Last year, higher education leaders were preparing for the possibility of Workforce Pell. Now, institutions have federal guidance, implementation timelines, and growing pressure to act.

The U.S. Department of Education’s (DOE) final Workforce Pell rule establishes a framework for short-term, Pell-eligible programs beginning July 1, 2026. For colleges and universities facing enrollment pressure, changing learner expectations, and increased scrutiny around career outcomes, this development represents a meaningful strategic opportunity.

It’s time for institutions to move from awareness to preparation.

What changed in the final Workforce Pell rule?

The Workforce Pell Grant program expands Pell eligibility to certain short-term undergraduate workforce training programs. The goal is to create new pathways for students seeking faster, career-focused education opportunities.

Under the DOE’s newly released guidance, eligible programs must generally:

• Run at least eight weeks, but less than 15 weeks
• Include between four and 15 semester credit hours
• Prepare students for “high-skill, high-wage, or in-demand” occupations
• Receive approval from governors and state workforce boards
• Meet accountability benchmarks tied to completion, placement, and earnings outcomes
• Receive final approval from the Department of Education

The rule also allows governors to establish agreements that enable approved workforce programs to be offered across state lines through distance education.

While institutions now have a clearer framework, many details will continue evolving over the next several years. State workforce priorities, approval standards, and accountability expectations may vary during the transition period leading up to the federal earnings metrics scheduled for 2030–31.

For institutions, Workforce Pell creates a new category of aid-eligible programming that connects workforce development more directly to academic strategy.

Why Workforce Pell matters strategically

The institutions most likely to benefit from Workforce Pell are the ones that focus on aligning academic portfolios with workforce demand and student expectations.

The opportunity extends beyond launching additional certificate programs. Workforce Pell creates new ways to engage adult learners, working professionals, career changers, and stop-out students seeking shorter educational pathways tied directly to employment outcomes.

Many of these learners prioritize flexibility, affordability, and clear career value. Short-term workforce programs supported by Pell funding align closely with those priorities.

At the same time, institutions may uncover opportunities to expand or refine their portfolios through stackable credentials, workforce-focused certificates, and employer-aligned education pathways.

As opportunities expand, accountability expectations will also increase. Institutions will need to demonstrate that programs lead to meaningful workforce outcomes and sustainable earnings potential. That reality places greater emphasis on labor market alignment, employer engagement, and data-informed planning.

The gray areas institutions need to watch

Although the final rule provides important direction, several operational questions remain unresolved.

Governors and state workforce boards will play a major role in defining workforce priorities and approval standards until federal earnings metrics take effect. Institutions operating across multiple states may encounter varying expectations regarding program eligibility and workforce demand.

Operational readiness will also become a major factor in institutional success. Launching Workforce Pell-eligible programs requires coordination across academic leadership, enrollment operations, marketing, financial aid, instructional design, and employer partnerships.

Many institutions already have promising workforce concepts in place. The larger challenge may involve building the infrastructure and processes needed to implement programs efficiently while maintaining compliance and quality standards.

How institutions should start preparing now

Schools don’t need to wait for every detail to be finalized before beginning strategic planning. Early preparation will help colleges and universities move more confidently as Workforce Pell implementation approaches.

1. Start with a portfolio audit

Many institutions may already offer undergraduate programs that align with Workforce Pell requirements or could qualify with modest adjustments.

Key questions to evaluate include:

• Which existing programs may already meet eligibility requirements?
• Which offerings could be adapted into shorter formats?
• Where are the gaps in workforce-focused programming?
• Which programs align with high-demand industries in the institution’s region?

This process can help institutions identify existing opportunities within their current portfolio.

2. Use labor market data to guide decisions

Workforce Pell eligibility will depend heavily on workforce demand and earnings potential. Institutions should evaluate regional employment trends, high-growth industries, wage projections, employer hiring demand, and skills shortages before making program expansion decisions.

