It’s not unusual for two new employees to start the same week at the same institution and have completely different onboarding experiences. One receives a well-developed schedule, clear expectations and thoughtful introductions. The other gets a laptop, a parking pass and little guidance. Both were recruited through the same process, but their onboarding turns out to be uneven, informal and heavily dependent on individual managers.
At Spelman College, we’re using AI to change that — treating onboarding as tactical infrastructure rather than a compliance exercise. We redesigned how we welcome and support new hires, using AI to bring consistency and personalization to those first days so every employee starts with a strong, connected foundation.
Spelman’s Culture as a Strategic Anchor
Spelman College is a historically Black liberal arts college for women in Atlanta, Georgia. Our workplace culture is founded on our institutional values known as R.I.S.E.: Respect, Integrity, Service and Excellence. These values are more than branding. R.I.S.E. determines how work gets done, how leaders act and how employees interact with each other.
Yet, when college leadership explored onboarding, one pattern emerged: the initial 90 days were not always effective in communicating our values. The way a new employee felt about the institution was based more on the manager they had, rather than how the institution had planned. Immersion in the culture was not intentional but informal, evolving by accident rather than design.
The Jaguar Journey Onboarding Framework
To make onboarding more intentional, Spelman created a year-long, AI-supported onboarding program known as the Jaguar Journey. The program takes a new employee from offer acceptance through the first year in a set course of gradual integration, with touchpoints at 30, 60 and 90 days, as well as a six-month checkpoint and one-year reflection dialogue.
The Jaguar Journey is based on three interlinked pillars:
Milestone integration. All new employees go through three major steps. Phase one, between the offer and day one, is psychological preparation and avoidance of any first-day confusion. Phase two, between day one and day 30, focuses on belonging and role clarity. Phase three, days 31 to 90, moves from employee learning to their contributions.
Manager accountability. Managers prepare using checklists prior to the start date of a new employee, and they have specific check-in discussions during every milestone. With increased accountability for onboarding, managers are an active partner in a new employee’s integration: (1) cultural integration into Spelman’s R.I.S.E. values and norms, (2) functional integration into the employee’s role and expectations, and (3) organizational integration into the broader campus ecosystem, including relationships, systems and workflows.
We use AI to scale the onboarding framework while keeping it personalized by tailoring resources and guidance to each employee’s role, department and responsibilities.
AI-assisted personalization. At Spelman, we use AI to scale the onboarding framework while keeping it personalized by tailoring resources and guidance to each employee’s role, department and responsibilities. Rather than delivering a static experience, AI supports the dynamic generation of role-specific summaries, campus navigation guides, and milestone-based prompts, ensuring each employee receives timely, relevant information while maintaining consistency across the institution.
AI-Supported Onboarding
We introduced AI early in the onboarding experience, beginning in the preboarding phase and continuing through the first 90 days.
Managers use AI-supported tools. Managers first use AI-supported tools through structured templates that generate role expectation summaries and onboarding plans. These tools are designed using secure generative AI platforms configured with institutional guidelines and prompts aligned to Spelman’s R.I.S.E. values.
At the departmental level, AI generates role expectation summaries. Summaries provide managers with a structured starting point for early clarity discussions, rather than requiring them to create documentation from scratch. Role expectation summaries synthesize position responsibilities, key priorities and early success indicators, allowing managers to move more quickly into meaningful conversations about expectations and performance.
For new employees, onboarding materials are personalized using AI tools. New employees receive personalized onboarding guides and campus ecosystem maps. These guides are generated based on role type and function, identifying key offices, systems and relationships most relevant to the employee’s day-to-day responsibilities. For example, a staff member in finance receives a different ecosystem guide than a faculty member or student affairs professional. Our targeted approach reduces information overload and accelerates an employee’s ability to navigate the institution effectively.
We also use AI to support manager effectiveness at critical onboarding milestones. At defined intervals (Day 1, 30, 60 and 90), managers receive AI-generated check-in prompts aligned with onboarding goals such as role clarity, belonging and performance expectations. These prompts serve as structured conversation guides, ensuring that onboarding discussions are consistent, intentional and aligned with institutional priorities. Integrated into existing workflows and calendar reminders, these tools reduce the likelihood that onboarding conversations are delayed or overlooked due to competing demands.
How Spelman Implemented AI in Its Process
The AI tools used are primarily built on the OpenAI platform and configured through prompt libraries developed by the director of talent services. These prompt libraries translate institutional knowledge, onboarding standards and cultural expectations into repeatable, scalable outputs. Rather than operating as standalone systems, AI tools are intentionally layered into existing onboarding processes to enhance, not replace, current practices.
Human resources informs employees and managers about the use of AI as part of the onboarding experience and continues to gather positive feedback on its impact. Early input indicates that users view AI tools as valuable in providing structure and reducing ambiguity, particularly in the early stages of employment. Managers have reported increased confidence in leading onboarding conversations, while new employees have noted clearer expectations and a stronger sense of direction during their first 90 days.
The college’s focus on being future ready drove the decision to implement AI-supported onboarding. We recognize that AI is shaping how organizations operate, develop talent and deliver employee experiences. The director of talent services within the Human Resources and Culture department leads this work, which reflects a broader strategy to improve employee experience and operational consistency. Our AI-supported onboarding serves as an early use case within Spelman’s evolving approach to responsible AI adoption, demonstrating how AI can be applied in a structured, values-aligned and human-centered way.
