Thriving Professionally in an Era of AI and Remote Work

It’s common to joke about robots taking our jobs, but beneath that humor lies a genuine anxiety. Every time a new tool emerges, we naturally wonder: What does this mean for my role, my career, and my sense of professional worth?

The emotions and hesitations around adopting new tools are real and expected. We’ve been down this road before: while the conversation around AI reshaping work is more intense due to the speed and continual evolution of the tools available, we’ve had these exact same conversations when other technologies have rolled out. 

When I first experimented with ChatGPT [in a professional setting], it was fun. It was easy to point out the flaws in the work, and I mostly used it to write silly song lyrics about the events of the day. But the tools kept evolving and the flaws became less glaring. Soon it became clear, if I didn’t step up and figure out how to leverage AI in a thoughtful, productive way, I was going to get left behind.

Why We Fear the Tools That Help Us

As humans, we’re wired to assign our self-worth based on what we can do, what we uniquely bring to the table. Naturally, when a tool appears capable of performing some of that ‘uniquely human’ work, our instinctive reaction can be defensive or fearful. 

What separates those who thrive is that they are able to work through that initial reaction and create a new understanding of their self-worth and how they contribute professionally.

A change in how we work naturally forces us to reassess how we value our work, and how we define a successful day. We may ask questions like:

• If I can complete an assignment in half the time, does that mean I have to complete twice as many?
• Do I instead have to massively up the quality, and if so how many good ideas can I produce before the well runs dry?
• If my boss finds out I can do the work faster, is she suddenly going to give me more work to do?

It’s not feasible to give advice on how to adjust your specific work to incorporate the latest tools, and if I did it would be outdated in 3 months when the newest tools arrive. But what I can say with certainty is that every job that has an upward career trajectory requires a constant evolution of how you deliver value. This was true before we all had access to AI supercomputers in our pockets and will remain true in the future.

Pause for a moment to consider:

• How do you define a successful day at work?
• How would you describe an ideal month at your job?

For both of those questions, how much of your answer is things directly in your control, and how much is out of your control? What would have to shift about how you define success for it to be in your control?

AI, Remote Work, and a Culture of Embracing Change

This conversation is all the more complex when you factor in remote work. But it’s the same core question. With the increased freedom and flexibility, how can you do your work differently and better?

It’s not about what remote team culture might be missing from in-office culture, but rather: what meaningful and impactful work can you do with the time you would have spent driving to campus or sitting in traffic?

It’s not about what a tool might take away from our sense of how we value our work, but rather: how do these tools free us up to do more meaningful, impactful, and connected work?

Doing this well requires trust in both directions. For a manager, it requires trust in your staff that they are leveraging the freedom well, proactively communicating about progress, and being transparent when they have capacity to take on projects. For staff, it requires trust in their leadership that they aren’t looking for a quick way to reduce headcount with tools, that workloads are an open conversation, and that learning a new tool won’t be treated as a shortcut to dump work. 

Each new tool is an opportunity to rethink how a role is structured and the best way to bring value to the work. Leveraging that opportunity requires openness from both the manager and staff. If that conversation doesn’t happen, the cost is paid by both parties as well — you end up with an underperforming team and a role that is stuck without an advancement path.

I think PLNU’s Marketing Office, which functions in a primarily remote/hybrid capacity, is an example of this working well. Our team has thrived in the remote-first environment because we’ve done the work of building a culture that supports it. Trust, autonomy, proactive communication, collaboration, and distributed authority. These values don’t just make us feel good — they uniquely position us to thrive in moments of disruption. The same strategies that helped us successfully navigate a complete change in where we work will help us navigate a change in how we work.

Where do we go from here?

There is no across-the-board answer for incorporating new tools into your work. You might already be utilizing AI tools in content creation, communication, business and project management, research, education, public service, or any number of other sectors. But across disciplines, perhaps we can apply to our work the same kind of advice we would give to current PLNU students who are considering how AI tools will impact their future jobs and prospects.

• Treat generative AI as a thought partner. Don’t ask it for answers, ask it for structure. In the same way that you might verbally process an idea with a coworker, have a conversation with the bot. Ask it to ask you what it needs to answer the question, and then let it build a response from your input instead of the general knowledge base
• Experiment, experiment, experiment. Every new tech tool (AI or otherwise) has flaws and limitations when it is released. Try different tools, different prompts, and different models. Compare the answers you get from asking the questions in various ways. Invest some of your saved time in understanding how your bot got to the answer and what blind spots it might have. If you are having your bot help with research, start with the questions you know about, and then ask her to surprise you with ideas you hadn’t considered
• Trust and verify. Think of your bot as a well-trained intern. Most of us are not working at the bleeding edge of this technology; in the majority of cases you can assume the results you are getting back are pretty solid. Do your diligence and verify, but unless you are trying something very edge case, you can probably assume your results are in the realm of relevance.
• Bonus: Stay human. You are going to spend a lot of time conversing with your AI in the future. So, don’t treat your AI like a machine, be human with it (a hat tip to Seth Godin of Seth’s Blog for his great breakdown of this). If you are worried about losing the human touch in your work, one of the quickest ways to do that is by treating your bot like a bot. As Seth puts it: Not because the bot will notice, but because you will. 

Collaboration Acknowledgement: I worked with my GPT to help develop this article. You can see the process I went through here. The article I ended up with is pretty different from where my prompt started, which I think is a good sign. I can’t say whether or not this article is better because I used AI to assist, you the reader will have to decide that. But what I can say for certain is that without a tool to help me organize the thoughts and get started, this article would have remained a sticky note on my desktop, never to be written.