Preparing for AI vendor reviews: What decision-makers need to know

Why vendor evaluation now defines AI success

AI adoption is no longer an innovation project. It is now central to strategic planning, cost management, and operational efficiency. Yet as more organisations accelerate AI investment, one barrier remains consistent: evaluating and selecting the right vendor.

This is where the Planning ICT Initiatives for Sustainable Growth microcredential from SkillX becomes critical. It helps leaders connect technology choices to organisational direction and build structured processes for AI vendor due diligence before procurement begins.

Many decisions still hinge on marketing claims rather than measurable capability. Procurement and executive teams face mounting pressure to move fast while maintaining due diligence. The result is AI implementations that miss strategic alignment or fail under real-world conditions.

SkillX has seen this tension play out across multiple sectors, where clearer evaluation frameworks and leadership capability have become essential to sustainable AI adoption.

The problem with today's AI vendor market and due diligence

The AI market has expanded faster than most governance frameworks. Vendors often present capability in broad terms, leaving executives to interpret what "AI-powered" actually means and how to conduct proper AI vendor due diligence.

In many cases, the term “AI-powered” refers to systems that use automation or rule-based logic rather than true machine learning. Automation tools follow pre-set instructions, while machine learning systems can recognise patterns, adapt, and improve from data over time. Understanding this distinction is crucial for decision-makers, as it helps separate marketing claims from real capability when reviewing proposals or technology options.

Recent findings from the Australian Computer Society (ACS), Australia's national professional body for ICT practitioners, highlight that executive-level digital fluency and strategic ICT alignment are among the top capability gaps identified in its 2024 Digital Pulse report. The ACS calls for stronger leadership capacity in technology oversight, linking directly to how AI procurement decisions are made.

The World Economic Forum (WEF), a global organisation that brings together business, government and academia to shape technology and economic agendas, notes that more than 60 percent of organisations globally underestimate AI risk when assessing vendors. The report stresses the need for cross-functional decision-making and ethical evaluation frameworks before adoption.

Meanwhile, Australia's Office of the Australian Information Commissioner (OAIC), the federal regulator for privacy and information rights, has issued updated guidance reminding organisations that AI vendors must meet Privacy Act 1988 obligations when using or training models with personal data. The guidance emphasises that compliance reviews should form part of every AI procurement process. In practice, this means confirming how each vendor collects, stores, and uses personal data before signing any agreement or allowing system access.

The real risks behind AI vendor selection

Behind the marketing claims, most AI procurement failures stem from three recurring weaknesses. These risks can undermine even well-funded projects if left untested during the vendor review phase.

1. Undefined capability

Many products use process automation or pre-set algorithms yet are marketed as full AI systems. Without validation, organisations risk paying for limited functionality that delivers minimal strategic value.

2. Opaque data dependencies

Some vendors require access to client data or system logs to train or fine-tune their models. Without clear data-handling controls, this can breach privacy laws or internal governance policies. The OAIC advises that all AI data transfers should be assessed for compliance and traceability.

3. Low integration maturity

A technically strong AI tool can still fail if it does not integrate with existing ICT systems. Weak interoperability often results in data silos, manual workarounds, and increased operating costs.

To manage these risks, procurement teams should request:

• Technical architecture documentation showing integration pathways.
• Independent security assessments for data handling and model transparency.
• Service-level commitments tied to measurable outcomes, not just uptime guarantees.

The real challenge is identifying vendors whose solutions genuinely strengthen operations and governance.

Building a structured AI vendor review framework

Effective vendor assessment now requires the same structure as any major capital procurement process. The review framework should include four essential domains.

1. Strategic alignment Does the vendor's AI solution support your organisation's business and ICT strategies? This step ensures each proposed technology contributes directly to enterprise outcomes rather than isolated innovation.

2. Capability evidence Ask for verifiable performance data, customer references, or benchmark results. Avoid adopting tools that cannot demonstrate measurable ROI or clear efficiency gains.

3. Governance and compliance Evaluate the vendor's privacy, data sovereignty, and ethical frameworks. Incorporate principles from the privacy guidance and AI ethics principles into your review checklist.

4. Workforce readiness Successful AI adoption depends on people as much as technology. Vendors should provide structured onboarding and support. Parallel internal upskilling, through programs like SkillX, ensures your team can assess, implement, and manage solutions effectively.

At a glance: Your AI vendor review checklist

Use this summary to guide your next procurement or vendor evaluation process.

• Strategic clarity - Confirm the AI proposal aligns with your business goals and ICT strategy.
• Evidence of performance - Request case studies or data showing proven results.
• Data integrity - Review how the vendor handles, stores, and protects sensitive data.
• Compliance readiness - Check privacy, security, and ethical standards against your organisation's obligations.
• Integration fit - Ensure the solution complements existing systems with minimal disruption.
• Support and training - Assess the vendor's capability to help your workforce adapt and operate the solution effectively.
• Long-term viability - Evaluate the vendor's financial stability, product roadmap, and service reliability.

From capability audit to commercial clarity

Procurement leaders should approach vendor selection through a capability audit that maps vendor strengths against organisational requirements, maturity, and existing ICT capacity.

Practical example: A national healthcare provider recently assessed two AI vendors offering predictive analytics for patient scheduling.

• Vendor A demonstrated impressive functionality but required full access to patient data stored across multiple systems.
• Vendor B offered a federated model that processed anonymised data within the client's environment.

Although Vendor A's interface appeared more advanced, the provider's review framework, developed using ACS and OAIC principles, flagged governance and privacy concerns as critical risks. Vendor B was selected due to stronger data controls, lower compliance risk, and better long-term interoperability. That decision reduced integration time by 30% and met board-level governance expectations without compromising analytical performance.

This type of structured comparison, based on capability, compliance, and alignment, illustrates how AI vendor reviews can produce measurable business value.

Ask direct, measurable questions such as:

• How transparent is the vendor's AI decision-making process?
• What dependencies exist between their system and our existing architecture?
• What is the total cost of ownership, including integration, training, and maintenance?
• How does the vendor manage data bias, privacy, and ethical use?

Why executives must lead the vendor review

AI procurement decisions shape future capability, not just IT expenditure. Senior leaders, including CEOs, COOs, and CIOs, must take responsibility for defining vendor criteria linked to strategic outcomes.

Delegating technical assessment to IT alone misses the broader commercial, compliance, and workforce dimensions. The most effective organisations embed AI readiness within their enterprise planning, not just their technology teams.

How SkillX helps align AI procurement with strategy

SkillX equips leaders with the tools to evaluate and plan technology investments that drive sustainable growth. The Planning ICT Initiatives for Sustainable Growth microcredential supports executives, program managers, and procurement teams to:

• Align ICT investments with enterprise strategy.
• Develop evidence-based vendor evaluation frameworks.
• Integrate governance, risk, and ethics into procurement planning.

Whether your organisation is initiating AI adoption or reviewing current partnerships, developing internal capability is now essential to sustainable digital transformation.

Book a consult with SkillX to align your next AI procurement cycle with your organisation's strategic direction.