What AI Does and Does Not Replace
The application of AI in the onboarding redesign at Spelman is specific and purposeful. We identified two primary pain points: administrative burden and the challenge of delivering personalized onboarding at scale.
AI reduces administrative burden. Administrative burden often required managers to create onboarding materials, define role expectations and prepare for milestone conversations with little structure or support. The result was inconsistent documentation, delayed check-ins and variability in the onboarding experience across departments. AI replaces much of this manual preparation, allowing managers to spend less time creating materials and more time engaging with employees.
AI eases the challenge of delivering personalized onboarding at scale. Traditional onboarding models rely heavily on standardized content, which does not reflect the unique responsibilities of each role. Personalizing onboarding at scale typically requires significant time and coordination, making it difficult to execute consistently. AI addresses this gap by generating role-specific materials, ensuring that each employee receives relevant and timely information without requiring manual customization.
AI use at Spelman is meant to complement the manager-employee relationship rather than replace it.
However, AI is not a substitute for human communication. AI use at Spelman is meant to complement the manager-employee relationship rather than replace it. Check-ins and discussions remain essential components of the onboarding experience. AI ensures that managers come prepared for each conversation. This preparation allows managers to focus on meaningful dialogue, coaching and relationship-building rather than determining what to cover or how to structure the conversation.
In this way, AI replaces inconsistency, administrative inefficiency and gaps in preparation, but it does not replace the human connection that defines effective onboarding.
Preserving Cultural Integrity
With the implementation of AI tools in processes that engage people, questions of cultural integrity become essential. At Spelman, leaders gave these questions deliberate consideration, as institutional values guide how employees experience the workplace.
Key cultural integrity questions included:
- How to ensure that AI-generated content reflects Spelman’s R.I.S.E. values (Respect, Integrity, Service and Excellence)
- How to mitigate the risk of bias or misrepresentation in generated materials
- How to maintain transparency in the use of AI
- How to preserve authentic human connection within a technology-supported onboarding process
To address these considerations, the team implemented a number of protection mechanisms.
Human resources reviews and approves all AI-generated content prior to dissemination to ensure accuracy, consistency and alignment with institutional values. The team also evaluates content against R.I.S.E. principles to confirm that messaging reflects expected communication and engagement standards.
Human resources informs employees about the use of AI tools within onboarding materials, reinforcing transparency and trust.
In addition, we established data guardrails to protect employee information. These guardrails include restricting the input of personally identifiable information into AI platforms and adhering to data security standards to ensure that sensitive information is not stored, retained or reused inappropriately.
Culture exists in the systems leaders create and sustain, and this principle is embedded in Spelman’s approach.
Culture exists in the systems leaders create and sustain, and this principle is embedded in Spelman’s approach. The institution did not deploy AI tools without structure or oversight. Instead, we established governance requirements that emphasize human supervision, accountability and transparency, ensuring that technology supports, rather than reshapes, the institution’s cultural foundation.
Observable Impact
Although Spelman is still in the process of building the longitudinal data of the redesigned onboarding framework, the initial qualitative pointers indicate the presence of significant changes.
- For new hires, they experience a feeling of being welcomed and expected, not just processed or oriented. Employees start developing dedication at an earlier stage.
- The rate of manager check-in completion has improved because well-organized reminders have minimized the need to schedule milestone conversations during peak times.
- Feedback on new hires after 30 days indicates better initial role clarity as compared to earlier reported cohorts.
- The 90-day preparedness talks are more unanimous in the departments, and onboarding becomes a more uniform experience, no matter which department the new employee is joining.
How Other Institutions Can Start
Leaders of higher education HR who would like to experiment with a similar approach probably should not start with AI. At Spelman, we used AI to address the right pain points, while grounding our implementation in enduring HR practices.
Map the onboarding experience. Start by conducting interviews with new hires and management on the departmental levels. Record what does occur within the first 90 days and not what is supposed to occur according to policy. Find out what the points of high friction are: the points at which clarity lapses, communication halts or when new employees complain of not knowing what to do.
Balance consistency with personalization. Determine which elements need to be consistent and which need to be personalized. Values orientation, compliance training and benefits enrollment should be consistent. Focus personalization where it benefits employees most, like role expectations, navigating the campus ecosystem and performance conversations.
Pilot AI assistance in highly structured risk-free functions. Good places to start are manager reminder systems and role summary templates. These tools do not interfere with high-stakes human interactions because they support the current workflows.
Establish governance. Before scaling AI, identify the reviewer of AI-generated material, the method of assessing cultural alignment, and the data practices that will regulate the use of tools. Innovation is not inhibited by governance. Governance is what renders innovation reliable.
Conclusion
The outcome of Spelman’s redesigned onboarding is a new-hire experience that is anchored in our values, improves equity across departments and is adaptable to the unique needs of the role and individual. For higher education HR leaders seeking to develop a similar system, the path forward is to prioritize your culture and values first, design with purpose, and integrate technology in support of the people, not the other way around.
About the Author: Durrel Parker, Ph.D., is the director of talent services at Spelman College.
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