Before Your District Adopts Another AI Tool, Read This

Most districts are somewhere on the same spectrum right now: either moving too fast without guardrails, or moving too slow while the window closes. According to Attorney Dondi West, both are equally dangerous.

West is a cybersecurity attorney, former Navy cryptology officer, and former legal counsel at Microsoft and TikTok. He now leads the cybersecurity law practice at a global pharmaceutical company, where AI is central to how drugs and treatments are developed. He's also one of the clearest thinkers on what responsible AI adoption actually requires — and on the Champion Every Voice podcast, he made a case that every district technology director needs to hear.

AI literacy is no longer optional infrastructure

West's opening argument is worth sitting with: "AI and digital literacy are not electives. They are the new reading, writing, and arithmetic."

That framing has immediate implications for how districts think about technology budgets, professional development, and staffing. If AI literacy is foundational — on par with reading and math — then treating it as a supplemental initiative or a single teacher's side project is a structural mismatch.

What makes this moment particularly complex for school systems is that teachers and students are on the same learning curve at the same time. There's no established cohort of AI-competent educators to train the next wave. Districts are, as West put it, "building the airplane while flying it." That's not a reason to slow down. It's a reason to build deliberately.

West's recommendation for district leadership: consider creating a Chief AI Officer role at the district level, and an embedded AI-focused administrator at each school — not a teacher who champions AI on top of their existing load, but someone with a formal mandate to drive adoption, support upskilling, and ensure the implementation keeps pace with how fast the technology is actually moving.

The digital divide gets worse if districts hesitate

West tracks what he calls the digital and algorithmic divide — the gap between students who have access to AI tools and those who don't. In Title I schools, where students may lack internet access or devices at home, that gap is already significant.

His argument is that AI has the potential to be the great equalizer, but only if school systems lean in the right direction. "If we fail to lean in the right way, it's going to increase that digital divide exponentially." Students who graduate without AI fluency will face a different set of career paths and life outcomes than those who don't — and that divergence will map, predictably, onto existing inequities.

For CTOs and tech directors in Title I districts specifically, this reframes the adoption conversation. The question isn't whether your district can afford to implement AI tools for education. Given the cost of inaction, the question is whether you can afford not to.

What "looking under the hood" actually means when evaluating vendors

West is direct about what districts should be asking AI vendors — and clear that these don't have to be technical conversations.

The essential questions are human-centered and non-negotiable: Do you collect student data? Do you use that data to train your models? What data is stored, where, and who has access to it? These aren't questions for your legal team to ask in isolation. They're questions every district leader should be comfortable raising in a procurement meeting.

West also flagged algorithmic bias as an underexamined risk. AI systems are only as good as the data used to train them, and implicit biases can end up embedded invisibly in how a system interacts with students — across every session, at scale, without anyone noticing. For districts serving diverse student populations, this isn't a theoretical concern. It's a due diligence requirement.

On vendor accountability specifically: districts should be looking for transparency as a baseline, not a differentiator. If a vendor can't clearly explain where student data goes, how their models are built, and what happens if the tool doesn't produce results — that's an answer. Outcomes-based contracting, where payment is tied to demonstrated student outcomes rather than just access to the platform, is one mechanism for holding vendors to that standard.

Shadow AI is already happening in your district

One of the most practical points West raised is one that rarely shows up in governance conversations: if teachers don't have access to approved AI tools that actually reduce their workload, they'll find their own.

West calls this shadow AI — teachers using personal accounts to do things like grade entry, lesson differentiation, or student data analysis, often pasting sensitive information into tools that sit entirely outside the district's security boundary. It's not bad intent. It's a rational response to an unmet need.

The governance implication is clear: restrictive AI policies that don't address what teachers actually need don't eliminate risk. They just move it outside the district's visibility. A technology policy that includes approved tools, clear use parameters, and genuine support for teacher upskilling is a better security posture than a blanket prohibition.

Fast and safe are not opposing goals

West's most useful reframe for district leaders who feel caught between innovation and responsibility is this: reject the false choice.

"The school districts that move fast with strong governance will outperform the ones that either move recklessly or don't move at all." His analogy is a fast car with good brakes — the brakes aren't there to prevent speed, they're what makes speed viable. A district with a clear AI vision, vetted tools, trained teachers, and accountability mechanisms can move quickly. A district that's either ignoring governance or using governance as a reason to stall is in the same place.

The governance model has to include speed as a design requirement, not an afterthought. And because agentic AI is moving fast enough that West's own legal guidance changes month to month, any framework districts build now needs to be fluid enough to adjust — not a static policy document, but a living process with someone accountable for keeping it current.

What to actually do with this

For tech directors preparing for board conversations, vendor evaluations, or district AI policy development, West's framework distills to a few concrete pressure tests:

Does your district have a named owner for AI adoption at the leadership level — not a committee, a person? Do your vendor contracts include data transparency requirements and outcome accountability, or just access terms? Does your acceptable use policy address shadow AI by providing teachers with approved alternatives? And is your governance model designed to be updated in six months, or will it be obsolete before implementation is complete?

Agentic AI in education is not a future concern. It's a current procurement and policy decision. The districts that get this right won't just be safer — they'll be the ones whose students are prepared for what comes next.

🎧 Listen to the full conversation with Attorney Dondi West on the Champion Every Voice podcast. https://rss.com/podcasts/champion-every-voice/

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