Key Takeaways
- Learning technology purchases are now enterprise decisions. IT, finance, procurement, legal and compliance teams are increasingly involved because learning platforms affect security, data, budgets and governance.
- AI has expanded the risk and oversight involved in learning technology. AI-enabled platforms can raise new questions about integrations, employee data, content accuracy, security and pricing.
- More stakeholders do not necessarily mean less trust in L&D. Cross-functional involvement can reflect the growing strategic importance of learning technology rather than a loss of L&D influence.
A learning platform purchase used to be a learning and development (L&D) decision with an IT sign-off at the end. Most organizations are still running the decision as if learning technology is only an L&D system. But new research from Go1 shows how much that’s changed. Across IT, finance and procurement, and legal and compliance, 85% of leaders say they’re more involved in learning technology decisions than they were two to three years ago, and 27% say they’re more involved than they’d prefer. If you lead an L&D team, you’ve watched this happen one added approval at a time.
The bigger committee is now permanent, because learning technology has crossed the line from departmental software to enterprise infrastructure, and decisions about enterprise infrastructure follow different rules.
AI Turned Learning Platforms Into Enterprise Infrastructure
Artificial intelligence (AI) did not create every new requirement, but it made the enterprise implications impossible to ignore. A platform that connects to human resources (HR) and communication systems raises security and integration questions, and IT is responsible for those. A platform with per-seat AI pricing adds cost to a category finance is already trying to shrink, since 79% of finance leaders report duplicate or redundant learning technology. A platform that generates content and recommendations raises questions about data handling and accuracy, and legal and compliance are responsible for those. That is the practical reality of AI transformation, with learning platforms now touching systems, risks, budgets and decisions that sit well beyond L&D.
None of those teams wants to run learning, but they want to know the systems delivering it meet the same bar as everything else in the enterprise stack.
Reluctant Participants Are Still Participants
Leading L&D is really hard at the moment. Budgets are tighter, expectations are higher and small teams are being asked to support workforces of thousands. So when three more functions show up with new requirements, the temptation is to read it as encroachment or as a sign the function has lost standing.
However, the same research found trust in L&D has risen over the same period, with 77% of IT leaders, 64% of finance leaders and 52% of legal and compliance leaders reporting greater confidence in the function than two to three years ago. Cross-functional involvement reflects how much the decision now matters, and the 27% who’d rather be less involved are responsible for governance work they never asked for. Give them a process they can trust and a skeptic becomes a sponsor.
The Committee Can Speed Decisions Up Instead of Stalling Them
Rather than presenting a chosen platform and absorbing objections through review cycles, bringing the committee in before the technology shortlist exists. That means gathering security, data and cost requirements prior to evaluating a single vendor. Late-arriving requirements are where learning technology purchases often go to die. Requirements gathered up front become selection criteria rather than roadblocks.
In practice, that means a short requirements meeting with each function before any vendor research starts.
- Ask IT which security certifications are mandatory, which systems a platform has to connect to and what its own review of a new vendor will cover.
- Ask finance what the budget ceiling is, which existing tools have overlapping features and what evidence of usage it will want to see after a year.
- Ask legal where employee data can be stored, what its review of AI features requires and who has to approve new data flows.
Write the answers down as pass-or-fail criteria. A vendor that fails a mandatory requirement never reaches the shortlist, and the functions that set the criteria have already agreed to approve whatever passes them.
Translating learning outcomes into each function’s language is harder because each team evaluates the same platform through a different lens. The requirements meetings teach you the vocabulary. An L&D leader who can present a platform in terms of security posture, cost-per-outcome and data handling will move a decision through the committee faster than one who only speaks in learning outcomes.
The Second Decision Tells You if It’s Working
A useful test of whether the committee is working is the speed of the second purchase. The first cross-functional decision is slow pretty much everywhere because the organization is negotiating its rules while trying to apply them. When the framework is finalized, the second decision moves faster, and each one after that gets easier.
Measure two things on that second purchase: Track the weeks from identified need to signed contract, and track how many review rounds each function needed along the way.
Both numbers should drop, because requirements get confirmed instead of discovered. Then watch for two more signals. Requirements should not change once an evaluation starts since mid-process additions mean the upfront meetings missed something. When the timeline shrinks, the requirements work and nobody relitigates the outcome, you know the committee is working.