Data-informed planning will become increasingly important as institutions compete to launch workforce-relevant offerings.

Collegis helps institutions identify high-demand, high-wage program opportunities through labor market analysis, publicly available workforce data, and Lightcast-powered insights. These resources help institutions align academic strategy with student demand and regional economic needs.

Learn more about this process in our article, “Leveraging Data to Guide Academic Portfolio Strategy”.

3. Assess operational readiness

Institutions should also evaluate whether they have the operational infrastructure needed to support Workforce Pell implementation.

Areas to assess include:

• Program approval workflows
• Online and hybrid delivery capabilities
• Enrollment and marketing strategy
• Student support services
• Financial aid administration

Institutions that can move efficiently while maintaining strong student outcomes will be better positioned for long-term success.

Workforce Pell reflects a broader shift in higher education

Workforce Pell aligns with broader changes already shaping higher education. Students increasingly seek faster and more flexible pathways connected directly to career advancement. Policymakers continue focusing on measurable return on investment, while employers need workforce-ready talent equipped with in-demand skills.

Institutions that respond effectively will strengthen their ability to adapt to changing workforce needs and evolving student expectations.

Position your institution now for the next era of workforce education

Workforce Pell reinforces the shift toward workforce-connected, career-focused education. As institutions prepare for implementation, leaders will need to evaluate how their academic portfolios align with workforce demand, student expectations, and regional economic needs.

The colleges and universities that begin assessing program opportunities, market alignment, and operational readiness now will be in a stronger position when these regulations take effect in 2026.

If your institution is evaluating how Workforce Pell could shape future program strategy, Collegis is here to help. Through market research and portfolio development support, we help colleges and universities identify high-demand opportunities and make informed decisions about future growth.

Rising acquisition costs, tighter budgets, and growing scrutiny from boards and cabinet leaders are forcing colleges and universities to rethink how they operate.

Many institutions have responded with budget reductions, hiring freezes, or across-the-board cuts. Yet cost-cutting on its own rarely creates long-term stability. In many cases, it limits growth opportunities, weakens the student experience, and reduces institutional agility at a time when adaptability matters most.

The greater opportunity lies in redesigning how work gets done across the institution.

Colleges and universities that improve operational efficiency and optimize enrollment spending are not simply reducing expenses. They’re creating stronger alignment between data, technology, and institutional leadership to gain clearer visibility into performance and make smarter investment decisions throughout the student lifecycle.

Understanding where acquisition and operating costs accumulate is the first step toward building a more sustainable path forward.

The hidden drivers of rising acquisition and operating costs

Financial pressure rarely stems from one source. It builds quietly across disconnected systems, siloed teams, and reactive decision-making.

1. Inefficient student acquisition strategies

Enrollment marketing budgets continue to rise, yet many institutions lack full visibility into:

• True cost per inquiry
• Cost per enrollment by channel
• Funnel conversion bottlenecks
• Marketing ROI across platforms

Without integrated data, enrollment cost optimization becomes guesswork. Dollars are spent, but performance insights remain fragmented.

2. Technology bloat and underutilized systems

Technology investments should drive efficiency and innovation. But in many cases, they create new layers of complexity and cost.

Many institutions operate with:

• Redundant platforms across departments
• Incomplete IT implementations
• Manual processes that increase labor costs
• Overburdened internal IT teams

When infrastructure isn’t streamlined, operational expenses rise while innovation slows. Technology should enable efficiency, not create friction.

3. Fragmented data environments

Data often lives in disconnected systems: CRM, SIS, LMS, finance, and marketing automation. Reporting becomes manual, forecasting becomes unreliable, and decision-making becomes reactive.

Without unified, accessible data, higher ed operational efficiency remains out of reach.

4. Leadership gaps during critical moments

Transitions at the executive level can stall progress. Open CIO, CMO, or enrollment leadership roles create uncertainty. Strategic initiatives pause and budget alignment weakens.

Institutions lose momentum, and momentum is expensive to rebuild.

