What Districts Must Do For GenAI Success

Yet, for every district ready to embrace this new era, there’s another grappling with questions about readiness, risks, and long-term implications. Their questions for the adoption of GenAI usually come in three flavors:

• Will Gen AI create more work for my educators?
• How can we ensure content quality and accessibility for all learners?
• What about data security, compliance, and governance?

Moreover, the openness to GenAI often varies based on where districts find themselves in their digital transformation journeys. Recently, the Council of the Great City Schools (CGCS) and Consortium for School Networking (CoSN) worked in collaboration with Amazon Web Services (AWS) to develop the K12 generative AI Maturity Readiness Assessment checklist. Accordingly, at any given point in time, an organization can be at the emerging, developing, or mature stage.

In the Consortium for School Networking’s State of EdTech District Leadership report, 35% of the US districts agreed to have a Generative AI initiative in place. While forward-thinking districts are mapping out strategies for widespread adoption, others are observing closely, waiting to learn from proven successes.

No matter where your district stands, the ultimate goal remains the same: to improve learning outcomes while upholding the integrity of your educational mission. Unfortunately, for a lot of district leaders, it’s not just about GenAI adoption. They have to deal with multiple pressing concerns.

Tips to Craft a Clear Strategy for Navigating the GenAI Mix

For district leaders trying to navigate the GenAI mix, below are some tips to help you get a foot in the door and approach the process with a clear and strategic plan.

1. Identify the Top 3 Priorities and Work with Market Leaders to Create a Roadmap

While GenAI has a lot of potential, it may sound overwhelming, like, how do you know what’s best for your district? Moreover, educators and community members have different concerns about integrating AI into education.

Teachers may be hesitant due to worries about how AI might affect the learning process, its overall cost, and a potential lack of AI literacy and technical expertise. Meanwhile, students display varying levels of understanding and uncertainty about how to use AI productively. Community members, on the other hand, are concerned about how rapidly evolving technology could impact their workforces and daily lives, as well as those of students.

If there’s one insight that stands out from LAUSD’s AI chatbot failure, it’s this: success with GenAI is not about chasing trends or adopting the latest tools for the sake of innovation. It’s about aligning technology with your district’s unique needs and aspirations. That requires involving all stakeholders, from teachers and IT teams to parents and students in the decision-making process.

As district leaders, you must start by identifying the district’s top 3 priorities and working with market leaders and SMEs to create a roadmap. This roadmap should define the measurable impacts that the integration is expected to bring— whether in terms of identifying the product/market fit for GenAI or addressing the primary pitfalls of poor communication and guidance. Only this way you can satisfy both educators and policymakers.

2. Collaborate with GenAI and Data Management Experts to Establish Comprehensive Policies

When it comes to generative AI even the most seasoned leaders can find themselves in the deep end. In a notable example, recently, a state education commissioner relied on AI-generated citations — unfortunately fabricated to support her stance on restricting cell phones in Alaska schools.  This highlights the growing pains many leaders experience as they navigate the potential and pitfalls of AI in decision-making processes. Without clear guidelines, the risks are significant.

A possible solution could be just as districts bring in curriculum consultants, they can collaborate with generative AI and data management SMEs to craft policies that guide responsible AI use. At the very minimum, these should include:

1. Protocols for handling student data in compliance with federal and local laws.

2. Mandates for educators (superintendents too) to review AI-generated content before classroom use.

3. Prohibitions on inputting student information into public AI models.

4. Training for educators on identifying and mitigating biases in AI outputs.

5. Guidelines for third-party AI tools that respect intellectual property rights.

Then depending on their unique contexts, district leaders can adjust their policies. Each stakeholder must have a clear understanding of the policies and must be regularly updated about relevant changes. The district leaders can also hold annual meetings and training to make sure everyone’s on the same page and ensure anyone new to the district understands their responsibilities.

Additionally, in June 2024, the US Department of Education also issued a series of recommendations for ed-tech developers, vendors, and the school officials who work with them regarding AI. Many state departments have also issued official AI guidance on things like best practices, literacy, and privacy. By keeping track of these, leaders can ensure that the policies align with the state and federal policies as well.

3. Retain a Data Management SME to Evaluate Solutions and Conduct Periodic Audits

For district leaders, the first priority is often ensuring that the technology meets the district’s educational needs.

But the responsibilities do not stop there.

AI technologies are not static. They evolve rapidly. Their impact on education is continuously shaped by both internal factors (such as curriculum changes or new educational goals) and external factors (such as advancements in AI technology or changes in regulatory frameworks). As AI systems process vast amounts of data, it’s essential that they do so in ways that protect student privacy, maintain fairness, and avoid bias. For leaders, the district data used to build the technology must be continuously subjected to privacy and data security regulations. Without regular, thorough audits, districts may unknowingly face risks related to algorithmic bias, data security breaches, or non-compliance with emerging regulations. These risks can compromise both the technology’s integrity and the district’s reputation.

To effectively manage these complexities, it’s crucial for districts to retain a Subject Matter Expert (SME) in data management and AI ethics. An SME offers specialized knowledge that goes beyond the technicalities of AI systems — they understand how these technologies intersect with educational goals, legal frameworks, and community expectations.

They can not only assess whether the technology works but also ensure it works in a way that upholds the district’s values, complies with regulations, and continues to serve the best interests of students and educators.

While it might be tempting to view these evaluations as a task that can be postponed, the truth is that failure to conduct regular audits and assessments can lead to significant long-term challenges.

As GenAI proves to be an integral part of K12 education, it will become crucial for educational districts to deal with it thoughtfully and strategically. However, this doesn’t mean districts should avoid Gen AI altogether. Instead, it emphasizes the importance of finding ways to use AI to support the larger district goals.

To make the most of AI, districts should partner with trusted experts who can provide guidance on all aspects. By working with these partners, districts can navigate AI’s complexities with the right insights and tools and make their initiatives well-grounded in practicality and success.