Connect with us

AI Insights

2 Historically Cheap Artificial Intelligence (AI) Stocks to Buy Hand Over Fist in July and 1 to Avoid

Published

on


Two fundamentally important businesses being bolstered by AI are begging to be bought, while another highflier is butting heads with history (and not in a good way).

Roughly 30 years ago, the advent of the internet ushered in a new era of corporate growth. Although it took many years for the internet to mature a technology and for businesses to figure out how to optimize this innovation to boost their sales and profits, it was a genuine game-changer.

For decades, Wall Street and investors have been waiting for the next technological leap forward. The evolution of artificial intelligence (AI) looks to have answered the call.

AI empowers software and systems with the ability to make split-second decisions, all without the need for human oversight. AI-accelerated data centers are facilitating generative AI solutions for businesses, as well as helping to train large language models (LLMs), such as chatbots and virtual agents.

Image source: Getty Images.

Based on estimates in Sizing the Prize, the analysts at PwC foresee AI adding $15.7 trillion to the global economy by 2030. If this projection is even remotely close to accurate, it’s going to lead to a lot of winners. But it doesn’t automatically mean every AI stock is worth buying.

As we push into the second-half of 2025, two historically cheap artificial intelligence stocks are begging to be bought, while another AI highflier with mounting red flags is worth avoiding in July.

Magnificent AI stock No. 1 that can be purchased with confidence in July: Alphabet

Although the “Magnificent Seven” played an undeniably huge role in lifting Wall Street’s major stock indexes to new highs, one of its seven components remains historically inexpensive. I’m talking about Google parent Alphabet (GOOGL -0.22%) (GOOG -0.27%).

While there’s been some concern about the possibility of LLMs siphoning away internet search share from Google, we haven’t witnessed any evidence of this occurring. Based on data from GlobalStats, Google accounted for a monopoly like 89.6% of global internet search market share in May 2025. Looking back more than a decade, it’s consistently accounted for an 89% to 93% worldwide share of internet search. This is a foundational cash cow of a segment that’s not going away.

Don’t overlook Alphabet’s strong cyclical ties, either. Approximately 74% of its net sales during the March-ended quarter can be traced to advertising, which includes ads found on YouTube, the No. 2 most-visited social media destination. With economic expansions lasting considerably longer than recessions, Alphabet is ideally positioned to take advantage of long-winded periods of growth and often possesses exceptional ad-pricing power.

However, Alphabet’s most attractive long-term growth prospect is its cloud infrastructure service platform, Google Cloud, which is already pacing more than $49 billion in annual run-rate revenue. Google Cloud is the world’s No. 3 cloud infrastructure service platform by spending, according to an analysis from Canalys, and its sales have the potential to accelerate further with customers gaining access to generative AI solutions.

As promised, there’s also quite the value proposition with shares of Alphabet. As of the closing bell on June 27, shares of the company can be scooped up for 12.7 times forecast cash flow in 2026, as well as a forward price-to-earnings (P/E) multiple of 17.5. For context, this represents a 28% discount to its average multiple to cash flow over the trailing-five-year period and is 20% below its average forward P/E ratio since 2020.

A hacker wearing a hooded sweatshirt who's typing on a keyboard in a dimly-lit room.

Image source: Getty Images.

Sensational AI stock No. 2 that can be bought in July: Okta

The second inexpensive artificial intelligence stock that makes for a no-brainer buy in July is none other than cybersecurity company Okta (OKTA -1.35%). While shares hit the skids in late May after the company guided for “just” 9% to 10% full-year sales growth in fiscal 2026 (ended Jan. 31, 2026), there are multiple reasons to believe Okta’s growth story is just getting started.

To begin with, cybersecurity has evolved from an optional to necessary solution for businesses. Regardless of how well or poorly the U.S. economy and stock market are performing, hackers don’t take time off from trying to steal sensitive data. This means demand for cybersecurity solutions from third-party providers like Okta is only going to increase.

What makes Okta such an intriguing investment is its AI- and machine learning-driven identity verification platform. Though AI platforms aren’t perfect, they offer the ability to become smarter over time at recognizing and responding to potential threats. This should make Okta’s Identity Cloud platform far nimbler and more effective than on-premises solutions.

Something else working in Okta’s favor is its subscription-based operating model. Subscription-fueled models tend to offer high margins (often in the neighborhood of 80%) and keep customers loyal to the platform. Additionally, it provides a layer of operating cash flow predictability that Wall Street and investors tend to appreciate.

Okta’s valuation also makes sense — especially following its double-digit percentage decline in late May. The company’s forward P/E ratio has fallen to 27, and its forward-year cash flow multiple of 21 is well below its average cash flow multiple of 51 over the last half-decade.

The exceptionally pricey AI stock to avoid in July: Palantir Technologies

However, not every artificial intelligence stock can be a winner. Despite adding north of $300 billion in market cap over the last 30 months, data-mining special Palantir Technologies (PLTR -4.09%) is the AI stock investors should steer clear of in July.

