Artificial intelligence (AI) inspires all the feelings: We love it, we hate it, we’re confused and intrigued by it.
One thing is true: We can’t ignore it. In late 2024 Gallup reported that 93% of Fortune 500 chief human resource officers (CHROs) say their organizations have begun using AI to improve business practices. Sixty-five percent of respondents to Mckinsey’s recent global survey on the state of AI said they’re regularly using generative AI at work—nearly double the percentage from its previous survey only 10 months prior. And in June, CNBC reported that almost half of U.S. teachers and K-12 students use ChatGPT on a weekly basis.
So, what is AI? The more you understand about it—its benefits and downsides, and its implications for the workplace and beyond—the better you can leverage it for your own personal and professional gain, and prepare yourself for what’s to come.
Here’s a breakdown of what artificial intelligence is (without getting too technical), its common applications in today’s world, and where it might be headed in the future.
What is AI?
Artificial intelligence is the ability for computers to mimic human intelligence—or at least “do things that can seem intelligent,” as Ansaf Salleb-Aouissi, a professor of computer science at Columbia University specializing in AI, puts it. This could be identifying or recognizing patterns, making predictions or decisions, or performing tasks routinely done by human beings. “For example, a self-driving car is an AI system—we call that an agent. And this agent is able to look around with computer vision, make decisions about the next action to do, and proceed in the environment, get some reward from that environment, and carry on,” Salleb-Aouissi says.
It’s able to exhibit this behavior thanks to exposure to vast amounts of data—visuals such as images or videos, text, and numbers, among other things. And because it can take in a lot of data, it can synthesize more of it, and more quickly, than humanly possible. “It’s designed to simulate human-like decision-making, but it does not think or feel,” says former engineer and veteran AI strategist Jennifer Ives. “It’s basing its decision as to how it was programmed.”
What about generative AI, computer science, machine learning, and similar terms?
What is generative AI? Or computer science, or machine learning? In the world of artificial intelligence, a lot of jargon can get tossed around. To help clarify, here’s one way to understand it:
- AI is a branch of computer science that encompasses other specialities such as hardware, computational theory, and data structures.
- Machine learning is a subcategory of artificial intelligence; it’s one application for teaching a computer how to autonomously learn, improve, and make decisions over time.
- Generative AI (or GenAI) is another subcategory of artificial intelligence that uses large data sets to create content, be it written, audio, or visual. Think: OpenAI’s chatbot ChatGPT or text-to-image generator DALL-E. It incorporates large language models to process and generate language.
- The flip side of generative AI is predictive AI (or predictive analytics), which leverages data to forecast outcomes. A healthcare company, for example, might use predictive AI to identify patients most at risk for certain diseases based on their health history and behavior.
How does AI work?
In the simplest terms, AI uses algorithms to analyze historic data, which then allows it to find patterns that can inform its decision-making.
“If you can back up those patterns with what a correct decision looked like, and then you brute-force-feed that into a machine billions and billions of times, it can start to put the patterns together and start to recognize when you would’ve made those decisions and when you wouldn’t,” says Chris Brown, the president of AI solutions provider Intelygenz.
What are common AI tools and applications?
Brown likes to break down AI’s applications into three categories: “It can do classifications, it can forecast, and it can generate, which is the new kid on the block,” he says, referring to large language models like ChatGPT, Google’s Gemini, Microsoft’s Copilot, Meta’s Llama, Anthropic’s Claude, and X’s Grok that are particularly buzzy right now.
But artificial intelligence comes in many shapes and sizes—many of which you may already use daily:
- Translation and transcription tools that digest one language and either regurgitate it via text or translate it into another language
- Virtual assistants or customer service bots that can recall past orders, start returns, or address basic consumer questions
- Recommended content services such as shopping recommendations on Amazon or “Watch next” ideas on streaming services that are based on past behaviors and preferences
- Social media algorithms that surface content based on what you watch, click on, or engage with most and least often
- Search engines that prioritize and tailor content based on a user’s profile and needs
- Facial recognition technology that can identify and evaluate individuals (think: checkpoints at airport security)
- Self-driving cars and autonomous robots that can perform basic tasks with minimal human intervention
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What are the benefits of AI?
AI can offer multiple benefits to workers and individuals. The biggest ones, experts agree, include the following.
You can work faster
AI can sift through data and generate outputs much faster than the human brain and body can process information, which makes completing routine tasks like writing an email or creating a meeting summary that much quicker. “Those repetitive tasks are really where you can create some really profound efficiencies,” Ives says.
Research backs this up: According to Gallup’s latest survey, 45% of CHROs say their organization’s operational efficiency has improved because of AI. Other recent studies have found that workers can answer more customer requests and write more documentation and code with the assistance of AI.
