In a tech landscape where buzzwords come and go faster than you can say “innovation,” AI has proven it’s more than just a passing trend. In fact, it’s quickly becoming a total game changer with the potential to transform industries across the board. And to be real: It’s already doing just that.
From automating mundane tasks to providing deep insights that drive smarter decision-making, AI is completely revamping the way we do business. Yet despite its well-established benefits and advantages, beneath the surface, we know there are some questions you might have.
Why? Well, that depends on whom you ask. Business leaders might argue that AI is too complex or pricey to integrate with their current systems. Employees might complain that AI feels too one-size-fits-all, while everyday folks might dismiss it as just another fleeting trend. But here’s the thing: These myths are, well, myths.
By clinging to outdated notions, businesses risk missing out on opportunities to streamline their operations game, boost customer experiences, and get a leg up on the competition. All the eyebrow-raising is misguided and potentially harmful to your business.
That’s why we teamed up with Arm (Nasdaq: $ARM) to dispel five common myths surrounding AI in the workplace. In this article, we’ll cut through the noise and get you all the real and right info.
Without further ado, here’s the scoop.
Myth: AI is only for large tech companies.
It’s easy to assume AI is reserved for tech giants with deep pockets and massive data centers. They have the resources to invest in the technology and hire cream-of-the-crop talent. Biggest of all? They hold the power to train their own models. Yep, industry giants indeed have the goods to collect vast amounts of data, run super-complex algorithms, and fine-tune AI systems over long periods of time. However, this is all set to change.
Mythbusted: Inference will democratize the game.
Incoming: inference. If you need a refresher on what this is in the context of AI, well, here ya go: Inference allows businesses to use pretrained models to make predictions or decisions. To get a little more technical, there are two predominant models of inference for text-based generative AI: SLM (small language models) and LLM (large language models). Both are readily available and are already changing business models by allowing businesses to bypass the need for pricey and resource-heavy model training. (In fact, Arm is leading the way here.) See where this is going, though? Smaller companies can tap into AI without needing massive datasets or super-complex infrastructures. AI is for everyone!
Myth: AI is not sustainable to implement.
Look, we get it. Convincing the C-suite to buy in to new tech can be a challenge, especially when the tool consumes vast amounts of power that can lead to increased long-term costs, energy-grid problems, and missed corporate sustainability goals. Not to mention that many operate under the false assumption that implementing AI into existing tech stacks requires hefty investments in specialized hardware, custom software, and a team of data scientists all sourced from the Ivy League.
Mythbusted: Advancements in power-efficient hardware and increasing ubiquity are boosting AI sustainability.
The belief that AI is unsustainable is quickly becoming outdated—tech innovation works *that* fast now. With breakthroughs in power-efficient hardware and the ever-growing use of AI across tons of industries, adoption is no longer an energy- or even a wallet-buster. Ubiquity is increasing sustainability while driving down prices as AI tools and platforms become more accessible than ever, often available through scalable, pay-as-you-go models that get both sustainability and finance people grinning.
Myth: AI solutions are one-size-fits-all.
When AI first hit the scene, many dismissed it as a rigid, one-size-fits-all development that could deliver only broad, standardized results without the flexibility to address hyperspecific business needs. In other words, there was a fear that AI lacked the nuance to handle challenges unique to different industries.
Mythbusted: Specialized AI solutions offer serious customization.
The reality is that AI is far from a one-size-fits-all solution. It’s incredibly flexible and can be customized to fit an enormous range of business needs for everything from souping up creative concepting to streamlining mundane accounting tasks—all from one tech stack. For example, AI can be fine-tuned to analyze specific data relevant to your industry, such as customer behavior in retail, financial patterns in banking, or engagement clicks in marketing. Many next-level platforms like Arm even allow for custom model training, which means AI can make itself at home within your industry and provide insights and automation power completely specific to your unique processes and needs. AI is and always has been flexible. That’s why it’s such a game changer.
Myth: AI compromises security.
Like any technological breakthrough, AI comes with its own baggage, especially in the context of security. It is true that AI presents unique security challenges. For one, its complex algorithms and vast data-processing capabilities open up all kinds of questions about cyberattacks, sensitive information, and data usage.
Mythbusted: AI is beginning to operate at the edge of the network, giving businesses and consumers more control over their data.
While it’s true that AI poses new security challenges (like any new tech), it’s incorrect to assume it’s insecure. The cloud and its core security principles paved the way for what’s becoming AI’s calling card when it comes to security: As AI becomes more common across industries, many companies have started running AI inference workloads at the edge of the network, on devices. Scratching your chin? No worries. Basically, this means AI inference is being conducted across decentralized groups of devices, rather than on one singular network. To get a little more granular about this, edge-of-network computing allows user data to be processed directly on the device instead of being sent to third parties. Yep. That’s classic, good ol’ cybersecurity.
Myth: AI is just another tech fad.
Ahh, this is a classic misconception. It’s probably heard most frequently during casual conversation. Skeptics often write off AI as another buzzword in the deluge of tech trends, a confusing and too-complex tool driven by marketing hype, innovation conferences, and emerging tech spotlights. Just remember: Every single innovation over the last decade in tech has had its deflectors. AI is no different.
Mythbusted: AI is the computing revolution of a lifetime.
Much like how the printing press made knowledge readily available to all, AI is set to even further democratize our informational world. It is and could continue to be one of the most powerful tech advancements we’ve seen, with a potential to transform business and life at large already taking shape. It’s impacting every corner of professional and daily life, from automating snooze-worthy tasks at the office to creating vibrant art and music. But rest assured: AI is not just about automating tasks. It’s really about redefining industries through enhanced decision-making, personalized experiences, and stronger problem-solving. You can see AI already leveling up nearly every industry, from healthcare and finance to education and marketing. In short, it’s more than a fad—it’s the future.
There’s no getting around it: There’s a cloud of misconception surrounding AI. And it makes sense; it’s a new technology that’s often discussed as the next big thing. But it’s imperative to understand these myths for what they are—myths. AI is already working to transform our world through enhanced efficiency, concrete innovation, and stronger decision-making, and that’s not gonna change.
And as the industry’s most pervasive, power-efficient, and high-performing compute platform—with the world’s largest software developer ecosystem—Arm is enabling AI everywhere.
It’s safe to say AI is here to stay.