Don’t get me wrong, Palantir is a rock-solid business. Its government-focused Gotham platform and enterprise-driven Foundry platform have no one-for-one large-scale replacements, which means the company has a sustainable moat. These platforms, which respectively incorporate AI and machine learning, also generate highly predictable operating cash flow. Gotham’s government contracts are spread over multiple years, while Foundry is a subscription-based model.

The problem is there’s only so much premium that can be bestowed on a company with a sustainable moat, and Palantir has unquestionably overstepped its bounds. Whereas companies on the leading edge of the innovative curve during the rise of the internet topped out at price-to-sales (P/S) ratios of 30 to 43, Palantir’s P/S ratio handily surpassed 110 last week. No megacap company has ever been able to sustain a multiple this aggressive for an extended period, and it’s unlikely that Palantir is the exception.

Furthermore, there hasn’t been a next-big-thing technology or innovation since (and including) the advent of the internet that avoided a bubble-bursting event. In other words, investors have persistently overestimated the early adoption and/or utility of game-changing technologies for three decades.

Though spending on AI infrastructure has been robust, the simple fact that most businesses aren’t optimizing this technology as of yet, or generating a profit on their AI investments, signals the growing likelihood of being in a bubble. If the AI bubble bursts, investor sentiment will weigh heavily on the exceptionally expensive Palantir.

Lastly, the long-term ceiling for Gotham (the company’s most-profitable segment) is lower than investors might realize. Since this AI-driven platform is only available to the U.S. and its immediate allies, Palantir’s customer pool is rather narrow. It’s all the more reason for investors to avoid Palantir Technologies stock in July.



Source link

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

AI Insights

5 Ways CFOs Can Upskill Their Staff in AI to Stay Competitive

Published

on


Chief financial officers are recognizing the need to upskill their workforce to ensure their teams can effectively harness artificial intelligence (AI).

According to a June 2025 PYMNTS Intelligence report, “The Agentic Trust Gap: Enterprise CFOs Push Pause on Agentic AI,” all the CFOs surveyed said generative AI has increased the need for more analytically skilled workers. That’s up from 60% in March 2024.

“The shift in the past year reflects growing hands-on use and a rising urgency to close capability gaps,” according to the report.

The CFOs also said the overall mix of skills required across the business has changed. They need people who have AI-ready skills: “CFOs increasingly need talent that can evaluate, interpret and act on machine-generated output,” the report said.

The CFO role itself is changing. According to The CFO, 27% of job listings for chief financial officers now call for AI expertise.

Notably, the upskill challenge is not limited to IT. The need for upskilling in AI affects all departments, including finance, operations and compliance. By taking a proactive approach to skill development, CFOs can position their teams to work alongside AI rather than compete with it.

The goal is to cultivate professionals who can critically assess AI output, manage risks, and use the tools to generate business value.

Among CEOs, the impact is just as pronounced. According to a Cisco study, 74% fear that gaps in knowledge will hinder decisions in the boardroom and 58% fear it will stifle growth.

Moreover, 73% of CEOs fear losing ground to rivals because of IT knowledge or infrastructure gaps. One of the barriers holding back CEOs are skills shortages.

Their game plan: investing in knowledge and skills, upgrading infrastructure and enhancing security.

Here are some ways companies can upskill their workforce for AI:

Ensure Buy-in by the C-Suite

  • With leadership from the top, AI learning initiatives will be prioritized instead of falling by the wayside.
  • Allay any employee concerns about artificial intelligence replacing them so they will embrace the use and management of AI.

Build AI Literacy Across the Company

  • Invest in AI training programs: Offer structured training tailored to finance to help staff understand both the capabilities and limitations of AI models, according to CFO.university.
  • Promote AI fluency: Focus on both technical skills, such as how to use AI tools, and conceptual fluency of AI, such as understanding where AI can add value and its ethical implications, according to the CFO’s AI Survival Guide.
  • Create AI champions: Identify and develop ‘AI champions’ within the team who can bridge the gap between finance and technology, driving adoption and supporting peers, according to Upflow.

Integrate AI Into Everyday Workflows

  • Start with small, focused projects such as expense management to demonstrate value and build confidence.
  • Foster a culture where staff can explore AI tools, automate repetitive tasks, and share learnings openly.

Encourage Continuous Learning

Make learning about AI a continuous process, not a one-time event. Encourage staff to stay updated on AI trends and tools relevant to finance.

  • Promote collaboration between finance, IT, and other departments to maximize AI’s impact and share best practices.

Tap External Resources

  • Partner with universities and providers: Tap into external courses, certifications, and workshops to supplement internal training.
  • Consider tapping free or low-cost resources, such as online courses and AI literacy programs offered by tech companies (such as Grow with Google). These tools can provide foundational understanding and help employees build confidence in using AI responsibly.