Plus, Salleb-Aouissi points out, AI doesn’t tire like we might at the end of a long day. “AI is meant to make our job easier,” she says. “It’s kind of supposed to be our extension.”
You can work smarter
Because AI can augment or replace certain activities, we have more room to focus on tasks that leverage our most advanced skills. Additionally, AI can supplement our creative process when we’re feeling stuck.
“It can be extremely powerful in helping you either discover or do research, or also generate content that is interesting that can help you speed up your activities,” Brown says. One 2023 study by a multidisciplinary team of researchers at MIT Sloan, Harvard Business School, and other top institutions found that generative AI can improve a highly skilled worker’s performance by nearly 40% compared with workers who don’t use it.
“It's an opportunity to be better versions of ourselves in terms of the way we work,” Salleb-Aouissi says. “Maybe we can do better. Maybe we can be more creative because we have more time. It can break barriers that people have.”
You can improve accuracy
People make mistakes. Machines can make mistakes, too (more on that below), but they also can’t forget, get distracted, or be influenced by emotion—all risks that can lead to human error.
“There have been a number of research studies that have shown that AI-assisted reviewing of mammograms are more accurate than doctor-only reviews of those mammograms,” Ives says. “It’s not to say that a doctor or healthcare provider shouldn’t be in the loop. It’s to say, ‘This is a real tool that can help us do our job better. We can find signs of breast cancer sooner, quicker, faster.”
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What are the potential challenges and cons of AI?
Nothing is perfect, including AI. Read on for some of the major challenges experts believe this technology poses.
Bias
Artificial intelligence is only as good as the data it’s provided. “Unclean” or messy data that incorporates inaccuracies, holes, or only select information will naturally lead to technology that’s inaccurate, biased toward or against individuals or ideas, lacks certain competencies, or “hallucinates” (yes—makes stuff up).
“Human beings aren’t purposefully building biases into models—but there are biases in all of us, and it gets built into the model,” Ives says.
AI also needs humans to “tell” it what’s right and wrong—or at least provide the context for figuring it out correctly. “It doesn’t do very well at figuring out what source of information to trust,” notes Colin Treseler, CEO of AI meeting assistant Supernormal, who previously worked on machine-learning teams at Meta and Klarna.
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Legal and ethical implications
By exemplifying human behavior, artificial intelligence puts itself—and its creators and users—at risk of breaching legal or ethical rules. For example, Salleb-Aouissi asks, “Who is liable [for a] self-driving car if it has an accident?”
“Decisions made by AI can raise real concerns around fairness and accountability, and there are real ethical concerns that we as human beings need to be aware of,” Ives says. Many ethicists, researchers, and policy makers have already taken it upon themselves to start conversations around this topic.
Bad actors
AI can be used for good and for bad. As it becomes more ubiquitous, many advocates and adopters must grapple with what to do when it's used for nefarious means.
“There’s a big fear of any technology, no matter what it is—whether that’s nuclear power or AI—finding its way into the hands of bad actors, and how do we reduce the impact of the use of the technology for bad intentions?” Brown says. Recently, OpenAI announced that it had deterred several covert influence operations in Russia, Iran, Israel, and China from using its models for deception.
Security of data
Kate Den Houter, an industrial-organizational psychologist researching AI in the workplace for Gallup, says many companies are wondering how they can protect sensitive, confidential, or proprietary data as their teams incorporate AI more and more into their workflows. For example, tools like Cisco’s AI Defense are growing in development, adoption, and reach.
“Communication is going to be key for organizations when it comes to implementing this type of technology into their workplaces,” Houter says. “They’ll need to be clear about the strategy and how employees can utilize this, so that these tools can be a way to further innovation and efficiency, rather than becoming a liability in terms of data privacy and security.”
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Supply of power
It takes a lot of electricity to power a large language model, and many experts worry about the strain increased adoption could put on our systems. This has implications for consumers and businesses, like a rise in costs or supply chain blockages, as well as our environment if we continue to increase our carbon footprint and stale renewable energy efforts. States, too, are seeing a strain on their power grids, and many lawmakers and advocates worry how AI could be contributing to natural disasters.
Complexity and rapid pace of development
Very few people understand the intricacies of AI, and that can lead to trust issues, Ives says. Without trust, people might stray away from important and crucial tools, or mishandle it or the knowledge of it. Throw in the fast pace in which this technology is being developed and adopted, and a lot of negative emotions can arise.
“The fear of change holds people back,” Brown says. “That creates rumors, scams—all of that stuff.” The more misinformation and fear spreads, the less likely companies and individuals can focus on the good things AI can do.
What does the future of AI look like?
No one can truly predict the future, but experts say we’re likely to see the following trends over the next few years.
More adoption
Experts agree that AI will become increasingly prevalent in all aspects of society and industry.
