- Anchor AI adoption in strategic goals by defining clear use cases tied to your organization’s broader objectives.
- Ensure responsible AI use by implementing a governance model or committee to advise and guide the process.
- Build a solid foundation by thoroughly vetting vendors and educating employees to support long-term success.
HR operations teams, I have to hand it to you. You’re steering the tech-stack ship, juggling implementations, and somehow keeping everything humming along like a well-oiled machine.
And just when you’ve got a rhythm going, boom! AI shows up like the wild, futuristic guest no one was quite ready for. With so much happening so fast, it’s increasingly difficult to know what’s actually worth your time.
We tackled this exact topic in March’s Talent Table with two brilliant minds: Mark Stelzner, Founder and Managing Principal at HR consulting firm IA, and Bharat Daga, Global Director of IT at Qualcomm, a manufacturer of products, software, and services used in wireless devices.
They broke down the Wild West of today’s tech landscape, dropped some serious truth about AI vendor selection, and shared how HR ops can lead the charge without breaking a sweat — or the budget.
Let’s dig into the highlights.
Related content: A peek inside our latest Talent Table conversation about what HR ops needs to know about adopting new technologies. Watch the full conversation on-demand.
Start with the ‘why’ before the ‘what’
Before you start clicking around for AI solutions, pause and ask: What do we actually need to solve?
“Let’s say we want to reduce our time to hire by X number of days, or we want to improve our employee experience by a certain percentage or have a higher recognition platform adoption,” Daga said. “Those are the key metrics which will put you on the success path.”
In other words: name your problem, then go find the solution.
Stelzner added, “If we can tie the goals and objectives of these particular opportunities to the goals and objectives of the people strategy, as well as our enterprise finance strategy… that [use] case will be approved almost every time.”
Alignment — people, money, mission — is the trifecta to a successful formula for a win.
But remember, AI is not a fairy godmother. Don’t think of it like a magic wand that solves every pain point with a single touch. Stay agile and keep it iterative. Test, learn, adjust. Keep going.
Related content: A lack of AI governance can be a road block when it comes to adopting new AI systems, says Bharat Daga, Global Director of IT at Qualcomm.
Want AI that plays nice? Build a governance plan
Daga shared an eye-opening stat: “Around 60% of organizations today don’t have any sort of AI governance,” he said. “Only 6% … have an AI governance with an HR body embedded in it.”
The problem is that the oversight we desperately need is often missing in action.
When you’re shopping for AI vendors, that lack of governance is a dealbreaker. You need guardrails.
Stelzner also called out a huge red flag: AI illiteracy. “Things are accelerating so quickly,” he said. “Do we really understand what the latest computer chip could achieve … or the difference between China’s advances versus ours in the EU versus here in the U.S.?”
This is why governance matters. — it separates hype from helpful information.
Related content: The employee experience with new AI systems are essential to a successful implementation — and for building a strong foundation.
Vet vendors like your budget depends on it — because it does
If you’re having nightmares about picking the wrong vendor, you’re not alone. Decision paralysis is a common roadblock in this process.
“One wrong move can basically take us back three to five years,” Daga said.
To avoid picking the wrong AI partner, you need to ask the hard questions upfront.
Here are a few starting points:
- Do you have real-life case studies?
- Can we talk to your customers?
- Who’s on your board? Who’s funding you?
- What’s your product update and customer support look like?
Don’t forget the legal stuff — AI laws are changing fast.
“Technology is moving at 100 mph,” Daga said, “On the other side, new laws are coming up. You don’t want to be in a space where you’re not able to utilize these newer technologies just because they don’t have flexibility right now.”
Look for vendors with staying power — and tools that won’t crumble under new regulations.
Build a solid foundation so you’re not constantly starting over
Even the fanciest AI solution will flop if people don’t get it.
That’s why education is key. If your employees don’t understand what the tool does, why you picked it, or how it helps them, they won’t use it.
“Think big, start small, and then scale,” Daga said.
AI shouldn’t be a revolving door of tools and trials. Set it up right, and you can build something that lasts. A solid foundation quiets the skeptics and quickly shows value.
Daga suggests creating an AI center of excellence (COE), a team that owns and oversees AI initiatives across the business. They help connect dots, see patterns, and keep things moving in the right direction. The best part is that these early adopters in COEs also become champions for progress and generate excitement for others to learn, too.
And don’t forget the content to support your goals.
“We often don’t have trusted and sustainable sources of information,” Stelzner said. “If we start to put AI capabilities against disassociated content repositories, we won’t be surprised when hallucination or misinformation is the answer.”
Know where your content lives, who’s maintaining it, and how it feeds your AI systems. Otherwise, things can get messy fast.
Their final note: bring IT and HR together. AI works best when the tech teams and people teams team up.
“If we don’t get buy-in, we will get dissonance,” Stelzner said.
Watch “Everything HR ops needs to know about adopting new technologies” on demand now.