A smarter path forward: Aligning data, technology, and talent

Reducing acquisition and operating costs requires more than tactical adjustments. It demands structural alignment.

Institutions that achieve sustainable higher ed operational efficiency focus on three integrated levers:

1. Strategic leadership alignment
2. Technology optimization
3. Data unification and intelligence

When these elements work together, enrollment cost optimization becomes measurable, repeatable, and scalable.

Strengthen strategy with fractional leadership support

Executive leadership shapes how institutions allocate resources, prioritize initiatives, and measure success. But hiring full-time cabinet-level leaders isn’t always feasible, especially during financial constraints.

Fractional leadership offers a strategic alternative. Experienced higher ed executives can step in to:

• Assess current systems and spending
• Align marketing, enrollment, IT, and finance
• Develop roadmaps tied to measurable outcomes
• Stabilize operations during leadership transitions

The impact is immediate. Institutions gain strategic clarity without adding permanent overhead. Strong leadership reduces waste before it happens. It prevents misaligned investments. And it ensures every dollar supports institutional goals.

That’s the foundation of enrollment cost optimization.

Optimize infrastructure with IT managed services

Internal IT teams are often stretched thin, managing daily maintenance while attempting to advance digital transformation initiatives. This imbalance drives inefficiency.

A managed IT services model allows institutions to:

• Reduce infrastructure overhead
• Improve system reliability
• Increase automation
• Shift internal focus from maintenance to innovation

Economies of scale make enterprise-level expertise accessible at a fraction of the cost of building large internal teams. When infrastructure is stable and proactive rather than reactive, higher ed operational efficiency improves across every department — from admissions to advancement.

And when IT operates strategically, institutions reduce unplanned expenses, project overruns, and costly downtime.

Turn data into a cost-control engine

Data isn’t just a reporting tool. It’s a financial strategy. Institutions that unify their data environments gain:

• Clear attribution across the enrollment funnel
• Real-time visibility into cost per enrollment
• Improved forecasting accuracy
• Faster identification of underperforming channels
• Better allocation of marketing and operational budget and resources

When data is fragmented, leaders rely on intuition. When data is integrated, leaders rely on evidence. That shift changes everything.

With a unified data environment, enrollment cost optimization becomes precise. Institutions stop overspending on low-performing tactics and reinvest in strategies that drive measurable returns.

Data clarity reduces volatility, protects tuition revenue, and fuels smarter growth.

The multiplier effect: Integration drives exponential impact

Each lever (leadership, IT, data) creates value independently.

Together, they transform institutional performance. Fractional leadership sets strategic direction. Managed IT stabilizes and streamlines infrastructure. Unified data informs continuous optimization.

The result:

• Lower cost per enrollment
• Reduced technology redundancy
• Fewer reactive expenditures
• Increased financial predictability
• Improved higher ed operational efficiency across departments

This isn’t isolated cost-cutting. It’s institutional alignment.

Cost Reduction as a Growth Strategy

Cost discipline doesn’t mean contraction. When institutions eliminate inefficiencies, they create capacity.

Capacity to:

• Reinvest in student experience
• Enhance digital transformation initiatives
• Support faculty and staff more effectively
• Expand into new markets strategically

Higher ed operational efficiency strengthens mission delivery. Enrollment cost optimization protects revenue. And aligned systems allow institutions to compete with confidence.

Financial resilience and growth are not opposing goals. When strategy, infrastructure, and data work together, they reinforce each other.

Build a leaner, smarter institution

Reducing acquisition and operating costs requires a more connected approach to institutional strategy. Colleges and universities that align decision-making with the right technology and operational structure are better positioned to improve efficiency, strengthen visibility into performance, and support sustainable growth.

When strategy, systems, and spending work together, institutions gain the flexibility to reinvest resources in areas that improve the student experience and strengthen long-term outcomes.

Collegis works alongside colleges and universities to build integrated operating models that improve institutional performance while supporting each institution’s mission and goals.

