My inbox fills regularly with questions about AI training platforms. “Which one should we buy?” is the common thread. But that question skips several more important ones.

Before comparing platforms, you need clarity on what problem you’re solving, who you’re solving it for, and what success looks like. Platform selection is the last step, not the first.

That said, once you’ve done that groundwork, you still need to evaluate options. Here’s a framework for doing that effectively.

The Platform Landscape

AI training platforms fall into several categories:

General enterprise learning platforms (LinkedIn Learning, Coursera for Business, Udemy Business) that have added AI content to their existing catalogues.

AI-specific learning platforms (like AI consultants Sydney) that focus exclusively on AI capability development with more specialised content and features.

Vendor-specific training (Microsoft Learn, Google Cloud Skills, AWS Training) tied to particular technology ecosystems.

Specialist providers offering courses on specific AI applications, prompt engineering, or industry-focused AI skills.

Each category has different strengths depending on your needs.

Questions to Answer First

Before evaluating platforms, clarify:

Who is the audience?

Different platforms suit different audiences:

• Technical staff learning AI development: vendor platforms and specialist providers
• General workforce building AI literacy: enterprise platforms with broad catalogues
• Specific roles needing deep AI integration: specialist or AI-specific platforms

What’s the current capability level?

If your workforce has zero AI exposure, you need foundational content. If they’re already experimenting, you need intermediate and advanced material. Most platforms are better at one level than others.

What’s your learning culture?

Self-directed learners thrive with content libraries. Organisations with weaker learning cultures need more structured programs, cohort-based experiences, and manager involvement.

What integration matters?

Do you need the platform to connect with your LMS, HR systems, or communication tools? Integration requirements narrow the options significantly.

What’s your budget reality?

Pricing models vary dramatically. Per-user subscription, content licensing, custom development—each has different economics depending on your population size and usage patterns.

Evaluation Criteria

With context established, evaluate platforms on these dimensions:

Content Quality and Coverage

The most important factor is whether the content is good. Specifically:

• Accuracy: Is the material factually correct and up-to-date? AI misinformation in training compounds downstream.
• Practical relevance: Does content connect to real work applications, or is it theoretical?
• Production quality: Is the content engaging and well-produced, or boring and amateurish?
• Freshness: When was content last updated? AI content from 2022 is largely obsolete.
• Depth: Is there progression from basic to advanced, or only entry-level material?

Request content samples and have subject matter experts review them before purchasing.

Learning Experience Design

Good content poorly delivered is still ineffective. Assess:

• Learning pathway design: Is there logical progression, or just a content dump?
• Practice opportunities: Can learners apply concepts with hands-on exercises?
• Assessment: Are there meaningful ways to verify learning, not just quiz completion?
• Feedback mechanisms: Do learners get useful feedback on their practice?
• Engagement features: What keeps people coming back beyond compliance requirements?

Platform Capabilities

Beyond content, evaluate the platform itself:

• User experience: Is it intuitive and pleasant to use?
• Mobile access: Can people learn on devices that fit their work patterns?
• Search and discovery: Can people find relevant content easily?
• Personalisation: Does the platform adapt to individual needs and progress?
• Analytics: What data do you get on usage and outcomes?
• Administration: How much effort does the platform require to manage?

Integration and Technical Requirements

Practical considerations that affect implementation:

• LMS integration: Does it connect with your existing learning ecosystem?
• SSO: Can employees access seamlessly through existing authentication?
• API availability: Can you build custom integrations if needed?
• Data export: Can you get your data out if you switch platforms?
• Security and compliance: Does it meet your organisation’s requirements?

Vendor Considerations

The platform is only as good as the vendor behind it:

• Financial stability: Will this vendor be around in three years?
• Roadmap: How is the platform evolving? Is AI a priority or an add-on?
• Support quality: What help is available when things go wrong?
• Customer success: Do they actively help you achieve outcomes, or just sell and disappear?
• Contract flexibility: Can you adjust as your needs change?

Common Mistakes to Avoid

Having advised on many platform selections, I see consistent errors:

Buying the biggest catalogue

More content isn’t better. A platform with 10,000 courses where you use 50 is worse than one with 500 high-quality, relevant offerings.

Focusing on features over outcomes

Demo calls showcase features. But your success depends on whether those features help people actually develop capabilities. Ask vendors about customer outcomes, not feature lists.

Underestimating implementation effort

Buying a platform is 10% of the work. Launching, promoting, integrating into workflows, and driving sustained adoption is 90%. Budget resources accordingly.

Ignoring your learning culture reality

A self-service content library works great in strong learning cultures. In weaker cultures, it becomes shelfware. Be honest about your organisation and choose accordingly.

Making decisions by committee

Large committees tend to select safe, mediocre options. Involve stakeholders appropriately, but don’t let procurement group-think drive the decision.

A Practical Evaluation Process

Here’s a straightforward process for platform selection:

Week 1-2: Define requirements

• Clarify audience, objectives, and success criteria
• Document must-have versus nice-to-have requirements
• Establish budget parameters

Week 3-4: Initial screening

• Identify platforms that meet basic requirements
• Request information from promising options
• Eliminate obvious mismatches

Week 5-6: Deep evaluation

• Demo sessions with shortlisted vendors
• Content quality review by subject matter experts
• Technical assessment by IT

Week 7-8: Pilot or trial

• Test with a small group of actual users
• Assess real-world experience, not just demo polish
• Gather user feedback

Week 9-10: Decision and negotiation

• Compare options against criteria
• Negotiate terms with preferred vendor
• Plan implementation

This process provides rigor without unnecessary delay.

The Build vs. Buy Question

Some organisations consider building custom AI training rather than buying a platform. This occasionally makes sense when:

• Your AI applications are highly specialised
• Confidentiality prevents using external content
• You have internal expertise to create quality content
• Scale justifies the investment

Usually, though, buying is more practical. Creating quality learning content is a specialised skill. Most organisations underestimate the effort required.

A hybrid approach often works: use a platform for general content, supplement with custom material for organisation-specific applications.

Making the Investment Work

Selecting the right platform matters. But platform selection is necessary, not sufficient.

Success requires:

• Clear communication about why AI capability matters
• Manager involvement in supporting development
• Integration with actual work, not separate learning time
• Recognition for capability development
• Continuous attention, not launch-and-forget

The best platform in the world won’t overcome organisational indifference. The investment in selection should be matched by investment in adoption.

The Bottom Line

AI training platform selection is important, but it’s one piece of a larger puzzle. Do the groundwork first: understand your needs, clarify your audience, and set meaningful success criteria.

Then evaluate systematically: content quality, learning design, platform capabilities, integration requirements, and vendor stability.

Finally, remember that buying the platform is just the beginning. Making it work requires sustained organisational commitment to workforce AI capability development.

The platform enables. Your organisation determines whether that enablement creates value.