications and appliances, digital assistants, synthetic media software, or autonomous vehicles, companies that aren’t investing in AI products and services risk becoming obsolete. Countless companies stand to benefit from AI, but a handful of stocks have AI and automation as a central part of their businesses. Here are 10 of the best AI stocks to buy, according to Argus:
Stock Implied upside over Aug. 8 closing price Microsoft Corp. (ticker: MSFT) 30.6% Alphabet Inc. (GOOG, GOOGL) 23.4% Amazon.com Inc. (AMZN) 23.6% Nvidia Corp. (NVDA) 42.9% Meta Platforms Inc. (META) 17.7% Taiwan Semiconductor Manufacturing Co. Ltd. (TSM) 21.5% Adobe Inc. (ADBE) 27.3% ASML Holding NV (ASML) 42.6% International Business Machines (IBM) 17.8% Arista Networks Inc. (ANET) 16.6%
Microsoft Corp. (MSFT)
Microsoft has invested $13 billion in OpenAI and has integrated ChatGPT into its Bing search engine. Microsoft has also combined all its AI copilots into a single AI experience called Microsoft Copilot. In May, the company published its inaugural Responsible AI Transparency Report, publicly detailing the company’s AI practices, spelling out its AI goals and highlighting its accountability initiatives. Analyst Joseph Bonner says Microsoft is investing heavily in AI via both internal development and outside stakes in AI startups. Microsoft CEO Satya Nadella aims to prioritize generative AI opportunities. Argus has a “buy” rating and $526 price target for MSFT stock, which closed at $402.69 on Aug. 8.
Alphabet Inc. (GOOG, GOOGL)
Google and YouTube parent company Alphabet uses AI and automation in virtually every facet of its business, from ad pricing to content promotion to Gmail spam filters. Google launched its Bard AI chatbot in March 2023. In December 2023, Google announced Gemini, its most capable and expansive AI model ever. In May, Google launched AI Overview, a service that provides AI-generated summaries on the top of Google search results. Bonner says Google is working to integrate its Gemini advanced AI model throughout its tech stack. Argus has a “buy” rating and $200 price target for GOOGL stock, which closed at $162.03 on Aug. 8.
Amazon.com Inc. (AMZN)
Amazon has integrated AI into every aspect of its business, including targeted advertisements, marketplace search and recommendation algorithms, and Amazon Web Services (AWS). Amazon offers a wide range of AI and machine learning services to its AWS cloud customers, including advanced text analytics, automated code reviews and chatbots. Amazon is reportedly investing $100 billion over the next decade in building a network of AWS data centers that can handle the tremendous AI workload. Analyst Jim Kelleher says the push for AI cloud services has reinvigorated AWS. Argus has a “buy” rating and $205 price target for AMZN stock, which closed at $165.80 on Aug. 8.
Nvidia Corp. (NVDA)
High-end chipmaker Nvidia provides the massive processing power needed to run advanced AI applications. Nvidia has been one of the best-performing stocks in the entire market in recent years, and it’s largely due to the company’s AI exposure. CEO Jensen Huang recently announced Nvidia will begin designing and rolling out new AI chips on an annual basis rather than the two-year chip refresh cycles it has used in the past. Kelleher says Nvidia’s Blackwell platform enables generative AI on trillion-parameter large language models. Argus has a “buy” rating and $150 price target for NVDA stock, which closed at $104.97 on Aug. 8.
Meta Platforms Inc. (META)
Meta Platforms is a market leader in social media and online advertising and is the parent company of Facebook, Instagram and other platforms. Meta is reportedly planning to release free AI customer-relations chatbots for businesses on its WhatsApp messaging platform. The move will be a test of CEO Mark Zuckerberg’s bold strategy to make Meta’s AI technology free and open to the public in an effort to gain market share and drive down competitors’ prices. Bonner says Zuckerberg has repeatedly built large customer bases and then effectively monetized them. Argus has a “buy” rating and $600 price target for META stock, which closed at $509.63 on Aug. 8.
[READ: Are We in an AI Bubble?]
Taiwan Semiconductor Manufacturing Co. Ltd. (TSM)
Taiwan Semiconductor Manufacturing is the world’s largest pure-play semiconductor foundry. TSM manufactures all the advanced AI semiconductors for Nvidia and other AI chipmakers. In June, CEO C.C. Wei said AI-driven demand makes him “very optimistic” about Taiwan Semiconductor’s outlook for the next several years. Kelleher says AI technology moving into the mainstream, coupled with lower inflation and a rebound in electronic device demand, will support solid revenue growth for TSM. The company expects global semiconductor market demand will grow 10% overall in 2024. Argus has a “buy” rating and $200 price target for TSM stock, which closed at $164.55 on Aug. 8.
Adobe Inc. (ADBE)
Adobe produces creative content software and other applications used for marketing and e-commerce. The company’s Firefly generative machine learning model is generating customer interest across Photoshop, Illustrator and other platforms. Adobe has also applied its Sensei AI and machine learning technology to its Adobe Analytics, Campaign and Target products. Adobe recently said it will not train its AI models on users’ content after artists accused the company of selling AI imitations of their work. Bonner says Adobe will continue to integrate additional AI features across its product set. Argus has a “buy” rating and $675 price target for ADBE stock, which closed at $530.24 on Aug. 8.
ASML Holding NV (ASML)
ASML produces photolithography systems and other processing equipment used in semiconductor fabrication. ASML is the only major producer of the extreme ultraviolet lithography equipment necessary to produce advanced AI chips. Taiwan Semiconductor and Samsung Electronics Co. Ltd. (OTC: SSNLF) are two of ASML’s largest customers. Nvidia relies on Samsung and TSM to manufacture the AI chips that Microsoft and Google are buying in massive quantities for their AI-capable data centers. Kelleher says generative AI applications and premium-tier edge devices will continue to support demand for ASML products. Argus has a “buy” rating and $1,250 price target for ASML stock, which closed at $876.65 on Aug. 8.
International Business Machines (IBM)
For years, IBM has been developing ways to adapt its AI supercomputer Watson to revolutionize health care, finance, law and academia. IBM’s portfolio of Watson AI solutions includes applications to improve customer service, automate workflow processes and predict outcomes. IBM’s Watson Studio even helps enterprise customers build proprietary AI applications. In June, IBM launched several new IBM watsonx AI assistant enhancements. Kelleher says AI and hybrid cloud sales have helped offset weakness in IBM’s consulting business. He says AI will play a central role in IBM’s future. Argus has a “buy” rating and $225 price target for IBM stock, which closed at $190.94 on Aug. 8.
Arista Networks Inc. (ANET)
Arista Networks supplies cloud networking solutions to internet companies, cloud service providers and enterprise data centers. Arista’s high-performance cloud networking solutions and high-throughput data center switches provide the processing power required for intensive AI workloads. Arista credited demand for networking gear from AI applications and cloud computing companies for its recent sales growth guidance that exceeded Wall Street’s expectations. Kelleher says Arista is the leader in enterprise and data center cloud networking and is uniquely positioned to benefit from the AI cloud services boom. Argus has a “buy” rating and $390 price target for ANET stock, which closed at $334.50 on Aug. 8.
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Artificial Intelligence Stocks: The 10 Best AI Companies originally appeared on usnews.com
Update 08/09/24: This story was previously published at an earlier date and has been updated with new information.