Let’s build an operating model that works harder for your institution.

AI didn’t just show up at this year’s ASU+GSV Summit. It took over.

In past years, artificial intelligence had its own dedicated space at the AI Airshow, a pre-conference event focused on emerging tools and forward-looking innovation. This year, that separation dissolved. Not because AI mattered less, but because it now defines the conversation.

AI wasn’t a track. It was just about the entire conference.

Across sessions, vendor showcases, and side conversations, one theme dominated: how AI is reshaping higher education. From student engagement to learning design to institutional strategy, AI has become the default lens institutions use to evaluate their priorities and how they invest for the future.

And yet, what stood out most wasn’t just what was present. It was what was missing.

The missing conversation: structural challenges still exist

For all the attention on AI, there was less focus on the systemic pressures facing higher education:

• Ongoing enrollment declines and demographic shifts
• Increased regulatory scrutiny
• Growing skepticism around the ROI of a degree

These challenges didn’t disappear. Not to say it was completely absent from the conversation, it was simply overshadowed.

AI is being positioned as the one-size-fits-all solution to many of these issues, but it does not address their root causes on its own. That disconnect is one that institutions cannot afford to ignore.

From tools to workflows: AI gets operational

One of the most important shifts emerging from the conference is how institutions are thinking about AI implementation. The conversation has moved beyond tools.

Institutions are now being pushed to rethink AI as part of how work actually gets done. That means embedding AI into core workflows, including:

• Enrollment funnels
• Advising models
• Student support systems
• Operational decision-making

This is a meaningful evolution. But the market has not fully caught up.

Many solutions are still positioned as “easy buttons,” promising outcomes without requiring operational change. That gap between expectation and execution is where many AI initiatives will stall.

AI does not transform outcomes on its own. It requires institutions to redesign workflows, rethink processes, and align teams around new ways of operating.

Data is the divider between progress and stagnation

If there was one clear line separating institutions poised to benefit from AI and those at risk of falling behind, it is data.

AI amplifies what already exists. It does not create capability from nothing.

Institutions with strong data foundations — including integrated systems, accessible insights, and clear governance — are already moving faster. They are scaling what works and translating experimentation into measurable outcomes. Others are stuck in pilot mode.

Without the right infrastructure, AI initiatives remain fragmented and difficult to sustain. This reinforces a broader reality. Data strategy is no longer a back-office function. It is a prerequisite for institutional transformation.

Collegis sees this firsthand. Institutions that invest in unified, actionable data environments are better positioned to drive decision-making, improve enrollment outcomes, and enhance the student experience at scale.

The vendor model is evolving into partnership

Another shift was impossible to miss. The traditional vendor model is breaking down.

AI solutions are not static. They require continuous tuning, iteration, and alignment with institutional context. There is no one-size-fits-all configuration that works across campuses.

As a result, institutions are rethinking what they need from external support. They are not looking for vendors. They are looking for partners.

The value is no longer just in the technology itself. It is in the ability to:

• Adapt solutions over time
• Align with institutional goals and operations
• Provide ongoing strategic and technical guidance

This shift reflects a broader trend across higher education. Sustainable impact comes from integrated partnerships, not point solutions.

AI’s real value is human impact

Despite the heavy focus on technology, the most compelling narrative at ASU+GSV was not about automation. It was about people.

Across sessions, AI was consistently framed as a way to free up staff and faculty time, enabling more meaningful engagement with students. In a sector built on human connection, that framing matters.
But it also raises expectations.

If AI does not lead to better student outcomes — stronger persistence, improved engagement, and clearer pathways to completion — it will quickly lose credibility. Institutions are not investing in AI for efficiency alone. They are investing in impact.

The shift from experimentation to accountability

Taken together, these themes point to a critical inflection point. Higher education is in a phase of rapid experimentation. AI tools are accessible, widely adopted, and full of promise.

