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By the teams at One Model and Ikona Analytics
Leadership has caught AI fever. They want rapid, AI-enabled workforce transformation. But ask them to invest in the data infrastructure tools that make it possible? Suddenly they’re reluctant.
In other words: The mandate got louder. But, somehow the case got harder to make.
One Model and Ikona Analytics wanted to know why. That's why we gathered a dozen people analytics and HR tech leaders for a working lunch. Not a presentation. A true working session. Attendees ranged from from single-person teams to leaders responsible for workforces in the hundreds of thousands.
We asked them to dissect two things:
- The last investment request that got a no
- The last one that got a yes
What we discovered is that executive enthusiasm for AI is actually a powerful new advantage for the people analytics team. Read on to find out the lessons we surfaced from this session, and how AI can help you secure the tech investment you’ve been gunning for.
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Lesson #1: Luckily, AI and the Data Team Share the Same Needs
Initially, it seemed like AI was stealing the shine from people analytics, outcompeting it for attention and budget. Luckily, that’s not really the case. The leaders who are winning right now realized that AI is not a competitor, but an ally with the same needs as the data team.
That clean, governed data foundation your team always campaigned for? AI can’t function without it. And because AI is increasingly seen as indispensable, it casts the need in a new light.
That means corporate AI fever can be used to your advantage. Your data infrastructure/foundation requests go from “a nice-to-have that the C suite shrugged off” to “an existential imperative if they want their AI to work.” The request that died for a decade lands when it is framed as AI-readiness.
The move, as one participant put it, is to take what you have been saying for ten years, present it as the prerequisite for the AI strategy your board already announced, and watch it get funded. Cleaning up your data foundation with the right tool has become phase zero–the groundwork to be laid before any AI initiative can lift off. Skip it, and you’ll build “confidently wrong” AI on top of broken data, which is far harder to walk back than to prevent.
Pro Tip
Urge Leadership to Instill Data Literacy Before AI Adoption: Several leaders present had lived through a particular warning: data literacy is the thing you cannot skip. You can deploy all the AI you want, but without literacy your people will not understand the answers it gives them, and they will not catch it when it is wrong. One team described a literacy program that was a genuine win, then watched it get downgraded the moment AI became the priority. This is classic “putting the cart before the horse.” Executives remain unaware that prioritizing AI deployment over data literacy and infrastructure will undercut stakeholders’ ability to use the system. Take the initiative to communicate the importance of data literacy to leadership while advocating for the tools you need.
Lesson #2: How You Pitch Data Infrastructure Tools Matters
An Executive “No” Is rarely about the Technology, It’s a Failure to Communicate Impact
When a leader says no to an infrastructure request, they are usually not rejecting the technology itself. They just can’t see how investing in an infrastructure/data foundation tool impacts the rest of the organization. The request lands without urgency, where it is easy to kick the can and conclude that the bubblegum and toothpicks holding things together are working well enough.
Your job is to ensure that leadership understands why that governed data foundation is indispensable to AI.
Here is the narrative to communicate:
- AI-generated work looks impressive at first glance, so bosses and investors often assume it is perfect.
- The problem is that AI makes quiet, subtle mistakes that go unnoticed until they pile up and completely ruin the accuracy of the data, destroying everyone's trust in the system.
- Investing in a data foundation ensures the AI is actually fed accurate, reliable information, preventing those hidden errors from breaking the system in the first place.
The benefits of the data foundation include:
- AI answers that leadership can confidently act on without questioning
- Having a single source of truth for your workforce data
- Avoiding bad advice, poor decisionmaking and the revenue leakage they cause
A recurring lesson we saw in our sessions was that data teams strictly pitch in the language of infrastructure, while the yes they’re looking for quietly lives in issues like governance and business impact. For example, the most powerful question one leader said they’ve ever asked, the one that freezes the room every time, was not about tools at all. It was “Who owns the data?” Point their attention to the lack of ownership, the fragmentation, and suddenly leadership realizes a new benefit angle.
Pro Tip
Team Structure Can Help You Secure a Yes: The clearest structural insight of the day: people analytics teams thrive when strategy, operations, technology, data, and analytics report into a single leader. Under that umbrella, you stop fighting the HR technology team for budget, because it becomes shared budget. You gain a political resource, which often goes further than another technical hire.
You Need to Present the Real Cost as Human, Not Technical
Every team we spoke to runs on what we call human APIs: someone pulls data from one system, joins it by hand, emails it to a colleague, who uploads it somewhere else, on a fragile chain repeated every reporting cycle. When we asked who could relate to this, every hand went up. This fragile, time-consuming labor is invisible to leadership and IT, and it does not scale. Tellingly, the single most common analytics product in most HR organizations is still Excel.
This reframes the business case for a data infrastructure tool. The C-suite considers the cost of the platform. But it’s dwarfed by the cost of inaction, when analysts and non-analysts alike lose countless hours simply holding the pipes together. Put that calorie burn on paper, and a tooling request stops looking like a cost and starts looking like a cost the business is already paying.
The Throughline
The teams that won people analytics funding knew how to relate their request to results people could feel, and rode an AI first agenda that leadership was already gunning for. These positioning changes can help any workforce data team earn a yes for the technology they need to truly perform.
Keep the Conversation Going
This was the first room. We are taking the format virtual as a roundtable series for people analytics and HR technology leaders, same premise, same candor, same Chatham House rules: patterns in, names out. It is not scheduled yet; follow One Model and Ikona Analytics, and we will share details soon.
Three ways to go deeper:
See your whole workforce in one place. One Model brings people, talent, and business data together so your team can answer the questions leadership is actually asking. Explore One Model.
Build the case for investment in about 30 days. Ikona's ISD Lite turns scattered stakeholder evidence into a board-ready people analytics business case you own. Learn about ISD Lite.
Join our AI Infrastructure Community. One Model and Ikona are bringing like-minded professionals together to help each of us transform our orgs for the better. Join the Community
