I was a newly-minted lawyer when mergers and acquisitions were on fire. Everywhere you turned, companies were gobbling each other up, grabbing synergies and reducing costs. People were petrified of being rendered obsolete and losing their jobs. One woman’s magazine ran a piece I will never forget. Headlined “Makeover for a Takeover,” the concept was absurd. You may not know what’s coming down the pike, the article posited, but if you’re wearing the right clothes and sporting the right hairstyle when the acquiring company shows up, you could stand out and survive.
Yesterday’s M&A feels a lot like today’s AI, except the absurd articles are about robot takeovers, not makeovers. The fact is, despite the fear and hype, generative AI remains an enigma. A recent McKinsey study reveals that 63% of leaders feel that AI must play a significant role in their business but 91% don’t yet know how. At the same time, there’s a palpable sense of urgency: Mercer reports that over half of C-suite executives believe that their business will be dead by 2030 if they don’t embrace AI. Uncertainty and speed are scary bedfellows: 79% of Americans do not trust corporations to make responsible choices about implementing AI.
The vast majority of experts believe that AI will support—not replace—human performance. But people who use AI will likely replace those who don’t. You have a choice. You can ignore AI until you have a better sense of how it will affect your life. Or, you can be proactive. There has never been a better time to lean on your growth mindset- to become an avid student of this vast and fast technology. Here are five ways to build the skills you need to survive.
Get Ahead Of The Learning Curve
The jargon around AI is like a new language. Start by learning as much as you can. There are hundreds of free courses on LinkedIn Learning alone. And for a small investment, you can earn a certificate from an online provider like Courseror MIT. Knowledge is power, and with a little work, you can flex yours.
Beyond just learning how AI works, explore where it works—or doesn’t. AI has promise, but it's not without pitfalls. For example, many companies are using hiring algorithms to surface talent. Are they missing good people because their algorithms are too narrow? Inundated when they’re too broad? Understand how companies are using AI well and where they’re stumbling. Listen to podcasts, and sign up for tech newsletters. Explore the philosophical and moral quandaries that underlie AI’s potential for good and bad. Like Alice in Wonderland, embracing the rabbit hole means exploring at every turn. It’s amazing how proficient you can become when you let your curiosity take the reins.
Experiment A Lot
Adopting an experimental mindset is the best way to gain in-the-trenches experience. Start with a non-proprietary work project. Feed it to a large language model like ChatGPT and ask it what it would add. Prompt it to rephrase your work for a non-English speaker, or to recast it for someone without expertise. Because you are experimenting in a field you already know, you will quickly gauge the value of its inputs. And it will also encourage you to see your own work from different angles.
Experimenting with this technology doesn't have to mean more work. You can play with AI to write your memoir in the style of your favorite author, or animate your doodles or your children’s artwork. There’s a brand new platform that uses AI to turn a still picture into an avatar that talks to you. And If you’re a history buff, you can chat with historical figures. When creative endeavors are your jam, the AI-driven experimental possibilities are endless.
Don’t Accept AI At Face Value
Large language models, with their very human-like communications, can feel misleadingly like experts when they produce data-rich answers in record time. But they can hallucinate—make up responses where their training data is lacking based on plausible but incorrect logic. And AI algorithms have been known to rely—like humans—on shortcut learning, causing false correlations, amplifying discrimination and producing unreliable results. Don’t accept AI’s outputs at face value. Challenge assumptions (its and yours) and triangulate with other research.
In my first foray with ChatGPT, I sought research-based insights, together with the relevant sources. Impressed by the outcomes, I looked up the sources, only to find that the authors and the journals were real, but the papers didn’t exist. When I asked ChatGPT where it found these sources, it responded that these papers were not real, but would be the type of papers to cite if they were. A colleague shared a brilliant piece of advice: “Treat AI like a first year intern,” eager to please but far from perfect.
Get Really Good At Asking Questions
New technologies cultivate new jobs. And AI is proving to be fertile soil. The World Economic Forum named prompt engineering—the art and science of asking the right questions—the #1 job of the future in 2023. Asking good questions helps you learn from diverse perspectives. Engaging with algorithms is no exception: better questions give you more outputs to explore a wider array of possibilities and find better solutions.
The most effective human questions are open-ended, curious and personal. But when it comes to an LLM, clarity is king. Frame the context of the inquiry (e.g., a report, strategy, job description) and the perspective you want the LLM to take (e.g., a specific point of view, a particular profession or an identity). Provide context: what you need and what you want to do with it, examples, process steps and even desired references. Finally, spell out the output, including format and style. The art of good prompts allows AI to handle the rote retrieval of technical information, freeing humans to access and curate a wealth of knowledge, and to combine and rapidly test new ideas in even the most technically complex contexts. Done well, it’s a powerful man-machine partnership.
Don’t Go It Alone
In the zeal to adapt, don't forsake the superpower that makes humans more effective than any machine: our ability to work and thrive in community. Throughout history, humans have leveraged their collective strength to make sense of thorny challenges and new threats. Working with others helps you experiment broadly, debate ethical implications, and share results to learn faster. And collaboration neutralizes the anxietythat comes with impending existential change. Widening the group of AI learners in your organization helps you to be part of crafting the strategy instead of waiting to see where the chips fall. Build a broadly diverse learning community to garner the best and most varied ideas. Your collective wisdom will make you and your colleagues indispensable to your organization’s AI future.
Thankfully, you don’t need a makeover to weather the AI storm. But your mindset probably does. This is not the time to take a wait-and-see approach. Even if it’s hard to imagine how generative AI will affect your job right now, the train is already barreling down the tracks. To stand out from the crowd and be ready for what comes, get ready now. A deeper understanding of AI and its trajectories is one of the most effective job skills you can develop—for today and tomorrow. The only thing we know for sure is that AI will fundamentally change the world of work. Instead of waiting for the road to clear, forge the path.
First published on Forbes.com.