But many of the solutions entering the market today lack the operational depth required to deliver sustained results. There are no plug-and-play answers to enrollment challenges or retention gaps.

These are system-level issues. Solving them requires:

• Strong data foundations
• Thoughtful workflow design
• Cross-functional alignment
• Partners who understand how institutions operate

The next phase will not be defined by experimentation. It will be defined by accountability.

AI will reward the institutions that are prepared

For me, the key takeaway from ASU+GSV 2026 is clear: AI will be transformative, but only for institutions prepared to do the work around it.

That involves:

• Investing in data infrastructure
• Rethinking how work gets done
• Building true operating partnerships
• Staying focused on outcomes, not just adoption

Institutions that take this approach will move beyond experimentation and unlock real, measurable impact. Those that do not will risk entering the next phase of the cycle, where expectations collide with reality and skepticism begins to take hold.

That shift may very well define next year’s conversation.

In higher education, “partnership” is a word that gets used often. But in practice, many institutions aren’t experiencing true partnership — they’re simply managing vendors.

And there’s a difference.

Institutions today are operating in an environment defined by complexity. Enrollment pressures, evolving student expectations, and increasing scrutiny around outcomes are converging all at once. Internal teams are navigating this while balancing limited time, resources, and competing priorities.

After working closely with several institutional teams, one thing has become clear: Partnership works best when it’s truly integrated. Anything less can create friction, slow progress, and limit impact.

What you don’t see from the outside

From the outside, institutional challenges can look straightforward. But inside, the reality is more nuanced.

There are silos across departments. Not because teams don’t want to collaborate, but because aligning priorities, timelines, and decision-making across a complex organization takes time. Everyone is working toward the same goals, but forward momentum can be slow.

At the same time, most teams are stretched thin. Leaders and staff are wearing multiple hats, often balancing day-to-day execution with long-term strategic initiatives. That combination (complexity and limited capacity) creates a real challenge. It’s not a lack of ideas. It’s a lack of time, alignment, and resources to move those ideas forward.

This is where the right partner can make a meaningful difference. Not by adding more to the plate, but by helping connect the dots, reduce friction, and create momentum across teams.

Why traditional models fall short

Many traditional outsourcing models weren’t built for this level of complexity. They often operate with limited transparency, where institutions don’t have full visibility into strategy, performance, or decision-making.

The focus tends to be on task execution rather than outcomes. And in many cases, there’s little effort to build internal capacity or share knowledge in a way that strengthens the institution over time.

The result is a disconnect. Work gets done, deliverables are met, but the institution isn’t necessarily better positioned for the future.

That’s the gap real partnership is designed to close.

What true partnership actually looks like

A true partnership isn’t defined by deliverables — it’s defined by shared ownership.

This looks like:

• Shared goals and accountability
• Strategic alignment across teams
• Transparency and open dialogue
• Integrated teams working side by side
• A commitment to continuous improvement

It also comes with a different mindset. One grounded in trust, where recommendations are made with the institution’s best interests in mind. A true partner asks, “What would we do if this were our own investment?”

That level of alignment allows both sides to move faster, adapt quickly, and stay focused on outcomes that matter.

How integration changes outcomes

When a partner is fully integrated, the way work happens changes.

Meetings shift from presentations to working sessions. Teams collaborate in real time, bringing different perspectives to the table and solving problems together. There’s a shared understanding of when to take initiative and when to pause for alignment.

That proximity leads to better and faster decisions. It also builds stronger relationships. Over time, trust develops not just through results, but through consistency, communication, and a genuine investment in each other’s success.

The work becomes more human, more connected, and ultimately, more effective.

Turning complexity into clarity and results

One example that stands out to me is a partner institution that lacked clear visibility into how their marketing efforts were performing. Data existed across systems and vendors, but there was no unified view, and no way to confidently connect strategy to outcomes.

Through close collaboration across teams, we aligned on both enrollment goals and a clear learning agenda for marketing. From there, we worked together to improve data governance, clean up historical data, and build custom reporting tailored to their business and learning needs.

