Dr. Angela Jackson has spent over a decade studying the future of work from the inside — embedded in companies, running research teams at Harvard, and advising organizations navigating some of the most disruptive transitions in modern business history. When she’s asked what comes to mind when she hears the word AI, her answer is one word: neutral.
Not threatening. Not exciting. Neutral. Because in her view, what AI actually does to your career, your workplace, and your sense of agency depends almost entirely on the intent of the people deploying it — and on the choices you make about how to engage with it.
In a conversation with Women Amplified host Lisa Bennett, Dr. Jackson offers a grounded, research-backed framework for staying human, staying sharp, and staying in control as AI reshapes everything around you.
The Worry Is Legitimate — But So Is the Agency
Dr. Jackson isn’t here to dismiss the anxiety. She has a 19-year-old daughter heading into the job market and thinks about what AI will mean for her regularly. She believes anyone who thinks this technology won’t touch their work life is wrong.
But she draws a distinction between fear and discernment. Most of the loudest AI headlines, she points out, are less about the actual state of the technology and more about market signaling — executives making dramatic announcements about workforce reductions that tend to move stock prices in the short term. Her research team is now tracking those announcements against market performance over multiple quarters to see whether the cuts actually stick, or whether companies quietly rehire.
“We have to interrogate the intent behind that. A lot of that is about market making.”
The counsel she gives her daughter, her students, and the women listening: read the headlines with discernment. The rhetoric and the reality are often very different things.
The Struggle Is Where You Build the Thing AI Can’t Replace
One of Dr. Jackson’s sharpest observations is about what gets lost when people outsource their thinking too early. When you write something yourself, wrestle with a problem yourself, and fail at something yourself, you develop an internal sense of what good looks like. That standard becomes the lens through which you evaluate everything — including AI output.
Without that standard, you can’t tell when AI gives you something average. And AI gives you something average a lot.
She describes a moment with her own research team: a doctoral student, under pressure, let AI take a first pass at a white paper and submitted it up the chain believing it was good enough. It wasn’t close to the team’s usual quality, and it bore no resemblance to their prior work. The teaching moment wasn’t about the technology. It was about what happens when you haven’t invested enough time to know what good looks like in the first place.
“Unless we really understand what good looks like, you will put things into AI and get things back that could be average or even below average — and it may seem good enough.”
Her advice for students and professionals alike: write your first draft yourself. Do the thinking before you check it. The struggle isn’t inefficiency — it’s the mechanism by which you build expertise that AI can’t replicate.
“Work Slop” Is Real, and It’s Easy to Spot
Dr. Jackson doesn’t shy away from the quality problem AI creates at scale. When everyone uses the same tools to produce the same kind of output, the results converge toward a recognizable average. She’s seen it in her students’ papers, in the proposals her colleagues receive, and in the proliferation of a single telltale punctuation mark.
“We all know the em-dashes we’ve been seeing more of. I’ve never seen more em-dashes in my life, and it’s a telltale sign.”
The risk isn’t just quality degradation. It’s the unintended signal that AI-slop output sends about the person submitting it — that they prioritized speed over thought, and that their “perfect” deliverable has no real thinking behind it. Recruiters and hiring managers are already noticing. Resumes and cover letters have never looked more polished, and interviews have never revealed a wider gap between what someone appears to be on paper and what they can actually do in the room.
Tinkering Is Not the Same as Depending
Dr. Jackson is not anti-AI. She actively encourages people to experiment with the technology, build familiarity with its capabilities and limits, and understand how it applies to their specific role and expertise. Leaving the workforce or graduating school without a clear-eyed sense of how AI can and can’t augment your work puts you at a disadvantage.
The distinction she draws is between productive engagement and passive dependence. Tinkering means you’re driving. Depending means you’re not sure what you’d do if the internet went out.
She also raises a less-discussed challenge: cognitive overload. Automating routine tasks doesn’t eliminate the management of those tasks. Reviewing AI output for accuracy, voice, tone, and quality is still work — and for many people, it’s a new layer of work added on top of everything else. The actual time savings, she argues, will take time to measure accurately.
What Grounded Leadership Looks Like Right Now
For women in leadership — already navigating the pressure to conform to cultures that weren’t built for them — Dr. Jackson’s research offers something concrete: companies that invest in the human side of transformation perform measurably better. Her study of over 17,000 companies and 200,000 workers found that roughly 30 percent were implementing what she calls human-centered practices, and those companies showed higher earnings per employee, stronger retention, and better stock performance over time.
The practices that made the difference weren’t perks. They were structural: benefits realigned around what employees actually need (childcare stipends, student loan repayment, elder care support), training extended to front-line and middle management rather than concentrated at the top, and genuine space built into the workday for experimentation and curiosity.
Her message to leaders feeling the pressure to follow the cost-cutting playbook: you can only cut so much. The companies that will be durable are the ones figuring out how to use AI as a force multiplier for their people — not a replacement for them.
What She Does When the Headlines Get to Her
Dr. Jackson grew up with a grandfather who built a family and a career from a factory job in a segregated South. When she reads headlines about AI eliminating entire job categories, she thinks about the real people behind the numbers — the workers whose livelihoods and dignity are tied up in those statistics.
That’s what triggers her. And what grounds her is returning to the data: the 30 percent of companies doing it right, the evidence that human-centered investment produces measurable returns, and the belief that in a competitive market, the model that actually works will eventually win.
She’s betting on the humans.
The Bottom Line
Staying grounded in the age of AI isn’t about ignoring the disruption or pretending the anxiety isn’t real. It’s about building the internal capabilities that technology can’t replicate — genuine expertise, a calibrated sense of quality, and the tolerance for struggle that develops both. Do the work. Tinker with the tools. Read the headlines with discernment. And don’t confuse a polished output with actual thinking.
The agency was always yours. AI just makes it more important to exercise it.
This post is based on an episode of Women Amplified, the podcast from the Conferences for Women, featuring Dr. Angela Jackson, CEO of Future Forward, Harvard lecturer and researcher, and author of the New York Times bestseller The Win-Win Workplace.
