AI is changing entry-level work, especially in video production, content creation and digital marketing.

Tasks that were once commonly assigned to interns or recent graduates—research, first drafts, content ideas, transcripts, social copy, outlines and basic organization—can now be completed much faster with AI.

That can reduce the need to hire someone solely for routine execution. But it also creates an opportunity.

The answer is not to compete with AI. It is to learn how to work with it well enough that you can contribute at a much higher level, even without years of experience.

I started thinking more seriously about this after listening to an episode of The Journal, a podcast from The Wall Street Journal, called “AI Is Coming for Entry-Level Jobs” (also available on Spotify and Apple Podcasts). The episode explored how companies are reconsidering roles traditionally filled by recent graduates as AI becomes capable of handling more of the work once assigned to them.

I am not a labor-market expert. But as a senior producer who has supervised many interns, I can see that the expectations surrounding entry-level work are already changing.

An intern who knows how to use AI properly can research faster, explore more options, solve problems more independently and arrive with a stronger first draft. In some cases, they can begin contributing with the capacity we might previously have expected from a more experienced employee. They still need guidance. But they do not need to be given every single step.

Knowing how to use AI is not enough.

Typing a question into ChatGPT is not a professional skill by itself.

The value comes from knowing what to ask, what context to provide, how to evaluate the response and how to improve it.

AI can produce polished work that is generic, inaccurate or completely wrong for the project. It can generate ten ideas without recognizing that none of them fit the audience. It can write quickly without understanding the brand, the objective or the larger strategy. A strong employee does more than generate output. They review it, question it, refine it and take responsibility for the result. That is why professional fundamentals still matter. Someone working in digital marketing needs to understand the audience, platform, campaign goal and brand voice. Someone working in production needs to understand story, logistics, deadlines and how their task affects the rest of the project. AI can accelerate the work. It cannot replace judgment.

Initiative is what makes someone stand out

Of all the qualities I look for in an employee or intern, initiative may be the most important.

The people who stand out do not wait to be given every single direction. They observe what is happening around them. They understand what the team is trying to accomplish. They recognize when someone needs help and offer it. When they are given a task and encounter a roadblock, they do not immediately stop and ask their supervisor what to do next. They first make an effort to solve it. They review the information available. They research possible answers. They try another approach. They use the tools they have, including AI, to move the task forward. Then, when they do ask for help, they can explain what they tried, what they learned and where they are still stuck. That makes a major difference.

The two interns who have stood out most to me both had strong initiative. They communicated clearly, took ownership of their work and were not afraid to say:

“I don’t know.”

Or:

“I haven’t done that before, but let me figure it out.”

That kind of honesty is far more valuable than pretending to understand something. An employer does not expect an intern to know everything. We do want someone who is willing to learn, resourceful enough to begin and confident enough to admit when they need guidance.

AI makes initiative more powerful

AI gives entry-level employees more ways to demonstrate initiative.

Instead of returning with one obvious content idea, an intern can explore several directions, compare them and recommend the strongest one. Instead of handing over a collection of unorganized research, they can summarize it, categorize it and identify the most relevant findings. Instead of waiting for someone to explain how to begin, they can develop a preliminary approach and bring it to their supervisor for feedback.

In digital marketing, that could mean using AI to:

– Research an audience or industry
– Develop content ideas
– Draft and adapt social media copy
– Organize keyword or competitor research
– Repurpose a long-form piece into smaller assets
– Prepare the first version of a content calendar

In video production and content creation, it could mean using AI to:

– Develop interview questions
– Research a subject
– Summarize transcripts
– Organize production notes
– Identify possible story themes
– Prepare a creative brief
– Create supporting content for a video release

The goal is not to hand AI-generated work to a supervisor and consider the task complete. The goal is to use AI to get further on your own before asking someone else to step in. That makes mentorship more productive. A supervisor can spend less time explaining how to begin and more time helping the person improve their thinking, decision-making and professional judgment.

Do not use AI to pretend you know more than you do

AI can make an applicant sound more experienced than they are.

It can write a polished cover letter, generate sophisticated language and help someone speak confidently about a subject they barely understand. That may help someone get through an initial application, but it becomes obvious when they are asked to explain their reasoning or perform the work. It is better to be honest. Saying, “I haven’t done that before, but I know how I would begin figuring it out,” shows self-awareness and initiative. Using AI to learn, research and prepare is valuable. Using it to manufacture expertise is not.

Work with AI, not against it

Recent graduates cannot create years of experience overnight. They can show that they know how to become more capable with the tools available to them. An entry-level employee who uses AI thoughtfully, takes initiative, communicates clearly and accepts responsibility for the outcome can contribute very differently from someone waiting to be assigned a list of basic tasks. From an employer’s perspective, that changes the question. It is no longer only:

“Do we have enough entry-level work for this person?”

It becomes:

“Can this person use AI and their own judgment to help the team accomplish more?”

That is the opportunity. Do not try to prove that you can complete routine work more cheaply than AI. Show that you can direct the tools, solve problems, make decisions and take ownership of the result.

To help recent graduates and junior professionals put this into practice, we created The AI-Ready Guide and Checklist. It outlines the habits, skills and AI workflows that can help an entry-level candidate become more resourceful, contribute more independently and stand out to a potential employer.