The result was more than better dashboards. It was clarity beyond KPIs.

The institution gained a clear understanding of attribution, which allowed them to make more informed decisions, optimize their strategy, and ultimately drive stronger enrollment outcomes.

That kind of progress doesn’t happen in isolation. It requires integration, alignment, and a shared commitment to getting it right.

What it takes to build a strong partnership

True partnership doesn’t happen automatically. It’s built over time.

It starts with listening — taking the time to understand each institution’s culture, history, and priorities. From there, it requires transparency. Not just when things are going well, but especially when they’re not.

Trust is built through honesty, alignment, and consistent follow-through. And most importantly, it’s sustained by a shared focus on outcomes. When both sides are aligned on what success looks like, the work becomes more focused, more collaborative, and more impactful.

What institutions should look for in a partner

For institutions evaluating potential partners, the right questions matter.

Look for a partner who can clearly articulate their approach — how they’ll understand your institution, align to your goals, and deliver results.

Understand how the partnership will function day to day. Who are your points of contact? How accessible are subject matter experts? How is communication structured?

And just as importantly, assess flexibility. The ability to adapt, pivot, and evolve alongside your institution is critical in today’s environment.

The right partner integrates into your team in a way that drives alignment, momentum, and measurable results.

A new standard for partnership in higher ed

Partnership models in higher education are evolving. Institutions are looking for greater transparency, more flexibility, and stronger alignment to outcomes. They need partners who can help them do more with less, leveraging data, technology, and expertise in ways that drive meaningful progress, not just incremental change.

The institutions that move forward fastest will be the ones that choose partners differently. Not vendors who operate at a distance, but integrated teams who align to their goals, adapt alongside them, and take shared ownership of outcomes.

That’s the standard Collegis brings to every partnership — working as an extension of your team to turn strategy into measurable impact.

The Collegis Impact 

The revised forecasting model gave Augusta University Online clearer insight into how marketing investment should be distributed throughout the year to support enrollment goals.

Key outcomes included:

• Revealed that inquiries generated in a given month often influence multiple future start terms, not just the next one
• Demonstrated that Fall start terms typically require at least a year-long lead generation cycle
• Identified opportunities to rebalance media spend across programs and months
• Provided leadership with a more accurate framework for forecasting enrollment impact from paid media investment

These insights helped Augusta align marketing budgets with realistic enrollment timelines and make more informed program-level investment decisions.

The Takeaway: Accurate Forecasting Drives Smarter Investment

Marketing performance isn’t just about generating leads. It’s about understanding when those leads will convert and how they support future enrollment goals. By leveraging historical CRM data, Collegis helped Augusta University Online build a forecasting model that better reflects real student behavior and supports more strategic marketing investment.

Align Marketing Strategy with Future Enrollment Demand

Augusta University Online’s experience highlights the importance of aligning marketing forecasts with actual enrollment patterns. Collegis partners with institutions to transform marketing and CRM data into actionable insights, helping leaders allocate budgets more effectively, support program growth, and drive sustainable enrollment outcomes.

The rush to AI implementation in higher ed is all too common. But most institutions start in the wrong place, focusing on AI tools and point solutions that promise a silver bullet to fix all their challenges and capacity constraints. Clouded by this AI land-grab mentality, teams overlook the unsung hero of AI success: your own data. Failure to focus on this foundational aspect just gets you another expensive tool that doesn’t scale, AI outputs you can’t trust, and missed opportunities for genuine institutional transformation.

Before your institution invests further in AI, it’s worth asking a more important question: Is your data actually ready to support it?

AI Starts with Your Data, Not Demos:
The AI Mistake Higher Ed Keeps Making
(and How to Fix It)

Thursday, April 30
1:00 pm ET / 12:00 pm CT 

What you’ll learn 

In this webinar, Dan Antonson and Bryan Chitwood break down the mistakes many institutions are making as they rush toward AI adoption and what to do instead. Join us for a practical conversation on how higher ed leaders can move past surface-level demos and start building the data strategy, structure, and readiness needed to support AI that actually drives impact.

