Wall Street, venture capitalists, technology executives, data scientists -- all have important reasons to understand the growth and opportunity in the artificial intelligence market to access business growth and opportunities. This gives them insights on funds invested in AI and analytics as well potential revenue growth and turnover. Indeed, the growth of AI, continuing research, development of easier open source libraries and applications in small to large scale industries are sure to revolutionize the industry the next two decades and the impact is getting felt in almost all the countries worldwide. To dive deep into the growth of AI and future trends, an insight into the type and size of the market is essential along with (a) AI-related industry market research forecasts and (b) data from reputable research sources for insight into AI valuation and forecasting. IBM's CEO claims a potential $2 trillion dollar market for "cognitive computing").

In late 2016, Adobe announced that Sensei, the company's AI technology, would begin to power and assist in some of its Digital Media applications, such as Photoshop and Illustrator. While that was only 3 short years ago, in the dawning of the AI era, Sensei's role makes Adobe one of the pioneers of machine learning- and deep learning-powered AI. What started in 2016 as narrow AI technology aimed at narrow use cases has become an AI engine that, according to Tatiana Mejia, group Product Marketing manager for Sensei, now powers dozens of different features across Adobe. "We don't tag any of the features with Sensei, it's just the engine behind Adobe products," said Mejia. Whether the technology is effective or not, the concept is advanced AI thinking.

If you are currently in the market for almost any kind of enterprise software, you will almost certainly run across at least one vendor claiming that its product includes artificial intelligence (AI) capabilities. Of course, some of these claims are no more than marketing hyperbole, or "AI washing." However, in many cases, software makers truly are integrating new capabilities related to analytics, vision, natural language, or other areas that deserve the AI label. The market researchers at IDC have gone so far as to call AI "inescapable." Similarly, Omdia Tractica predicted that worldwide revenue from AI software will climb from $10.1 billion in 2018 to $126.0 billion in 2025, led in large part by advancements in deep learning technology.

Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long.

Compared to a few years ago, the artificial intelligence (AI) market is starting to solidify around real-world applications with the pace of change being faster than it ever has been before, as startups and technology providers rush to create platforms and targeted niche solutions for solving specific enterprise problems. According to a new report from Tractica, the rising tide of AI adoption across multiple industries will drive significant growth during the next decade, and the market intelligence firm forecasts that annual worldwide AI software revenue will increase from $3.2 billion in 2016 in 2016 to $89.8 billion by 2025. This forecast is a significant upgrade of Tractica's previous projection for AI market revenue, which was published in 2Q17, due to an improved outlook for a number of specific use cases across multiple industries. "Artificial intelligence is already key to how consumer internet companies operate today, allowing them to roll out hyper-personalized services by following an'AI first' strategy," says research director Aditya Kaul. "The rest of the market in the enterprise and government sectors is still catching up on adopting AI and has yet to fully understand its value, including the breadth and depth of use cases, the technology choices surrounding AI, and the implementation strategies."

According to research by Tractica, machine learning applications are expected to bring more than $107 billion in annual enterprise revenue by 2025, up from just $7.6 billion in 2018. There are no fewer than 167 existing enterprise AI use cases for technologies like speech recognition, natural language processing and generation, computer vision and sentiment analysis. In this eBook, sponsored by Dow Jones, we look at real-life examples of ML and AI working in concert with the latest data analytics technologies to change the way people do business. We talk to experts in the field who share their insights into the current and upcoming developments in this space. This eBook is essential reading for any decision-maker looking for ways to transform their organization and prepare it for a digital future.

Inside you'll learn about the major market drivers and barriers, technologies, key players, and forecasts related to eight telecom AI use cases:

Artificial intelligence (AI) within the consumer, enterprise, government, and defense sectors is migrating from a conceptual "nice to have" to an essential technology driving improvements in quality, efficiency, and speed. According to a new report from Tractica, the top industry sectors where AI is likely to bring major transformation remain those in which there is a clear business case for incorporating AI, rather than pie-in-the-sky use cases that may not generate return on investment for many years. "The global AI market is entering a new phase in 2020 where the narrative is shifting from asking whether AI is viable to declaring that AI is now a requirement for most enterprises that are trying to compete on a global level," says principal analyst Keith Kirkpatrick. According to the market intelligence company, AI is likely to thrive in consumer (Internet services), automotive, financial services, telecommunications, and retail industries. Not surprisingly, the consumer sector has demonstrated its ability to capture AI, thanks to the combination of three key factors – large data sets, high-performance hardware and state of the art algorithms.

The manufacturing industry exhibits some contradictions when it comes to automation and technology. On the one hand, manufacturing was among the first industries to integrate any type of technology more than a century ago, as companies incorporated tools to aid in the production process. On the other hand, manufacturing companies are risk-averse when it comes to implementing new technology quickly, mainly due to the large amount of capital and time at stake. However, according to a new report from Tractica, manufacturing companies are now incorporating artificial intelligence (AI) technology within their environments at a modest, yet steady, pace. The market intelligence firm forecasts that annual worldwide manufacturing sector investment in AI software, hardware, and services will increase from $2.9 billion in 2018 to $13.2 billion by 2025.

I covered the AI Summit in New York last week because I wanted to learn more about AI and Machine Learning. According to Tractica, AI is being implemented globally. AI and Machine Learning used in many verticals and processes. For example, when I compose an email using GMAIL, I received suggestions on how to finish a sentence. To use the GMAIL suggestion, I can tap the right arrow button on my keyboard.