Artificial intelligence (AI) has become a hot topic for countries worldwide, and both public- and private-sector organizations have already started leveraging it as a response to continuous digital disruption. According to IDC's 2022 Artificial Intelligence Spending Guide, global AI spending reached $88.6 billion in 2021, and it is forecast to grow at a compound annual growth rate (CAGR) of 25.6% over the 2021–2025 period. Canada, China, and the United States are among the countries in which many organizations began their AI journeys early, supported by government initiatives. Saudi Arabia is no different in terms of its commitment to becoming an AI powerhouse. As an extension of the country's Vision 2030, the Saudi Data and AI Authority (SDAIA) was established in 2019, followed by the release of the National Strategy for Data and AI in 2020.

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In a 2016 article from Business Insider, General Electric described what an ideal intelligent factory would look like. Their vision for the "Brilliant Factory," as they called it, would start with automatic ordering based on detected customer need, and use 3D printing technologies to design, prototype, and test a new part in hours rather than days or weeks. Streamlining production would be next, with highly intelligent robots bearing a majority of the assembly workload. These stages would be continuously monitored by artificial intelligence (AI) technologies to detect abnormalities or faults, and eliminate downtime in the process. While posing an interesting trajectory for the manufacturing field, this "Brilliant Factory" remains in the future for now.

Memory specialist Micron (NASDAQ:MU) sells both DRAM, a type of computer memory that's used in virtually every kind of computing device, and NAND flash, which is rapidly gaining traction for high-performance data storage applications as it's quicker and more efficient than hard disk drive-based storage. Micron's business has continued to benefit from what seems like an insatiable amount of demand for both DRAM and NAND in applications such as mobile phones and data center servers. One of the sub-segments within data center servers is the market for servers that handle machine learning, commonly referred to as artificial intelligence, processing tasks. That sub-segment is small today, with data center chip giant Intel estimating the market at around 7% of total data center server shipments in 2016, but it's also, according to Intel, the fastest growing. The companies that make the processors that perform these machine learning computations are clearly very excited about the artificial intelligence opportunity as it means they'll get to sell a lot more computing power over the years.

Over the last couple years, I've spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). Some of these possibilities have already been realized (more on this later in the post). And, I could not be more excited to see them out in the world. Through it all, I've felt there are a handful of breath-taking realities that most people are not grasping when it comes to an AI-Powered world. Why the implications are far deeper for humanity than we imagine. Why in my areas of expertise, marketing, sales, customer service and analytics, the impact will be deep and wide. Why is this not yet another programmatic moment. Why the scale at which we can (/have to) solve the problems is already well beyond the grasp of the fundamental strategy most companies follow: We have a bigger revenue opportunity, but we don't know how to take advantage? Let's buy more hamster wheels, hire more hamsters and train them to spin faster!

I've felt there are a handful of breath-taking realities that most people are not grasping when it comes to an AI-Powered world. Why the implications are far deeper for humanity than we imagine. Why in my areas of expertise, marketing, sales, customer service and analytics, the impact will be deep and wide. Why is this not yet another programmatic moment. Why the scale at which we can (/have to) solve the problems is already well beyond the grasp of the fundamental strategy most companies follow: We have a bigger revenue opportunity, but we don't know how to take advantage?

Over the last couple years, I've spent an increasing amount of time diving into the possibilities Deep Learning (DL) offers in terms of what we can do with Artificial Intelligence (AI). Some of these possibilities have already been realized (more on this later in the post). And, I could not be more excited to see them out in the world. Through it all, I've felt there are a handful of breath-taking realities that most people are not grasping when it comes to an AI-Powered world. Why the implications are far deeper for humanity than we imagine. Why in my areas of expertise, marketing, sales, customer service and analytics, the impact will be deep and wide. Why is this not yet another programmatic moment. Why the scale at which we can (/have to) solve the problems is already well beyond the grasp of the fundamental strategy most companies follow: We have a bigger revenue opportunity, but we don't know how to take advantage? Let's buy more hamster wheels, hire more hamsters and train them to spin faster!

NVIDIA (NASDAQ:NVDA) was one of the hottest tech stocks of 2016, jumping 230% over the past 12 months. The company makes the vast majority of its revenue from gaming -- about 62% in the fiscal fourth quarter 2017 -- but NVIDIA is much more than just a a gaming processor company. The artificial intelligence (AI) market is quickly expanding and NVIDIA is positioning itself to make big gains in the space. According to an investor note published by Goldman Sachs' Toshiya Hari a couple of months ago, NVIDIA's total addressable market in AI and deep learning could be as big as $5 billion to $10 billion -- out of a total market of $40 billion. Hari mentioned that NVIDIA already has a lead in the AI space and that the company's competition "continues to face high barriers to entry."

The global artificial intelligence market is set to reach $16 million by 2022, according to the latest data by Research and Markets, which predicts that AI could double economic growth rates within two decades while boosting labor productivity by 40 percent. Meanwhile, research by Spiceworks shows that organizations are considering their AI strategy and investments; over the next five years, 46 percent of organizations plan to adopt intelligent assistants, 60 percent plan to adopt machine learning, and 72 percent plan to deploy business analytics with AI. The research clearly indicates that organizations are ready for AI. Helping break down the barriers that prevent partners from taking advantage of emerging technology like AI is just one part of Neeracha Taychakhoonavudh's job as senior vice president of partner programs at Salesforce. She's been at Salesforce for over 7 years and in her current role is in charge of the overall partner program, which includes a number of categories of partners including systems integrators, consultants, ISVs, and resellers, which she says "is a small but growing part of our strategy."