It’s Not Just IT Anymore: Where the AI Buyer Lives Across the Org Chart
AI first entered business teams and business processes as an experiment. It was a futuristic tool reserved for technical teams, innovation leads, or R&D labs. Fast-forward a decade, and that narrative’s toast.
AI is now a competitive differentiator. What started as a playground for early adopters has become a strategic focus across every department. From marketing and operations to finance and HR, today’s AI buyer could be anyone, regardless of title, function, or tech fluency.
The new face of AI buying
It’s time to bust the myth that AI buyers all live in IT. Yes, IT still holds a big share, 32% of AI buying happens within tech departments. But here’s what’s more important: 68% of AI buyers don’t work in IT at all.
Our research shows strong representation from operations (13%), finance (12%), procurement (11%), and HR (7%). Even sales and marketing, traditionally the last to adopt back-end tech, are stepping up—driven by a need to automate outreach, qualify leads faster, and scale content creation.
In other words, AI has gone cross-functional. No one department owns it anymore. AI buyers now emerge wherever a team needs to move faster, do more with less, or solve a workflow bottleneck. And that changes everything for how AI vendors need to market, sell, and educate.
The rise of the researcher class
Here’s another important shift: decision-makers aren’t doing all the heavy lifting.
Our global survey found that 48% of AI research is conducted by staff-level employees, long before the final buyer signs a contract. These researchers are on the front lines—reading case studies, testing tools, and building the internal case for AI investment.
That means your message needs to hit two levels:
- The user-researcher, who’s looking for credibility, clarity, and real-world application
- The budget holder, who cares about ROI, efficiency, and organizational fit
Neglect either audience, and your pipeline suffers.
Gender dynamics: Who’s researching AI
Digitalzone proprietary intent data surfaced something interesting: 51% of AI researchers are women, even though the majority of B2B purchase decision-makers (67%) are men.
This suggests a growing gender gap between who’s doing the research and who’s making the final call. For go-to-market teams, that means you can’t rely on traditional people.
If your messaging speaks only to senior male decision-makers, you’re likely missing half your actual audience.
AI buying today isn’t about features—it’s about outcomes. The most effective AI solutions don’t just improve a task. They reshape entire workflows.
Take Dice, for example. Their marketing team expanded from 25 to 45 people by embedding AI teammates into everyday processes, automating content generation, campaign analysis, and lead routing. The result? 50–75% faster output, improved accuracy, and more time for strategic work.
Or look at Cin7. Their sales, marketing, as well as customer success teams now use AI to create a seamless loop of insights and engagement, from demo requests to onboarding. AI connects the dots between departments—no handoffs, no lag.
This is the new standard. Buyers want connected workflows, not isolated tools. And they’re evaluating vendors accordingly.
Departmental priorities: What each AI buyer really cares about
When organizations consider implementing AI, the conversation quickly shifts from what the technology can do to what problems it can solve — and for whom. Different departments within a company approach AI with distinct expectations, shaped by their roles, responsibilities, and day-to-day pressures. Understanding those nuances is essential to delivering solutions that resonate.
IT
For IT leaders, integration is often the first hurdle. New technologies must work seamlessly with existing infrastructure, without compromising system performance. Data security remains paramount, especially when sensitive information is in play. Additionally, there is growing demand for model transparency; decision-making processes need to be explainable, not opaque. Compatibility and maintainability aren’t just preferences; they’re requirements.
Marketing
In marketing departments, urgency and scale are constant themes. Marketers want to launch campaigns faster, scale content without bottlenecks, and tailor messages to increasingly specific audiences. If your AI helps them move quickly while staying relevant, you’ll have their attention.
Finance
Accuracy and accountability rule this space. Finance leaders are looking for better forecasting, more transparent audit trails, and ways to keep costs under control. Anything that helps them see around corners and stay compliant with fewer surprises is a win.
Operations
Operations teams thrive on efficiency. They’re focused on automating routine workflows, gaining real-time visibility across tools and teams, and minimizing downtime. If your solution improves day-to-day performance and helps avoid disruptions, it’s likely to land well.
Procurement
Here, it’s all about reducing risk. Procurement teams want to ensure compliance, clearly classify and manage vendors, and minimize exposure to supply chain issues. A tool that simplifies oversight and flags potential red flags early is a strong value add.
Human Resources (HR)
HR buyers are balancing fairness, speed, and experience. They want to reduce bias in hiring, move candidates through the process quickly, and create a smoother, more engaging experience for applicants. If your AI can help do all three, you’re speaking their language.
Each buyer brings a different lens, but all of them want proof that AI will improve their work without creating more friction.
Roadmap to Winning the Modern AI Buyer
| Stage | What the Buyer Cares About | Tactical Moves |
| Awareness & Research | – Clarity over complexity – Relevance to their function | – Role-specific content – Case study libraries |
| Internal Alignment & Buy-in | – ROI justification – Workflow impact | – Shareable 1-pagers – Internal business case templates |
| Evaluation & Comparison | – Integration, security, usability – Real-world proof | – Customer references – Department-specific demos |
| Decision & Procurement | – Risk mitigation – Vendor credibility | – Procurement guides – Pilot program outlines |
| Post-Sale Adoption | – Speed to value – Low learning curve | – Training hubs – Role-based onboarding workflows |
| Expansion & Advocacy | – Sustained performance – Internal visibility | – Quarterly reviews – Workflow-based outcome reports |
To stay relevant in today’s AI landscape, go-to-market teams need to shift their approach:
- Target function, not just title: Focus on solving department-specific problems, even if the buyer isn’t “technical.”
- Educate the researcher: Build content that equips staff-level champions to sell the solution internally.
- Demonstrate outcomes: Don’t sell models or algorithms. Sell faster onboarding, smarter decisions, and better ROI.
- Tailor to buyer intent: Use intent data to customize outreach based on buyer behavior, not assumptions.
The bottom line? The AI buyer is no longer a single person in IT. They’re a cross-functional team, driven by performance goals, not platform specs.
