At Transform 2026, one pattern stood out. Organizations that built a strong HR foundation before deploying AI are now pulling ahead. Their blueprint is something any company can copy.
Every CHRO should bring this finding to their next executive meeting. Organizations that reviewed and rebuilt their strategic HR function before using AI are posting 34% higher business performance metrics: revenue, profitability, and market share. The gap between those companies and the ones that skipped this work is large. It is measurable. And it is still growing.
This signal ran through 82 talks at Transform 2026. Thirty-one of those talks focused directly on workforce planning. The speakers were not making predictions. They were reporting what had already happened. The companies winning in the AI era made one clear choice. They built the foundation right before deploying anything. Their approach is not secret or complicated.
Multiple Transform sessions used the same metaphor: AI needs roads. Not just technology. Data pathways that are clean, connected, and consistent. The organizations posting 34% performance lifts built those roads first. When they deployed AI, it had somewhere useful to go.
"AI is only as good as what it's built on. And that's what people call context in AI, right? So that's going to be your data and how the data is interconnected and speaking the same language and making sense for the AI to interpret it."
— Arnaud Grunwald, "The CHRO's Blueprint for Connected Talent Systems in the AI Era"
"AI has to have roads. It has to have a connection to get the job done."
— Stacey Harris, "The CHRO's Blueprint for Connected Talent Systems in the AI Era"
In practice, this meant consolidating around two to three core systems, what they called a "platform cluster." Every vendor in the tech stack had to integrate in both directions. One-way data feeds did not qualify. Skills data, performance data, and recruiting data needed shared definitions. They had to flow both ways. Organizations that achieved this did not just improve AI outcomes. They also gave their leadership teams the visibility needed to make faster, better decisions.
"Visibility is the prerequisite for outcomes."
— Stacey Harris, "The CHRO's Blueprint for Connected Talent Systems in the AI Era"
Sequencing matters. Transform research was direct about what happens when you reverse the order. Organizations that deployed AI on top of broken HR processes got measurably worse results. AI is an amplifier. It makes what is already there bigger. Organizations with clean data foundations gave AI something worth amplifying.
Successful organizations shared a second trait. They were problem-first. They named the specific business outcomes they wanted to change. Then they worked backward to the tools. That discipline is what separates strategic AI deployment from buying tools under pressure.
"More often than not, big enterprise applications are being deployed because someone senior has said, you need to use AI. You've got a board or a CEO or someone that said, you need to use AI. And so you end up having a technology looking for a problem to solve as opposed to someone who is a business leader saying, okay, I can solve this problem."
— David ibnAle, "The Next Big Bet: VCs on Emerging Workforce Technologies"
The VC panel was honest about why this pattern keeps happening. Executive pressure flows through procurement. It lands on HR teams that never got room to define the actual problem. Organizations that avoided this trap built space between "we need AI" and "here is what we are deploying and why." Even a few weeks of that space is where real strategy gets made.
The prescription is simple. Start with a blank slate. Define the outcome you want. Work backward to the tool. Every organization sharing case studies at Transform had done exactly this.
Deploying AI because a senior leader mandates it creates "technology looking for a problem to solve." The same pattern plays out in global hiring. Organizations that enter new markets without a clear reason spend years and significant money correcting course. Setting the purpose before deployment is the variable that separates the 34% performers from the rest.
Workforce planning now means managing talent across borders. Some of the strongest sessions at Transform came from organizations that had figured out how to do global expansion well. The consistent lesson: treat international growth as a design problem. The decisions made before the first hire shape outcomes for years.
"Global hiring can start with a really exciting idea. And we're like, oh, it's going to be so fun. We're going to grow. We're going to expand in new countries. It's going to be so cool, new markets and new customers. We're going to take our culture and go worldwide. It's going to be amazing. And then reality sets in, and it's really, really hard."
— Jenny Dearborn, "Growing Beyond Borders: Tactical Approaches to Faster Growth Through Global Hiring"
Successful organizations planned for the difficulty instead of being surprised by it. They got clear on the strategic rationale before opening any entity: market access, talent pool, cost structure. That answer shaped every decision downstream, including legal structure, compensation philosophy, how equity would be explained across geographies, and what culture integration would require.
One session made the stakes vivid. A company expanded to the US and gave American employees equity with strong upside. Employees in Finland had chosen a different structure. They had not been fully informed about the difference in value. When the company went public and US employees became millionaires, the Finnish employees were blindsided. The lesson was not about equity preferences. It was about the need to design compensation and culture as if every policy will be compared across every country. Because it will be.
Organizations that treat global expansion as a long game build lasting competitive advantage through their talent footprint. The ambition is worth it. The planning is what makes it survivable.
"You have to play the long game. You have to understand when you're saying to a country, we will come in and employ 600 people in this rural place... and then you pull that away, there are repercussions at a government level that are above your CEO and your board of directors that heads of state start calling other heads of state."
— Jenny Dearborn, "Growing Beyond Borders: Tactical Approaches to Faster Growth Through Global Hiring"
Top-performing organizations shared one more pattern. They treated culture design as a core workforce planning activity. This showed up most clearly in how they approached new offices, distributed teams, and international locations.
"If you don't design ahead of time the planful way to how it is you're going to create that meaning, purpose, culture, et cetera, in these parts of your organization, they will be created for you. And once they're created for you, they're more difficult to reverse, and it may not actually be aligned with what the greater firm's ambitions are."
— Linda Ho, "Growing Beyond Borders: Tactical Approaches to Faster Growth Through Global Hiring"
The framework is direct: Define, Drive, Develop. Articulate what the culture will be. Build systems to reinforce it. Create space for people to live it. Organizations that did this before headcount hit critical mass found culture scaled with them. Those that skipped it paid for fixes years later.
Skills matrices and headcount models matter. But the design of the human experience also matters. What does it feel like to work here? What does meaning look like in this role? Those questions determine whether talent stays and contributes at the level that drives 34% performance gains.
The strongest organizations had moved past the "AI vs. jobs" debate. They were operating a "human plus AI" model. That model was grounded in an honest read of what AI can and cannot do.
"No one really knows the full value of what AI is going to do to our work. I think we're all experimenting."
— Somrat Niyogi, "The Next Big Bet: VCs on Emerging Workforce Technologies"
Acknowledging uncertainty while building clear adoption pathways was a common trait among organizations reporting positive results. They did not wait for certainty. They gave employees a clear route into the technology. That turned anxiety into competence.
"The AI is not supervising you. You're supervising the AI. It's got to be a meaningful collaborative partnership. You have to engage with the technical intelligence as a thinking partner because it cannot replace your thinking."
— Lorelei Carobolante, "ISO International Standards: How HR Leaders Shape the Human + AI Future of Work"
The data and the speakers pointed to the same conclusion. Employees best positioned for an AI-augmented environment are the ones whose organizations gave them structured access to the tools. Those organizations also gave employees a mandate to help redesign the work. The people closest to the work are often the most creative about reimagining it.
"I think it's actually people who are doing work that often think of the ways to best reimagine their own work. And so to the degree you are managers of people who do that, I'd listen to them."
— David ibnAle, "The Next Big Bet: VCs on Emerging Workforce Technologies"
Organizations that created formal channels for frontline employees to propose how their roles should evolve reported two results. They surfaced ideas no consultant would have found. They also turned employee anxiety into ownership. When people help design the change, they stop feeling like it is happening to them. At scale, that shift is a competitive advantage.