Birth Of An Industry: Early Investing Hot Spots In Artificial Intelligence – Investor's Business Daily

It doesn’t take a rocket scientist to know that the cutting-edge technologies known as artificial intelligence will transform many U.S. industries.

But, it takes a savvy investor to sort through the technology’s early possibilities.  Even the biggest tech names have yet to see their AI-related revenue growth take off, and the market is still waiting to see any real pure-play AI stock names. But the rapidly developing technologies are starting to contribute sales to a handful of companies, while driving others to modify their products and technology platforms to tap into AI’s possibilities.

At a basic level, artificial intelligence is the use of computer algorithms to attempt to replicate the human ability to learn, reason and make decisions. The buzz around the rapidly developing technologies has become nearly constant. And while things like AI-driven toothbrushes (already available) may seem a stretch, sources as stalwart as Goldman Sachs consider it possible that the next Apple (AAPL) or Facebook (FB) could be an AI startup.

Chipmaker Nvidia (NVDA) is one company that can lay claim to incremental AI-driven growth. Though its biggest business is still PC graphics and gaming, Nvidia sells AI processors to internet and tech companies engaged in cloud computing. Those companies include Amazon.com (AMZN), Microsoft (MSFT) and Alibaba Group (BABA).  Its AI chips also are helping guide some self-driving cars in early trials.

Nvidia aside, there’s a slew of tech companies that Wall Street analysts tout as possible AI stock plays. They include enterprise software providers like Salesforce.com (CRM), internet giant Facebook, tech consultancy Accenture (ACN), Alphabet‘s (GOOGL) Google, Microsoft and lesser known names like Splunk (SPLK).

Some of them are called AI “enablers” because they provide some of the high-speed computing infrastructure needed to run AI programs. Other AI players will make the technology more accessible for small and big businesses. Google, Amazon.com, IBM (IBM) and Microsoft are pushing into AI-as-a-service. They plan to rent AI tools to customers on a pay-as-you-go basis via their public cloud-computing services.

Then, there are tech companies that embed AI tools in their own products to make them better. Video streamer Netflix (NFLX) uses AI to make program recommendations to subscribers. Payment processor PayPal (PYPL) uses AI tools in fraud detection. Social media leader Facebook employs AI in targeted advertising and facial recognition tools which drive, among others things, photo sharing apps.

Computer security specialist Palo Alto Networks (PANW) uses AI machine learning, which involves computers sifting through and learning from data, to detect hacker threats. Zendesk (ZEN) predicts customer support success through AI technologies.

“You hear Nvidia as probably the most horizontal play for AI, because it’s an enabling infrastructure for processing all the data,” said Derrick Wood, a Cowen & Co. analyst. “There are enablers and companies that are harnessing AI into their products, weaving it into the cloud in a way that they can monetize, like Salesforce. There’s data ingestion, helping companies pull in lots of data for processing.”

Companies are also selling tools so customers can build their own AI models, and large cloud vendors find themselves in a good position.

“But, it’s very early,” Woods said. “We haven’t seen many vendors with material monetization.”

A $50 Billion Market?

AI, around since the 1960s, now comes in new forms. The two most mentioned are “machine learning” and “deep learning networks.” The basic idea is to make better predictions by analyzing massive amounts of data that even supersmart humans can’t process.

There’s little doubt that customers of tech companies — spanning banks and finance, health care, energy, retail, agriculture and other sectors — will increase spending on AI, says a November Goldman Sachs report. They’ll seek productivity gains by doing more with fewer workers. They’ll aim to grab a strategic edge on rivals with AI-processed data that produce new discoveries.

“We see the potential for AI and machine learning to reshuffle the competitive order across every industry,” said the report.

One way to look at AI investing opportunities, says Goldman Sachs, is monitoring companies that could use the technology effectively. It points to oilfield services giant Schlumberger (SLB) as one example. Schlumberger has developed, among other things, a smart oil rig using AI technologies.

If rosy market forecasts prove correct, there will be sizable AI spending budgets for suppliers to pursue. Research firm Tractica forecasts that artificial intelligence revenue will reach $59.8 billion worldwide by 2025, up from $1.4 billion in 2016.

“AI is very application specific, very industry specific,” said Cowen’s Wood. “CIOs are at the stage of saying, ‘We’ve got to invest in AI. If we get it right, we’re going to be more competitive.’ That applies for any company in any industry.”

IDC, another market research firm, forecasts that AI revenue will grow from $8 billion in 2016 to more than $47 billion in 2020, with about half that total being software-related.

