AI Rec 6 Resource Allocation Plans

States should develop detailed resource allocation plans for AI implementation in schools, school districts and institutions of postsecondary education to ensure that the implementation of AI is successful, sustainable and available to all students.

These plans should inform state fiscal notes related to education and AI.

It is hard to imagine that integrating AI technology into education across districts and institutions will not require some state investment, considering local capacity issues and limited economies. If past educational technology efforts are any example, state funding for AI in education will not be cheap nor a one-time expense. 

The Commission strongly recommends that states develop resource allocation plans for AI to ensure that the implementation of AI in schools and postsecondary institutions is successful, sustainable and available to all students. 

States with detailed resource allocation plans will have the financial foresight required to implement AI in education and advocate for additional funding from the federal government or other sources. 

An Important Tool for Wise Spending, Planning, Transparency

Resource allocation plans are a critical tool to understand the financial resources to cover initial setup, training, hardware, software licenses infrastructure upgrades and ongoing operational expenses. 

Well-developed resource allocation plans should help states better predict and mitigate potential cost overruns and spend state funds wisely. They can help states to identify opportunities to optimize spending, such as more cost-effective AI solutions, less reliance on expensive hardware, or streamlined training programs. This can help states better prioritize funding for critical areas such as infrastructure and training and identify potential cost savings.

States could also use resource allocation plans to build multi-year projections for components such as maintenance, software updates and scaling costs, forecasting how costs may evolve over time with inflation, increased usage, and technology upgrades. Multi-year projections can help states sustain AI programs financially over the long haul. 

Resource allocation plans can promote transparency by providing the public with blueprints for how a state is responsibly managing its finances and providing value to taxpayers. 

Clear, detailed resource allocation plans should serve as the foundation for any fiscal notes related to potential state-level AI investments until newer data is available.

References

Allen, S., & Seaman, J. (2018). AI in education: Opportunities, challenges, and implications for policy and practice. Center for Digital Education.

Bughin, J., Hazan, E., Ramaswamy, S., Chui, M., Allas, T., Dahlström, P., Henke, N., & Trench, M. (2017). Artificial intelligence: The next digital frontier? McKinsey Global Institute.

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson Education.

Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1–13. https://doi.org/10.1186/s41039-017-0062-8

Saldaña, J., Pérez, P., & Gutiérrez, R. (2018). Cost estimation for AI projects in educational settings. Journal of Educational Technology, 5(2), 12–22.

UNESCO. (2021). AI in education: Challenges and opportunities for sustainable development. UNESCO Publishing.