Read more:

CFOs Move AI From Science Experiment to Strategic Line Item

3 Ways AI Shifts Accounts Receivable From Lagging to Leading Indicator

From Nice-to-Have to Nonnegotiable: How AI Is Redefining the Office of the CFO



Source link

Continue Reading

AI Insights

Real or AI: Band confirms use of artificial intelligence for its music on Spotify

Published

on


The Velvet Sundown, a four-person band, or so it seems, has garnered a lot of attention on Spotify. It started posting music on the platform in early June and has since released two full albums with a few more singles and another album coming soon. Naturally, listeners started to accuse the band of being an AI-generated project, which as it now turns out, is true.

The band or music project called The Velvet Sundown has over a million monthly listeners on Spotify. That’s an impressive debut considering their first album called “Floating on Echoes” hit the music streaming platform on June 4. Then, on June 19, their second album called “Dust and Silence” was added to the library. Next week, July 14, will mark the release of the third album called “Paper Sun Rebellion.” Since their debut, listeners have accused the band of being an AI-generated project and now, the owners of the project have updated the Spotify bio and called it a “synthetic music project guided by human creative direction, and composed, voiced, and visualized with the support of artificial intelligence.”

It goes on to state that this project challenges the boundaries of “authorship, identity, and the future of music itself in the age of AI.” The owners claim that the characters, stories, music, voices, and lyrics are “original creations generated with the assistance of artificial intelligence tools,” but it is unclear to what extent AI was involved in the development process.

The band art shows four individuals suggesting they are owners of the project, but the images are likely AI-generated as well. Interestingly, Andrew Frelon (pseudonym) claimed to be the owner of the AI band initially, but then confirmed that was untrue and that he pretended to run their Twitter because he wanted to insert an “extra layer of weird into this story,” of this AI band.

As it stands now, The Velvet Sundown’s music is available on Spotify with the new album releasing next week. Now, whether this unveiling causes a spike or a decline in monthly listeners, remains to be seen. 



Source link

Continue Reading

AI Insights

How to Choose Between Deploying an AI Chatbot or Agent

Published

on


In artificial intelligence, the trend du jour is AI agents, or algorithmic bots that can autonomously retrieve data and act on it.

But how are AI agents different from AI chatbots, and why should businesses care?

Understanding how they differ can help businesses choose the right solution for the right job and avoid underusing or overcomplicating their AI investments.

An AI chatbot or assistant is a program that uses natural language processing to interact with users in a conversational way. Think of ChatGPT. It can answer questions, guide users and simulate dialogue.

Chatbots only react to prompts. They don’t act on their own or carry out multistep goals. They are helpful and conversational but ultimately limited to what they’re asked.

An AI agent goes a step further. Like a chatbot, it can understand natural language and interact conversationally. But it also has autonomy and can complete tasks. It is proactive.

Instead of just replying, an AI agent can make decisions, take actions across systems, plan and carry out multistep processes, and learn from past interactions or external data.

For example, imagine a travel platform. An AI chatbot might help a user plan their travel itinerary. An AI agent, on the other hand, could do more, such as:

  • Understand the request, such as booking a flight to Los Angeles.
  • Search multiple airline sites.
  • Compare flight options based on user preferences.
  • Book the flight.
  • Send a confirmation email.

All of this could happen without the user needing to click through a series of links or speak to a human agent. AI agents can be embedded in customer service, HR systems, sales platforms and the like.

Read also: Understanding the Difference Between AI Training and Inference

Why Businesses Should Care

Knowing the difference can help a business plan more strategically. AI chatbots use less inference than AI agents and therefore are more cost-effective. Moreover, businesses can use AI chatbots and AI agents for very different outcomes.

AI chatbot use cases include the following:

  • Customer service
  • Data retrieval
  • Planning and analysis
  • Basic IT support
  • Conversation
  • Writing documents
  • Code generation

AI agent use cases include the following:

  • Automated checkout
  • Automated content curation
  • Travel and reservation execution tasks
  • Shopping and payment processing

AI chatbots and AI agents both use natural language and large language models, but their functions are different. Chatbots are answer machines while agents are action bots.

For businesses looking to improve how they serve customers, streamline operations or support employees, AI agents offer a new level of power and flexibility. Knowing when and how to use each tool can help companies make smarter AI investments.

To choose between deploying an AI chatbot or AI agent, consider the following:

  • Budgets: AI chatbots are cheaper to run since they use less inference.
  • Complexity of use case: For straightforward tasks, use a chatbot. For tasks that need multistep coordination, use an AI agent.
  • Skilled talent: Assess the IT team’s ability to handle chatbots versus agents. Chatbots are easier to deploy and update. AI agents require more advanced machine learning, natural language processing and other skills.

For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.

Read more:



Source link

Continue Reading

Trending