AI insights series #2: You probably won’t lose your job to AI (but you might lose it to this person)

Weston Morris, Senior Director of Global Strategy, Digital Workplace Solutions at Unisys

Editor’s Note: This article is part of an exclusive series featuring insights from our latest ebook, AI in the workplace: An expert’s guide for CIOs. We sat down with AI leaders from Microsoft, Google, Logitech, and Unisys to move past the hype and get to the practical realities of AI at work.

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There’s always been a technology gap between frontline workers and information workers. And unfortunately, for a long time, that gap was widening.

Eight out of ten employees are frontline workers. They’re the people in factories, hospitals, and retail stores who keep the world running. Yet, historically, they have been left behind by the digital revolution. While knowledge workers got Slack, Teams, and Zoom, frontline workers often got … a bulletin board in the breakroom.

But recently, I’ve seen a shift. Unified communication vendors are embedding generative AI into their platforms and consciously providing lower-cost licenses specifically for the frontline.

Now, someone on a factory floor or in a hospital ward can use AI to find information, summarize lengthy documents, or quickly create instructions for peers. AI is finally breaking down the silos that have kept these teams disconnected. But with this new connection comes a new fear: “Is this technology going to replace me?”

Here’s the honest conversation we need to have about AI, jobs, and the future of work.

The replacement myth

Let’s address the elephant in the room. When it comes to AI, employees are afraid of losing their jobs.

It’s true that some jobs currently fulfilled by humans will be replaced by AI. But it will be much more common for AI to augment human tasks.

Think of it this way: You probably won’t lose your job to AI. Instead, you may be at risk of losing your job to someone who knows how to use AI better than you do.

AI creates a need for entirely new roles – training models, optimizing data, classifying information, and analyzing business processes. The best thing you can do as a leader is to provide training so existing employees can step into these new, AI-enabled roles.

Building a culture of trust

If employees are scared, it doesn’t matter how rosy of a picture their leader’s paint. Workers will create their own narrative based on their worst fears.

That’s why it’s critical to start with a culture of trust. If you don’t put that in place first thing, your AI rollout will likely stall. 

You can do this by engaging employees in the process. Ask for their feedback. Find out who the “tech trailblazers” are in your organization – the people already adopting these tools – and use them to evangelize the benefits to their peers through gamification, podcasts, or town halls.

When that trust is in place, you can start having more honest conversations about the future. You should outline the overall goals for using AI, but also be vulnerable enough to admit that you don’t have all the answers.

Unexpected AI wins in the wild

When you empower employees with AI, the results can be surprising. Beyond typing prompts into a chat box, you need to remove barriers that we assumed were permanent.

For example, we utilized Appspace’s AI translation features at a recent sales training event with hundreds of associates from around the world. It helped colleagues speaking Portuguese, Mandarin, English, German, Dutch, and Spanish communicate seamlessly.

Normally, language barriers would divide these groups. But AI enriched their interactions in a way that simply wasn’t possible before.

Another example: A colleague traveled to our headquarters in Blue Bell and needed to set up a printer. Historically, this is an exercise in frustration – finding the right driver, the right IP address, the right room.

She asked an AI agent for help. The bot recognized she was physically in the Blue Bell office, told her exactly which three printers were available in that specific building, and gave her the correct setup instructions for the model she chose.

That’s the power of AI, It takes a moment of frustration and turns it into a moment of “magic.”

Avoiding the “garbage in” trap

But, there’s a catch. Generative AI is only as good as the data you feed it.

I see a few main challenges in proving AI’s value, and data hygiene is the biggest one. Generative AI will quickly reveal how well you’re classifying and controlling access to your data.

If you haven’t done the work, generative AI will find that out-of-date policy document from 2010 and present it as fact. Even worse, if you have poor access rules, AI might share your confidential client list with a contractor or reveal bonus payouts to the wrong department. The old maxim of “garbage in, garbage out” applies even more in the age of AI.

Before rolling out any form of AI, take a detailed look at your data hygiene. Any flaws in your data management will be magnified the second you turn the AI on.

Choreographing your AI

As time goes on, enterprises will collect multiple AI bots, all providing niche services. You might have a bot for HR, a bot for IT, a bot for facilities, and a bot for finance.

The challenge of the future won’t just be using AI to choreographing it. How do you integrate multiple bots in a secure fashion? How do you prevent them from hallucinating or giving conflicting advice?

We don’t have to wait for the future to see the risks of blindly accepting AI’s recommendations. But if we focus on training our people, cleaning our data, and building trust, we can turn those risks into a competitive advantage.

Want more workplace AI insights?

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