5 Steps to Transform Your Institution with AI and Agents

The next wave of the artificial intelligence (AI) revolution has begun in higher education.

Much of the debate on AI has focused on whether and how students should use generative AI tools, such as ChatGPT, in their coursework. But what about how higher education institutions can leverage AI to improve the student experience and increase efficiencies across campus? Can AI tools improve faculty and staff workflows? Can it help drive critical outcomes throughout the student lifecycle—in areas such as recruitment and admissions, student success, and advancement? Absolutely. In fact, the 2025 Connected Education Report revealed that 83 percent of staff agree that AI tools free up time for higher-value activities.^Footnote1

As an institutional leader, you need to proactively develop an effective AI strategy that is rooted in trusted, holistic data to help your institution thrive in the long term. But where should you start? How should your institution begin an effective AI conversation? How do you ensure that you adopt the right AI technologies—ones that will drive the most impact for your students, faculty, and staff? And how do you execute your AI strategy in a thoughtful, strategic, and trusted way?

The five practical steps below provide answers to these questions and can help institutions unlock meaningful value from AI across multiple use cases.

Step 1: Identify the top three areas where faculty and staff have trouble getting the data they need.

Make a list of all the scenarios in which your faculty and staff struggle to get the data they need to do their jobs effectively. Then, set priorities. Identify the top three areas across campus that would benefit from a holistic constituent profile. This step will help you identify where predictive and generative AI can drive efficiencies and improve the overall constituent experience.

Step 2: Determine where you are on the AI Maturity Model.

Salesforce developed an AI maturity model to help institutions determine where they stand and where they need to go as they develop an AI strategy. It consists of the following three phases:

• Phase 1: Harmonize your data. Does your institution have data scattered across different databases that can't talk to one another? Do you struggle to contextualize data coming from different sources? Do you need to wait until the end of the week or month for reports? If so, focus on creating a unified, real-time view of your students, alumni, and donors. You need holistic data and a reliable data set for AI to generate accurate conclusions.
• Phase 2: Develop predictive insights. Once you have harmonized your data, harness predictive AI to gain insights into small issues before they become bigger ones. For instance, predictive AI can trigger alerts in your CRM when a student is at risk of not enrolling in courses or of dropping out, helping to ensure that your staff is one step ahead of students' needs.
• Phase 3: Use generative AI to take action. Once you have access to deep insights across your constituent data, you can use that data to generate new actions, such as drafting an email to a student who needs to begin career planning, creating a summary of a recent advising call, or creating a list of relevant job skills for specific courses and programs.

Step 3: Prioritize areas across campus where you want to improve the student experience and increase efficiency.

Where does your institution need a better real-time view of student experiences? Where do you want more than a few "snapshots" of students? By answering these questions, you'll identify areas where you can improve the student experience—and where your staff can be more efficient. Once you've made your list, determine your priorities. Those priorities will inform how your institution advances in its AI journey.

Step 4: Leverage a platform that maximizes the value of AI and data across your institution—one that you and your constituents can trust.

An integrated platform built for the needs of higher education combines the power of data and AI with your CRM so that you can access data, act on it in one place, and trust the results. The CRM is often referred to as the "system of record," but institutions need to move to a "system of engagement" that allows them to create a unified constituent profile and take action on their data—all in one place.

A platform approach also enables you to lead with a trusted AI strategy. With AI innovations developing rapidly, data security is essential for every institution. Salesforce's Einstein Trust Layer ensures that any data passed through the layer is securely retrieved and masked to keep the large language model (LLM) from processing personally identifiable information, is never stored anywhere outside of the CRM, and is scanned for toxicity and bias.

Step 5: Take the next steps to becoming agent ready.

AI agents are the next wave of AI. AI agents are intelligent systems that can understand and respond to inquiries, augmenting the work of humans. They rely on machine learning and natural language processing (NLP) to handle a wide range of tasks, from answering simple questions to resolving complex issues—and even multitasking.

Most importantly, AI agents can continuously improve their own performance and adapt through self-learning. Becoming an agent-ready institution means rethinking how work gets done. The question isn't "How can I do this?"—but rather "How can agents help me today?" Intelligent digital assistants reduce complexity, automate repetitive tasks, and free up time for staff to focus on high-value work—whether that's solving critical problems, driving innovation, or building stronger relationships with prospects, students, alumni, and donors.

Take the following five key steps to prepare for AI agents and make them more accurate and helpful.

1. Invest in staff.
2. Invest in infrastructure.
3. Prioritize data quality.
4. Consider ethics.
5. Think big, start small, and scale.

Becoming agent ready means making a positive shift toward purposeful, impactful work. By aligning technology with staff needs, institutional leaders can streamline operations, enhance the student experience, and strengthen university advancement.

Higher education institutions cannot afford to be slow to adopt predictive and generative AI—or even AI agents. As competition for students intensifies and student expectations increase, institutions that don't develop an AI strategy will fall behind. What you do now to build that strategy will determine where your institution will be in a few years.

Notes

1. Connected Education Report, 4th ed. (Salesforce, 2025). Jump back to footnote 1 in the text.↩