| | | Hi , here's your monthly Dose of Noetic! |
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| | | AI + Data Privacy: What Higher Ed Leaders Must Know Now
As AI becomes more integrated into marketing workflows, it’s not just your results that are evolving. Your responsibilities are, too. ➡️️
With new interpretations of PIPEDA (Canada), GDPR (Europe), and CCPA (California), higher ed leaders face tougher questions about how AI tools are trained, what student data is being used, and who is ultimately accountable.
Here’s what you should have on your radar this fall:
✅ Consent is Evolving.
Using student or applicant data to train AI models (even anonymized) could require explicit opt-ins. This may mean updating application forms, inquiry flows, or CRM permissions.
Example: If you’re using AI to analyze web sessions and predict prospective student behaviour, ensure your privacy policy communicates this clearly.
Shadow AI is a Real Risk.
Faculty and staff experimenting with tools like ChatGPT, Jasper, or Gemini may unknowingly upload sensitive student or institutional data.
Solution: Provide a clear, internal guide for your teams on what’s safe to share and what’s not.
Privacy Violations Can Tank Trust and Enrolment.
Misuse of AI-trained data can lead to reputational damage, compliance fines, and loss of prospective student confidence.
Example: LinkedIn is facing a class-action lawsuit after allegedly using private messages from premium users to train its AI without proper consent. This highlights how even perceived missteps in data use can quickly erode trust and trigger costly legal consequences.
REMEMBER: This isn’t just an IT concern. It’s a brand, legal, and leadership issue. Champion ethical AI use through internal privacy officers and institutional governance. |
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| | | | | | Are Your Funnels Built for Students or Algorithms?
In the race to optimize, it’s easy to forget who your funnel is really for. Yes, algorithms help you scale, but are you designing for applicants as well as admissions targets?
If your landing pages are overloaded with keywords for SEO bots ️, or your CTAs are A/B tested into blandness , you may be missing what students actually need: clarity, trust, and relevance.
Here’s why it matters:
1️⃣ Algorithms can tell you what converts, but not always why. For example, your highest-performing ad may have a short headline, but your most qualified applications could come from students who clicked deeper, researched your faculty, or visited multiple pages.
2️⃣ Students take nonlinear journeys. While your funnel may look like a neat line in the CRM, actual student behaviour is messy. Prospects Google your professors. They compare competitors. They check Reddit and Quora. Is your institution present at those touchpoints?
3️⃣ Too much automation can create tunnel vision. Automated rules may optimize for cost-per-inquiry but miss long-term student quality or fit. For example, we’ve seen campaigns hit CPA targets while applications from high-intent students lagged.
PRO TIP: The best enrolment funnels? They’re built with students in mind first, then refined with smart, strategic AI support. Not the other way around. |
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| | | | | | What AI Can't Do: The Competitive Advantage of Human Strategy ✅
AI is changing higher ed marketing, but it’s not replacing the strategic minds behind the most effective campaigns. ✨
Human insight remains your institution’s most valuable differentiator, especially in areas like ethics, nuance, and long-term vision. ♀️♂️
Here’s where your leadership still leads:
Seeing the bigger picture.
AI can recommend what to post or when to send, but it won’t capture board priorities, academic reputation, donor expectations, or multi-year enrolment goals.
Tip: Use AI to support your execution, but rely on your team to connect the dots across departments, audiences, and timelines.
❤️ Understanding human emotion.
AI can mimic tone, but it doesn’t understand the gravity of a first-generation student applying or a donor making a legacy gift.
Tip: Craft key messaging for important moments manually. You can then use AI to personalize and scale once the strategy is clear.
⚖️ Making ethical calls.
AI doesn’t always know when something feels off. It might automate outreach that unintentionally targets vulnerable audiences or amplifies bias.
Tip: Set a governance checkpoint before deploying AI-driven campaigns. Your leadership team should always have final say.
Prioritizing what matters most.
AI can crunch numbers, but it doesn’t know your board cares about graduate enrolment growth, program reputation, or alumni engagement.
Tip: Set clear strategic priorities before using AI for recommendations. Let data inform decisions, not dictate them. |
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| | | | | | | Thank you for reading!
We hope you enjoyed your Dose of Noetic. |
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