Time to Think Beyond the Senior Year Career Readiness Checklist

When thinking about AI in education, or even edtech in general, many district leaders have shifted from what’s the latest and greatest that we need to buy, to thoughtful implementation of tools that truly have an impact on student outcomes.

“EdTech fatigue” is real for teachers, so making sure new solutions take on a lot of the administrative tasks is key, and that’s where AI comes in.

Career readiness does not always land at the top of the list for technology tools administrators are thinking about, but there’s so much promise in using AI to help solve the “skills gap” and help students discover their talents.

During a recent conversation with Allison Danielson, CEO of Tallo, she called this “invisible talent” but also talked about the importance of first defining what we actually mean when talking about a skills gap. Is it competency? Are we giving students the right tools to properly voice their talents?

5 Aspects to Consider When Looking at AI-Enabled Technology for Career Readiness

If you’re a district leader thinking about procurement for AI-enabled education technology, check out these five things you should think about when taking a skills gap approach to career readiness:

1. Timing Is Everything: Career Ready by 10th Grade

When we traditionally think about career readiness, it is usually in the context of a senior year scramble to update our resume or take that one interest assessment. However, kids are generally creating assumptions about careers way too early based on their surroundings. How can this be more formally introduced, and what are the benefits?

• Prioritizing assessments and tools as early as middle school is key to unlocking students’ likes/dislikes and interests.
• Students can fall behind fast in Math and English, and being at a certain level is required to take credit-level courses at most colleges.
• Students who know why they are taking a math or English class (how does this help me earn?) will have higher engagement levels and overall confidence.

2. Translation Layer for “Invisible Talent”

District leaders have the opportunity to close not only a skills gap but also a language gap with students. Students working service-level jobs (retail, food service, or even sports) often believe they are gaining “no skills” from their job.

• Artificial intelligence and smart technologies can be the scalable “translation layer” that helps students talk through how working at  a restaurant or in retail has given them the ability to demonstrate high-level skills like prioritization during crunch times, crisis management, and leadership through teamwork.
• By procuring the right tools that can help students understand their “invisible talent,” leaders can focus on equity and ensure underrepresented students are receiving this type of coaching.

3. Better Simulations Mean More Prepared Students

When thinking about evaluating AI career coaches or readiness platforms, district leaders should consider how the technology helps students actually “try on” a career before taking on the debt or time commitment of post-secondary education.

• Look for tools that provide students with an immersive “Day in the Life” experience as opposed to a static job description.
• Strategic AI tools should lead students through conversational simulations, like what they would actually experience during an urgent hospital shift. Not only will students walk through the steps they would take to solve problems that come up during their shift, but they can also assess what they don’t like about that career.
• By allowing students to simulate moments in a career, students can avoid the “ROI risk” of spending time and money on a certain training program or degree path if they hate it.When looking at different AI coaching platforms, district leaders should ensure the tool is trained on valid career readiness frameworks.
• Additionally, vendors should have thoughtfully “trained out” biases in the technology that may downplay certain vocations or non-traditional career paths.

4. Lose the GPA, Focus on the Artifacts

As AI changes starts to change the game for recruiters, the traditional GPA benchmark starts to lose meaning. Ultimately, employers are looking at GPAs as only a proxy that a student was competent in school.

• Leaders should prioritize tools that allow students to build artifacts of their skills (portfolios, work samples) that can be used to validate skills with outside employers.
• While professional connections are always important to help students pursue careers, we often don’t have the infrastructure to track how many professionals students have actually spoken with. Seek out tools that help students map and grow network connections, as networks are one of the largest drivers of success in the workforce.

5. Leveling up How Students Think About AI

One of the things Allison pointed out that I love is that one of the most important things we can do as we start to introduce AI into the classroom environment is to help students learn to be healthy skeptics and think through how to use these tools strategically.

• Leaders should look to procure tools that make students think when interacting with AI. The more we can require students to use advanced communications skills (how do you know this is a fact and not an AI hallucination?), the more comfortable they will be navigating AI solutions outside of school.
• Students are already skeptical that they will be replaced by a robot one day. Leaders should focus on empowering students to see how AI handles mundane tasks and enables them to tackle bigger problems.