Sacred Heart’s AI Grants Put Workplace Judgment at the Center

Learning to use an AI tool is different from learning to make sound decisions with it in a workplace. That distinction is at the heart of two new initiatives announced by Sacred Heart University (SHU), which says it has received a combined $150,000 in Connecticut Tech Talent Accelerator (TTA) 3.0 Innovation Grants. For students, families and educators watching how AI changes career preparation, the announcement offers a useful example of what applied learning can look like: projects with real partners, feedback from people outside the classroom and attention to the limits of automated systems.

Two grants, two versions of real-world learning

According to SHU, the Business-Higher Education Forum and the New England Board of Higher Education awarded two separate $75,000 TTA 3.0 Innovation Grants to Sajal Bhatia, a cybersecurity professor, and Grace Guo, a management professor and SHU’s vice president for human resources. SHU says the statewide program requires participating higher-education institutions to work directly with employers to create pathways into technology-related fields.

The university says Bhatia will lead AI TalentBridge, a one-year program based in its School of Computing & Engineering. The initiative is expected to combine foundational AI learning with employer-sponsored challenge projects and virtual pre-apprenticeships. According to SHU, students will work on problems connected to AI-enabled operations, cybersecurity, risk management, responsible AI and digital transformation.

Guo’s grant will support the AI Leadership and Organizational Transformation, or AI LOT, Lab, SHU says. In partnership with the university’s Center for Nonprofits, the lab is intended to pair students with nonprofit organizations. SHU says students will develop recommendations and a playbook meant to help partner organizations use AI in serving underrepresented community members.

The distinction matters. One initiative is designed around employer challenges and professional preparation; the other is designed around organizational needs in the nonprofit sector. According to SHU, both ask students to address problems in a live working context rather than treat AI solely as a classroom topic.

Why the project design matters as much as the technology

SHU says employer partners in AI TalentBridge will help identify challenges, while industry mentors will guide projects, review milestones and provide feedback on technical and professional work. The university also says partnerships may include iQ4, the Cybersecurity Workforce Alliance and OdysseyRe.

That structure points to an important practical lesson for students: a usable AI proposal has to account for more than whether a model or tool can produce an answer. According to SHU, participants will be asked to consider business requirements, security concerns and stakeholder expectations. Those considerations can turn a seemingly simple AI task into a broader exercise in defining the problem, checking outputs, explaining trade-offs and deciding who remains responsible for the final decision.

Bhatia told SHU that students need to understand when AI is appropriate, how to evaluate its output and where human judgment should remain central. For teachers and families, that is a helpful framework for discussing AI use in any setting. A strong assignment or project can ask learners to document their goal, identify what information should not be entered into a tool, verify important claims against reliable materials and explain what they changed after reviewing an AI-generated draft.

• Start with the problem: What need is the organization or community trying to address?
• Set boundaries: What data, privacy, security or fairness concerns need consideration?
• Test the output: What could be inaccurate, incomplete or unsuitable for the intended audience?
• Explain the judgment: Why is a recommendation appropriate, and who will be accountable for acting on it?

Community projects can make AI learning more concrete

According to SHU, the AI LOT Lab will give nonprofit partners recommendations they can use after a student project ends. Guo told the university that the work is intended to have a dual purpose: helping students learn while helping nonprofits improve their capacity to serve their communities.

The announcement does not specify the nonprofit projects, participating students or the measures that will be used to assess results. Those details will matter as the work develops. For instance, families and educators may reasonably look for clarity about how community partners define success, how student recommendations are reviewed before implementation and how the program addresses confidentiality or sensitive information. These are not obstacles to hands-on learning; they are part of responsible project design.

SHU says Guo views the current work as an initial pilot that could eventually extend to students across the university. She also told SHU that AI use should remain grounded in leadership, critical judgment, empathy and compassion. That emphasis is especially relevant when projects involve organizations supporting people who may already face barriers to services or opportunity.

What younger learners can take from the announcement

Although SHU’s grants concern university students, the habits described by the university can begin well before college. K-12 learners can practice explaining their reasoning, checking sources, revising work after feedback and recognizing when a question needs a human conversation rather than an automated answer. These are durable learning habits whether students later pursue computing, health, business, the arts or community work.

For guided practice with those habits, COSMIQ is a free voice-driven AI tutor that is free forever for every K-12 student. Used thoughtfully, free learning support can help students talk through a difficult concept or rehearse an explanation, while teachers and families can still emphasize verification, original thinking and appropriate boundaries around AI use.

According to SHU, the two grants aim to bring classroom learning, industry and community engagement closer together. The announcement’s most useful takeaway is not that AI should replace existing learning, but that students need opportunities to apply knowledge responsibly, receive informed feedback and see how technical choices affect real people and organizations.