Vendor Acquisition

Vendor Acquisition

Districts exploring AI for instruction, operations, and student support must adopt thoughtful vendor acquisition protocols. Unvetted tools can risk our scholars data privacy, misalignment with learning goals, and wasted resources. Effective acquisition balances innovation with responsibility.

Key Considerations:

• Comply with FERPA, COPPA, and state data laws.
• Evaluate instructional alignment and equity impact.
• Require transparency and explainability from vendors.
• Ensure human oversight in AI-supported decisions.
• Assess contract clarity, sustainability, and renewal terms.
• Require vendor training and support for staff.
• Use cross-functional evaluation teams (legal, IT, instructional).
• Maintain a public list of approved AI tools.
• Reassess AI tools annually for safety and effectiveness.

Pros:

• Reduces educator workload and administrative tasks.
• Enables adaptive, personalized learning.
• Expands tutoring and translation access.
• Improves data-driven decision-making.
• Demonstrates district innovation.

Cons:

• Privacy and ethics compliance risks.
• Opaque “black box” AI models.
• Possible algorithmic bias.
• Cost and scalability challenges.
• Resistance from untrained stakeholders.