“It’s new and exciting, with what seems like limitless potential applications,” Den Houter says. “A lot of companies are still just sort of at the start of their journey when it comes to AI. So I think we are going to see organizations continue to invest.”
Multimodal AI
Multimodal in AI refers to models that can interpret multiple types of data. For example, a chatbot that can both read text and images.
This is already the case for many popular apps, but Salleb-Aouissi believes this will only become more commonplace, essentially ensuring these tools can do as many tasks (and as many complex tasks) as possible in the shortest amount of time and with the most amount of accuracy. For example, she says, multimodal AI could revolutionize genetic research by analyzing biomedical data, health records, and possibly even DNA.
Advancements in regulation
Because of all the legal and ethical ramifications of letting a machine make business and personal decisions—and leverage those decisions on data that’s owned by a variety of parties— experts expect there to be more talk of regulation. In the U.S., that might mean standards around how this technology is built and used, or transparency around data usage.
Investments in AI training
Den Houter notes that because AI is still a fairly new concept for many, we’re probably going to see more investment in training and skilling up employees in this area.
“Very few employees feel prepared to work with this,” she says, citing Gallup’s report that only 6% of employees feel very comfortable using AI in their roles. “In fact, we actually saw a drop from our 2023 survey to our 2024 survey by six percentage points.”
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Continued need for humans in the loop
All experts agree that AI cannot function in its current and expected forms without some human interference. “Human-in-the-loop is so critical to artificial intelligence and how we leverage it,” Ives says. For example, social media managers could use GenAI to come up with ideas for LinkedIn posts, but would still need to be involved in copyediting text and overall content strategy. Similarly, coders might leverage AI to build apps faster, but with their keen eye they’re able to catch bugs or steer the AI in the right direction in terms of how the app is formatted.
“It’s a real companion,” Brown says. “I’m not seeing huge amounts of no-human-in-the loop solutions, especially when it comes to human-to-human interaction being replaced. There’s a huge amount of capability and speeding, where your process becomes quicker, more efficient, more accurate—but you are not removing the human from the loop in its entirety.”
How will AI affect workers now and in the future?
AI is already here, so you likely already know whether it’s directly impacting your job or career path. If it’s not part of your routine now, experts say you should prepare for its role in your life to emerge in short order.
“There’s inevitably going to be some trial and error as organizations figure out the best place to incorporate AI technology and tools into their workplaces,” Den Houter says. “But employees are increasingly going to see these types of tools being offered.”
Ultimately, because human-in-the-loop is so critical at this stage of AI, there’s little worry from experts that workers are going to be completely replaced by machines. Like with any major advancement, such as the dawn of the digital age, our workforce is going to have to adapt—but not cease to exist. “There will be jobs that will disappear, and jobs that will appear,” Salleb-Aouissi says.
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How can you stay informed on AI trends and tools?
The ever-evolving AI landscape can be intimidating, but there are plenty of ways to stay educated and updated on where the technology is going and how it might impact you. Brown notes that your first stop should be to ask AI itself what the latest trends are. “The best thing about AI is you can use it to research what AI tools you should be using,” he says.
Following leaders in the space on social media is also a great strategy. Both Ives and Treseler say they set aside time to track news and discussions on the topic. “I am an AI expert, and on a daily basis I'm looking up information and following certain thought leaders that I trust and that I really enjoy, and that put out a lot of really good information into the world,” Ives says. She recommends voices such as Sabrina Romanov, Allie K. Miller, Cassie Kozrykov, Swathi Young, Meghan Anzelc, Kevin Tupper, Kellee Franklin, and Liza Adams.
Another thought leader in AI, says Salleb-Aouissi, is Andrew Ng, who also teaches AI courses on learning platform Coursera. Alongside his lectures, Ives says, you could explore content on Code.org, DeepLearningAI, InnovateUS, and the Marketing AI Institute, or through learning modules by Google, Amazon/AWS, Microsoft, and LinkedIn. Finally, Treseler says, you could subscribe to newsletters or blogs related to popular technologies, such as Anthropic’s newsroom or OpenAI’s news portal.
“Just being online is the best place to see what is coming out with this technology,” Den Houter says.
Embrace AI, don’t fear it
Bottom line: You don’t need to be an AI know-it-all to succeed long-term in your career and outside of it.
“It’s a bit like driving a car—I don’t know how a full stroke combustion engine works, but I know how to drive a car,” Brown says. “You don’t have to know how AI works to take advantage of some of the capabilities. You need to know the features and functions of what the tool can do and whether it suits your needs.”
The most important thing, he says, is being open-minded and curious. “It’s happening, and therefore the quicker you can get yourself through the change curve and start using some of these tools and understanding how they can be a really positive benefit to you achieving your goals—whether that’s personally or from a work perspective—then you’re going to find yourself in a better place.”
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