In this employee spotlight Q&A, we sit down with Joseph Ours, Centric Consulting’s AI Strategy lead, to explore his perspectives on artificial intelligence and its transformative impact on business and society.
With a background rooted in technology and a self-described “science fiction geek,” Ours shares insights on AI’s evolution and its implications for the future of work.
How did you become interested in AI technology?
I’ve always been interested in technology and been a science fiction geek, so the future possibilities of technology have always captivated my attention. Like most people, I really started paying attention when ChatGPT emerged in late 2022.
When I began exploring its capabilities, I recognized it as a game-changing development within the AI space. It allows us to do some unique things we’ve not been able to do before. I realized that inside Centric, we needed to get ahead of this because it would absolutely change the shape of work in the future, and I don’t want to be on the wrong side of that change.
What drew you to focus on AI?
Large language models exist in the world of predicting words from a language perspective, and everything we do — every idea we want to communicate — is done through language. Whether it’s an engineering drawing, an electrical diagram, or coding, our society is governed by language.
Having large language models that can participate in that conversation and help facilitate tasks at scale and quality better than what we might be able to do on our own absolutely represents a societal-level transformation. That’s when I knew I had to get ahead of it and started becoming familiar with the technology, its capabilities, and its limitations. I knew I needed to wrestle that bull to the ground.
What does your typical day look like?
A typical day is filled with pretty much talking all day long. While there’s client delivery work, a lot of what I do involves educating, bridging gaps, and helping people understand various aspects of AI — from the technology itself to understanding how it solves problems, the risks it might pose to an organization, or envisioning future possibilities.
No day is exactly the same or highly repetitive. There are always new AI developments emerging, and different clients have different situations, concerns, constraints, needs, and desires. It’s a very engaging, fast-paced environment, and I think that will persist for quite some time.
How is the world talking about AI today?
I’ve observed three distinct groups approaching AI differently:
Skeptics: First, there are the “traditional skeptics” who view AI as mostly hype and question its value and transformative potential. They’re asking: “Is there an AI bubble? Is it popping?” They’re looking for published use cases providing value, and if they can’t find them, they ask, “Can AI truly transform my business?” The challenge they face is understanding the potential impact of AI and how it can help them.
Tinkerers: Then, there are the “tinkerers” who are conducting experiments and proof of concepts, trying to figure out how to scale their initiatives while ensuring reliability and accuracy. They’re asking: “How can I provide reliability and accuracy with what we’re doing? How are how can we scale this beyond an experiment or proof of concept? How do I make sure I select the right tools to avoid being oversold?” Their biggest challenge is working to break out of one-off pilots and scale their AI project.
Visionaries: Finally, there are the “visionaries” who are looking ahead, concerned about the sustainability of AI companies and wondering when we’ll see market consolidation of tools and stabilization of features. They’re asking questions about whether AI companies can stay open and turn a profit, and if not, where does that leave companies using their technology?
“Are we going to be able to capitalize on these gains? When will we see market consolidation of tools?” They don’t want to hitch themselves to a company that may go out of business. Their biggest challenge will be to make sure they’re positioned for whatever the future brings.
How is AI changing the technology landscape?
On the challenging side, generative AI is still early in its maturity. We have many organizations rushing to market with implementations that might not be the best fit. For example, recent studies have shown issues with transcription accuracy that could be problematic in sensitive industries like healthcare.
On the positive side, many firms are implementing AI in measured, pragmatic ways to drive real value. We’re seeing significant improvements in worker productivity through tools like AI copilots, and AI agents are reducing individual workloads by significant percentages.
Additionally, people are starting to understand that AI is more than just generative AI — they’re seeing the broader possibilities across the entire AI umbrella, which has helped AI break out of just the realm of data scientists.
What advice do you give people about AI?
First and foremost: use it. Get comfortable with it. Dive into it. Embrace it. I believe AI is going to be transformative on a societal level, affecting everything from our relationships to how businesses deliver goods and services.
People who use AI are going to displace those who don’t because the productivity gains from using AI in a smart way makes you more valuable. This isn’t like internet technology that you can pick up over five to seven years. The pace of change and capability improvement in the AI space is absolutely astounding, and people need to start getting into it now.
What’s the biggest misconception about AI?
The top three misconceptions are:
- AI is coming for our jobs. I don’t believe that’s true. I think this will be as transformative as the Industrial Revolution, and we will have a displacement of jobs. There may be a lag between that and when new opportunities arise, just like with the Industrial Revolution. There will be a lot of challenges, but it will also be faster, and it will bring job growth in new and different areas.
- AI can do everything. People are looking at AI as being a silver bullet to every problem, and it’s not. It’s a targeted solution to a targeted problem. Understanding how to use it will tell you what issues it can solve. Also, people need to understand that it may not solve 100 percent of the problem, but maybe it can solve 70 percent of your problem 70 percent faster, and that’s nothing to sneeze at.
- There’s no way to measure the value of AI. Value use cases are going to take a while to materialize. It doesn’t happen overnight. You have to make sure you have the right KPIs and track toward the right expectations, which will be key to getting value out of AI.
Do you have any words of advice for a leader searching for an AI consulting firm?
As a leader, you need to understand how AI impacts your organization. It can be helpful to enlist someone who can help translate what’s going on in the space of AI and what it means for your business, workforce, and future.