They’ll explore what AI readiness really means in higher education and why strong outcomes start with connected, usable, trustworthy data.

• Why starting with AI tools instead of a data strategy often leads to stalled initiatives and weak results
• What institutions need in place before AI can drive meaningful value
• How to identify the biggest data barriers standing in the way of AI readiness
• Where to focus first to create momentum without overcomplicating your approach
• How to connect AI efforts to measurable outcomes across enrollment, student experience, and operations

Who should attend

If you’re a leader responsible for strategy, transformation, and data-informed decision-making, and your institution is exploring AI but wants to make smarter decisions before moving too fast, this is one conversation you don’t want to miss.

• Presidents, provosts, and cabinet-level leaders
• CIOs, CTOs, and IT leaders
• Institutional research and data leaders
• Enrollment, marketing, and student success leaders
• Strategy, innovation, and operations teams evaluating AI use cases

Expert speakers

Complete the form on the top right to reserve your spot. We look forward to seeing you on Thursday, April 30. 

Higher education is at an inflection point with AI.

Across the market, institutions are being presented with a steady stream of solutions promising fast implementation, low cost, and immediate impact. For leaders navigating enrollment pressure, retention challenges, and operational strain, the appeal is obvious. A tool that delivers quick wins and signals innovation to boards and stakeholders feels like an easy yes.

But there’s a more important question beneath the surface: Are institutions truly positioned for AI to deliver value at scale?

That’s where many AI point solutions begin to fall short.

The promise (and the gap)

AI point solutions often perform well in controlled environments. They demonstrate clear value in narrow use cases such as automating outreach, flagging at-risk students, or improving service response times. In isolation, those capabilities matter.

But higher education doesn’t operate in isolation.

Most institutions are working across a complex ecosystem of systems and stakeholders. Student data lives in SIS platforms, LMS environments, CRMs, marketing automation tools, and more. Even when that data exists, it’s rarely unified. Definitions vary, records are incomplete, and structures differ across departments.

So while a point solution may function well on top of a single dataset, scaling that impact across the institution becomes significantly harder. Because when data is fragmented, outcomes are inconsistent. And when outcomes are inconsistent, adoption stalls.

AI doesn’t fix disconnected data

There’s a common misconception driving many early AI investments: that AI can compensate for weak data environments. The truth is that it can’t.

AI accelerates analysis. It identifies patterns faster than any team could on its own. But it still relies on the quality, consistency, and completeness of the underlying data. And in higher education, that foundation is often the limiting factor.

A student is not a single record or transaction. Each student represents a series of connected signals over time, including academic progress, engagement patterns, financial behavior, and support interactions. When those signals remain disconnected across systems, no AI layer can fully reconstruct the story.

The result is partial insight. And partial insight leads to partial action.

Institutions don’t need more outputs. They need outputs they can trust and operationalize.

Building a foundation for scale

This is why successful AI adoption in higher education doesn’t start with the model. It starts with the data foundation.

At Collegis, we approach this through the concept of the ‘student digital twin’, a connected, continuously updated view of student behavior and institutional data. The goal isn’t to introduce another tool. It’s to create a trusted layer that enables better decision-making across enrollment, retention, and student engagement.

When AI models are built on that kind of foundation, the outputs become more than predictions. They become actionable insights tied to real institutional context.

We see this directly in our own solution design and delivery work. The most effective retention strategies don’t operate as standalone tools. They rely on structured data integration, defined onboarding processes, and governance frameworks that ensure outputs are grounded in accurate, current information.

That’s the work many point solutions attempt to bypass. And it’s the reason they struggle to deliver sustained value.

Without governance, AI stalls at experimentation

Even with strong data, another challenge emerges: how AI is deployed across the institution.

