Best AI Stocks for 2025: Artificial Intelligence Investing
The AI Edge: Transforming Business Growth In The Digital Era
Chris "Jay" Hawkinson is the Senior Director of Data & Analytics at Lamb Weston.
gettyIn today's rapidly evolving digital landscape, data and artificial intelligence (AI) are no longer optional tools—they are essential drivers of innovation, efficiency and competitive advantage.
The question isn't whether to adopt AI, but how. Think of it in terms of building the "Six Million Dollar Man"—meaning, enhancing capabilities requires careful oversight to avoid unintended consequences. Fortunately, there are plenty of insights to help businesses avoid said consequences.
Readiness depends on a few key factors, such as data quality, governance and ethical usage. While most companies are technologically ready, success depends on aligning AI adoption with robust governance and real accountability.
So, how should business leaders begin? To leverage AI effectively, start with the fundamentals: understanding and simplifying existing processes. It's vital to identify inefficiencies before introducing AI. Otherwise, AI will simply help make mistakes faster.
AI is most impactful when used to identify process weaknesses and eliminate unnecessary complexities, such as redundant approval flows. The result: streamlined operations that enhance customer-facing value.
The next step is to select the right data analytics tools, which is not a one-size-fits-all approach. Since there are no perfect tools, it's important to align them with your company's maturity level and business objectives, while avoiding frequent switching.
Switching tools often results in lost productivity, so it's best to prioritize maximizing the value of existing tools while maintaining long-term visibility. The goal is to give people access to the information they need as soon and as comfortably as possible.
In industries like consumer packaged goods (CPG) and manufacturing, data can be impactful or actionable—but it's not always both. For example, supply chain visibility is crucial for long-term strategy, but inventory movement data often provides the most actionable insights in the short term.
It's important to remember that good data drives actionable decisions, in any industry. Focus on data that is both high-quality and within the company's control.
When it comes to measuring the success of implementing new tools and AI initiatives, keep this in mind: it's not always about the bottom line. Business impact should be defined before implementation—and while some outcomes, like metrics, can be seen directly, others (like improving safety and reducing risk) aren't as easy to track.
With sustainability being a core value at so many companies, including ours, it's important to note that AI and data are vital in meeting sustainability goals. AI helps standardize and analyze sustainability data quickly, enabling actionable plans without months of manual human processing.
The key lesson for leaders is clear: Data and AI are tools for enabling better decisions, not just faster ones. The true value lies in using these technologies to drive long-term growth, improve efficiency and create meaningful business outcomes.
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3 Artificial Intelligence Stocks (AI) You Can Buy And Hold For The Next Decade
AI will continue to drive these stocks higher.
Artificial intelligence (AI) isn't just a trend that will disappear in the next few years. AI is fundamentally how we do business, and the impacts will be felt for decades to come. With that in mind, there are a few AI companies that investors can feel confident buying and holding over the next decade, as they have sustainable trends that will continue pushing their stocks higher.
The three stocks to buy and hold for the next decade that are expected to capitalize on AI are Amazon (AMZN 2.39%), Alphabet (GOOG 1.62%) (GOOGL 1.60%), and Taiwan Semiconductor (TSM -1.53%). This trio makes for an excellent group to buy now with the intention of not selling unless something fundamental changes.
Amazon and AlphabetCloud computing is one of the biggest beneficiaries of the AI arms race that isn't discussed enough. Not every company has the resources available to spend billions of dollars on a supercomputer for AI, but they still need access to the computing power that these servers can provide. To gain access to that power, companies rent it from cloud computing giants like Amazon Web Services (AWS) and Google Cloud.
By renting it, clients can easily scale up or down the amount of computing power needed and store the data on which they're training these AI models. With both Amazon and Alphabet giving clients access to cutting-edge GPUs and custom AI accelerators, they offer a significant value proposition to their customer base.
Furthermore, many companies still host many websites and store data on-site. As the need to replace outdated hardware arises, these workloads will likely continue to migrate to the cloud.
All of this adds up to a massive growth industry, which Amazon and Alphabet dominate. According to Fortune Business Insights, the cloud computing market is expected to expand from $676 billion in 2024 to $2.3 trillion by 2032. That's huge growth, and investors need to be aware of and consciously invested in it.
AWS and Google Cloud are currently the largest and third-largest operations in the cloud computing market, respectively. With this dominance level, they are positioned to capitalize on future growth. During the third quarter, AWS' sales rose 19% year over year to $27.5 billion, and its operating income rose 50% year over year to $10.4 billion -- a 38% operating margin. Google Cloud also had a solid quarter, with revenue rising 35% year over year to $11.4 billion, posting an operating margin of 17%.
While these two divisions are just part of a larger entity, they make for compelling reasons to buy the stocks. Cloud computing is a massive trend that isn't going away, and investing in these two now is a great way to capitalize on that trend.
Taiwan SemiconductorAn investment in Taiwan Semiconductor is a clear bet that we'll use a great deal of technology and more advanced technology over the next decade. That seems like a no-brainer, which is why Taiwan Semiconductor is on this list.
Taiwan Semi is a chip foundry, which means it fabricates chips for clients who cannot do it themselves. This includes GPUs and CPUs that go into Amazon and Alphabet's cloud computing data centers and smartphones. If you have a high-tech device, chances are it's filled with chips that originated from Taiwan Semiconductor's factories.
