For the past few years, much of the conversation about artificial intelligence has centered on one question: Is AI going to take my job?
It’s a reasonable concern. But another question is emerging, and it may have more immediate implications for employers and employees alike.
What happens when your employer expects you to use AI, and you don’t want to?
That isn’t entirely hypothetical anymore.
Some major employers are moving beyond encouraging employees to experiment with AI and are making its use an expectation. Accenture, for example, has tied the use of its AI tools to eligibility for promotion. Other companies are increasingly looking for AI skills when hiring.
We’re moving from a conversation about whether AI will replace employees to one about whether employees who refuse to use it will remain competitive in the workplace. And I suspect that shift will eventually reach businesses of every size, including those here in East Texas.
We’ve Been Here Before. Sort Of.
There was a time when knowing how to use a computer wasn’t a basic requirement for many jobs. Neither was email or a spreadsheet. Today, most of us wouldn’t think twice about expecting employees to use those tools when necessary. AI may be headed in the same direction.
But there’s an important difference. AI can generate information, analyze data, and make recommendations. It can also produce convincing but inaccurate information and create problems when sensitive information is handled carelessly. That means learning to use AI requires more than technical skills. It requires judgment.
An employee who uses AI to produce twice as much work isn’t necessarily twice as productive. If the work is inaccurate or has to be redone, what have we accomplished?
The goal shouldn’t be to use AI simply for the sake of using AI. The goal should be to do better work.
Not All Resistance Is the Same
Here’s something I find interesting. We tend to assume younger employees will be the most enthusiastic about new technology. But that isn’t necessarily true with AI.
A 2026 Gallup study found that 48% of employed Gen Z respondents believed AI’s workplace risks outweighed its benefits, even as many were using the technology themselves. That suggests something more complicated than a generation simply resisting change. And the concerns aren’t limited to younger workers.
Some employees question how AI systems are trained, their environmental impact, the use of copyrighted material, or whether relying on AI diminishes human creativity and judgment. For some, these aren’t simply concerns about learning new technology. They’re moral objections to using it.
There’s a meaningful difference between someone unwilling to learn and someone who believes using a particular technology conflicts with deeply held convictions. Good leadership requires recognizing that distinction, even when we don’t necessarily agree with the objection.
Responsibility Goes Both Ways
I understand why employers are establishing expectations around AI.
Businesses face constant pressure to improve productivity, manage costs, and remain competitive. When a tool has the potential to help, it’s reasonable to expect employees to learn how to use it. But there’s a difference between expecting people to adapt and expecting them to figure everything out on their own.
If an employer makes AI part of the job, that employer should provide direction and training. What tools are employees allowed to use? What information can they share? What work requires human review? And what does successful use of AI actually look like?
Those questions are probably more important than deciding which AI subscription to purchase.
Employers also need to listen when employees raise legitimate concerns. That doesn’t mean every objection can be accommodated or every job requirement eliminated. It does mean we shouldn’t automatically confuse conviction with resistance to change.
Employees have responsibilities, too. Technology, customer expectations, and business models continually change. The skills that made someone successful ten years ago may not be enough ten years from now.
Not everyone needs to become an AI expert. But refusing to understand how emerging technology affects your work could eventually limit your opportunities.
What Does This Mean for East Texas?
When we talk about AI, it’s easy to picture large technology companies with enormous budgets. But the implications are just as relevant for a local accounting firm, insurance agency, manufacturer, construction company, or retailer.
AI won’t be equally useful in every job, and not every task should be handed over to a machine. For smaller businesses, there’s also a practical concern. Employees may already be experimenting with AI, whether their employers realize it or not. That makes establishing reasonable guidelines and involving employees in the conversation particularly important.
Rather than starting with a mandate, perhaps the better question is: What part of your work could be done better if we gave you the right tools and training?
The answers might surprise us.
The Real Competitive Advantage
I don’t believe the businesses that succeed with AI will necessarily be the ones that adopt the most tools or require the most employees to use them. I suspect they’ll be the ones that combine technology with people who understand their customers, exercise good judgment, and are willing to keep learning.
Employers need to provide direction, training, and an environment where people can raise concerns without automatically being labeled resistant to change. Employees need to recognize that adaptability is increasingly part of what makes them valuable.
The question facing businesses may no longer be whether artificial intelligence belongs in the workplace. Increasingly, it already does. The more important question is whether we’re approaching its adoption with the leadership, judgment, and mutual respect it deserves.
And perhaps the question for employers isn’t simply whether employees are willing to use AI, but whether we’ve given them good reasons, clear expectations, and the confidence to use it wisely.
