Retraining, reskilling, upskilling, and AI-aware professional development are the new norm in many jobs, from entry-level to senior executives. Maybe I shouldn’t say “new norm” because workers have been down this career path many times before. When telephone operators were displaced by switching systems 100 years ago, they branched into new areas like directory assistance and customer service. Similar transitions happened in printing plants, branch banks, and elsewhere as new technologies transformed the workplace.
What is new is the dizzying pace of change with AI and the sense that this time the stakes are higher. So don’t be surprised by it; be ready.
A good starting point for many people is to raise their AI IQ by getting hands-on experience with generative-AI tools like ChatGPT, Gemini, Claude, or Perplexity. I recently tinkered with text-to-image creation, and I’ve experimented with using gen AI as a personal coach. Once we’ve chalked up these types of rudimentary learnings, the next steps into things like agentic AI will feel more familiar.
Today’s college graduates may feel especially vulnerable, having spent the past few years learning a vocation only to confront a topsy-turvy job market. One way to adapt is to embrace the principle of continuous learning. For Gen Z, who are digital natives, that may mean becoming early adopters of AI technologies, which can give them an edge.
AI certifications can be a way to come up to speed on complex technologies such as APIs, machine learning, language models, and frameworks. However, not everyone has the time or budget for these programs. Harvard recommends self-directed development through online learning, project-based learning, and even “micro-learning” with bite-sized content during breaks or between tasks.
At Informatica, we’re doing everything we can to help employees quickly ascend the AI learning curve. Our IT organization developed an AI literacy class that has been widely attended. That’s given us a common vocabulary, so terms like LangChain (an open-source framework), retrieval augmented generation (RAG), and vectors (an emerging data type) are more widely understood across teams and departments.
We also created an AI Center of Excellence to establish best practices and synergies across departments and ensure that legal, privacy, and security issues are top of mind for everyone.
As these first-hand experiences show, AI learning and skills development happen best when employees take some of the responsibility on themselves, yet within an organizational culture that values, encourages, and provides career-building opportunities.
That doesn’t mean we all need advanced degrees in AI. LinkedIn also found that “human skills”—things like curiosity, creativity, communication, and courage—may matter the most in today’s workplace.
Frankly, that’s wonderful to see because it signals that the future of work will be an eclectic mix of human skills and AI skills. So, while it’s important to recognize that we must raise our AI proficiencies, it’s equally vital that we bring our best versions of ourselves to work every day.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
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