Additionally, TSMC has always been at the forefront of launching new technologies. While it's currently producing 3nm (nanometer) chips, it's slated to launch 2nm chips by the end of the year and ramp up production next year. Beyond that, it's already preparing its A16 chip, which will be launched in the second half of 2026.
All of these advancements will help keep TSMC on top and further advance AI technology.
Over the next decade, we will need more chips to power all of the AI devices, and buying shares of Taiwan Semiconductor now is a surefire way to capitalize on AI growth.
Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. John Mackey, former CEO of Whole Foods Market, an Amazon subsidiary, is a member of The Motley Fool's board of directors. Keithen Drury has positions in Alphabet, Amazon, and Taiwan Semiconductor Manufacturing. The Motley Fool has positions in and recommends Alphabet, Amazon, and Taiwan Semiconductor Manufacturing. The Motley Fool has a disclosure policy.
AI And Creativity: How Business Can Add Ethics To Decision-Making
The absence of human intervention in generative artificial intelligence outputs presents new ethical ... [+] dilemmas for business leaders.
gettyBy Antonino Vaccaro and Rosa Fioravante
In the artificial intelligence onslaught of recent years, many business leaders are scrambling to balance adoption of the technology at speed with protecting human creativity.
When AI tools can generate texts, images, video and audio in a matter of seconds, what constitutes creative expression? What makes it human? Why does preserving human creative expression matter?
In considering the potential economic opportunities presented by the adoption of generative AI, decision makers may face an ethical dilemma over having to choose whether to prioritize speed in technological adoption, or to dedicate the time and resources to ensure ethical compliance in the use of the technology for humans to flourish.
This is not the only ethical AI dilemma business leaders are grappling with. But we wanted to understand specifically the ethics around creativity, since one of the novelties of generative AI is that it has the potential to automate, and/or augment and integrate human creative expression, that most human of activities.
Generative AI threatens human expression in at least two ways: by disregarding existing creative work through its use without adequate permission or recognition, and by replacing creative jobs in organizations.
For example, a group of news organizations led by The New York Times has sued ChatGPT maker OpenAI for using their articles without consent or payment – which they allege is massive copyright infringement – to train its large-language models. At the same time, more than a quarter of work tasks in arts, design, entertainment and sports could be automated with AI, according to a Goldman Sachs report.
To understand the ethics, we start by looking at the foundations of creativity through the lens of personalism, a worldview that emphasizes the centrality of the human person, the starting point for all ontological and epistemological understanding. Personalism believes in human exceptionalism and irreplaceability, and thus places much importance on the human attributes that should never be disregarded. Personalism also emphasizes the role of creativity in expressing a person's intrinsic morality and, therefore, dignity.
Since generative AI impacts a morally salient dimension of human life, decisions on its use should be rooted in ethics. Organizations bear the responsibility of ensuring their economic sustainability through technological innovation, as well as fostering human flourishing through creative expression.
Thus, we build on this understanding to present a three-dimensional model based on the concepts of uniqueness, relationality and unpredictability:
UniquenessThe originality of an output stems directly from the creator's uniqueness and participation in the creative act. Creative expression is understood as an expression of the inner self and uniqueness is a quality that distinguishes every human being.
With generative AI, the absence of the creator's direct involvement undermines claims of the output's uniqueness. That may not matter in some applications: a mass-market advertising campaign, for example, may not be entirely unique. But where uniqueness matters, a participatory approach is necessary, in which creative professionals contribute insights into the compatibility of AI deployment with creative processes and objectives. This entails collaborative decision-making processes that bring together creative professionals and organizational stakeholders.
RelationalityArtistic creation is the expression of the creator's interior self but it is also closely linked to their dynamics with others. There is a give and take, a process of reciprocal recognition, between the creator and the audience.
In industries that rely on generative AI for artistic and creative output design, careful attention must be paid to the relationship between creators and external stakeholders. Generative AI accelerates the creative process and enables the exploration of numerous possibilities in a shorter time frame, but it lacks the continuous exchange between different perspectives inherent in human interaction. Again, collaboration is the key: organizations should integrate professionals skilled in prompt engineering with humanistic experts in artistic and intellectual endeavors. This multidisciplinary approach ensures that the relational aspect of the creative process is preserved, allowing for a more nuanced understanding of audience needs and the broader societal impact of creative outputs.
UnpredictabilityIn personalism thinking, the act of creation revolves around the exercise of freedom beyond necessity. A person is not limited to choosing among already existing options, but rather may create new options, scenarios and possibilities. The act of creation is the act of pushing something new into the existing world.
But what if a machine creates something harmful or inappropriate? Humans in the loop may contribute to various stages of the AI process, including dataset curation and content validation. This can be attained by reinforcing the presence of human reviewers to evaluate generative AI outputs, flagging certain content before such models are released to the public.
Much of the debate around generative AI and creative expression has focused on the outputs. Outputs are important, but we believe that organizations should begin with the people who create and the foundations underpinning human expression, when making decisions on AI deployment. In doing so, they bring ethics into the decision-making process.
Antonino Vaccaro is a professor in the Department of Business Ethics at IESE Business School. Rosa Fioravante is a research fellow at IESE's Center for Business in Society and teaches a Business Ethics and Social Responsibility course at Católica Lisbon School of Business & Economics.
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