Another way to look at AI investing is to focus on tech companies that use the technology internally, such as Amazon, with its shopping-recommendation engine.

“AI is making companies with already good products even better,” said Josh Spencer, manager of T. Rowe Price’s global technology fund.

Tech giants are pouring money into AI research and gobbling up AI startups. Their size gives them an edge in the AI battle, says Spencer.

“AI is maybe 10% of the investment case at Google now, but it’s an important 10%,” he said.

The Cloud Learns To Predict

Steven Milunovich, analyst at UBS, says web-connected devices, generally called the “Internet of Things,” will require AI to process real-world data gathered from sensor networks, suggesting a very large market.

“AI likely will not be a winner-takes-all game as vendors will be successful in different verticals,” Milunovich said in a report. “IBM has purchased health care and weather data to feed Watson. Microsoft has augmented its enterprise data with the purchase of LinkedIn. Specialists such as General Electric (GE) in industrial should do well.”

Google’s AI efforts span its major products — internet search, Android mobile phone software, Gmail, translation, maps, YouTube, and self-driving cars. Google in May unveiled a new AI-based photo recognition app for smartphones. In mid-June, it added a new AI-based jobs search feature.

Amazon, Apple, Facebook, Google and Microsoft have been racing to use AI in natural language processing, video and image recognition. They’ve rolled out “chat bots,” software programs that interact directly with consumers via natural language processing. Facebook has been teaching its chat bots how to negotiate.

Amazon, Google and more recently, Apple, have also rolled out smart home hubs featuring voice-activated digital assistants. Amazon’s sales of Echo speakers have been strong. But, the bigger battle may be building AI tools into smartphones — with billions of mobile devices in use worldwide.

One example of how companies are going after the AI market is Salesforce.com, which aims to be a leader in bringing AI technologies to the enterprise software market.

Salesforce.com’s cloud software helps businesses organize and handle sales operations and customer relationships across service and marketing. The company has expanded into financial services, health care and e-commerce.

The company has made several acquisitions to acquire AI tools, including RelatelQ, MetaMind, Minhash  and PredictionIO. Salesforce.com is in the early stages of embedding AI tools in existing cloud products to make them more predictive, analysts say.

Salesforce.com introduced its “Einstein” AI cloud platform in September 2016. In March, Salesforce.com showcased its AI tools at a customer event.

Einstein tools identify and prioritize sales leads and recommend products and pricing options, making it easier for sales reps to convert leads to sales.

Salesforce.com also demonstrated how Coca-Cola (COLA) built an app using image recognition that retailers can use for inventory management. Salesforce’s AI tools and forecasting models automate the restocking process.

Pricing varies, some features are added into existing licenses and others require an additional charge. Salesforce.com’s pricing varies by cloud product with some features included at no extra cost while others range from $50-$150 per user.

Highly Competitive Proving Period

While Salesforce.com has told analysts AI could help fuel its next leg of growth, that may depend on whether upgrading to AI platforms unleashes productivity gains for customers.

“Customers need to see it work, buy in and believe that it’s adding value,” said Wood at Cowens & Co. “Some new (AI) products are in the evaluation stage. For Salesforce, the second half of this year could be telling.”

Analysts say Adobe Systems (ADBE), Workday (WDAY), ServiceNow (NOW) and other enterprise software providers also plan to embed AI tools into products.

One red flag for AI investors is that early leaders, like Nvidia or Salesforce.com, may face new challenges. Intel’s acquisition of AI startup Nervana Systems heated up its rivalry with Nvidia. Google has built its own in-house AI chips.

Barclays says Nvidia could also face stiff competition from AI chip startups such as Graphcore, Cerebras and AIMotive

Much venture capital, meanwhile, has been flowing to AI startups. Tech giants, led by Google and Apple, have been gobbling many of them up.

More than 200 private AI companies have been acquired since 2012, with 30 acquisitions taking place in Q1 2017, says market research firm CB Insights. On the other hand, funding of AI startups jumped to $1.73 billion in Q1, up from $939 million a year earlier, says CB Insights.

According to New York-based CBI Insights, some of the well-funded AI software startups include Sentient Technologies, Ayasdi, Digital Reasoning Systems, Vicarious Systems, DataRobot, StackPath, Flatiron and Zoox.

Some AI startups may stay independent and file for initial public offerings.

IPOs would mark another opportunity for investors.

“We certainly wouldn’t dismiss the potential for a Google or Facebook of AI to emerge,” said the Goldman Sachs report.

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