Too often, AI adoption begins as a series of disconnected experiments owned by individual departments, driven by immediate needs, and implemented without a shared framework. While that approach can generate early momentum, it rarely leads to long-term impact.

Scaling AI requires governance.

Institutions need clear answers to critical questions:

• What decisions should AI support?
• What data is accessible and trusted?
• How are outputs validated and monitored?
• Who is accountable for oversight and outcomes?

Without that structure, confidence in AI erodes quickly. Teams hesitate to act on insights they don’t fully understand, leaders struggle to evaluate effectiveness, and adoption slows.

This becomes even more critical in student-facing applications. If staff can’t explain how a recommendation was generated, or if the underlying data is unclear, trust breaks down. And without trust, AI becomes another underutilized tool rather than a strategic asset.

Expertise turns insight into action

There’s one more gap that technology alone can’t close: context. AI can generate insight, but it doesn’t understand institutional nuance on its own.

Enrollment isn’t just lead management. Retention isn’t a standard lifecycle model. Student engagement isn’t solved through automation alone. Each of these areas requires a deep understanding of how colleges and universities operate, how students behave, how teams work, and where friction actually exists.

That’s where expertise becomes essential.

It takes experienced teams across enrollment, marketing, retention, and IT to interpret AI-driven insights, determine what matters, and translate that into meaningful action. Without that layer, even the most advanced models fall short of their potential.

Technology informs decisions. People make them effective.

The foundation institutions need for AI success

None of this suggests institutions should slow down their investment in AI. The opportunity is real and growing. But institutions that see lasting value won’t be the ones that adopt the most tools. They’ll be the ones that build the right capabilities.

That includes:

• Connected data environments that unify information across systems
• Clear governance frameworks that guide how AI is used and evaluated
• Operational models that translate insight into consistent action
• Deep institutional expertise that grounds AI in real-world context

Point solutions will continue to play a role. Some will deliver meaningful value within targeted workflows. But they aren’t a substitute for the foundational work required to support AI at scale.

If the goal is to improve enrollment outcomes, strengthen retention, personalize engagement, or drive operational efficiency, the path forward is clear: Build the infrastructure that makes AI effective before expecting it to be transformative.

Leading with intention in an AI-driven future

AI will shape the future of higher education, but leadership in this space won’t come from moving fastest. It will come from building with intention.

The institutions that lead will invest in data they can trust, governance they can sustain, and expertise they can rely on. They’ll move beyond experimentation and toward integration, embedding AI into the way their institutions operate, not just the tools they use.

That’s where real impact happens. And it’s where Collegis continues to focus, helping our partners build the connected, scalable foundation required to turn AI from a promise into measurable progress, grounded in a clear data and AI strategy that aligns insight with action.

The Collegis Impact 

MGH IHP launched its Doctor of Health Sciences program in Fall 2025 with strong initial demand.

Key results include:

• Inaugural cohort filled for the Fall 2025 launch
• Exceeded first-year enrollment goal by 130%
• Additional prospective students waitlisted for future starts
• A streamlined curriculum designed to leverage existing institutional strengths
• Competitive tuition pricing with special benefits for employees at partner institutions

These outcomes demonstrate how a market-informed strategy can help institutions launch new programs with confidence and generate early enrollment momentum.

The Takeaway: Strategic Market Intelligence Drives Successful Program Launches

Launching a new academic program requires more than a promising idea. Institutions need clear insights into market demand, competition, and positioning. With the support of Collegis program research and marketing strategy, MGH Institute of Health Professions launched a doctoral program aligned with market opportunity — resulting in a successful first cohort and strong student demand.

Launch Your Next Academic Program with Confidence

MGH IHP’s success highlights the value of data-driven program development. With the right market research, marketing strategy, and enrollment support, institutions can turn program ideas into market-ready offerings.

You Can’t Cut Your Way to Growth in Higher Education

During conversations with dozens of institutional leaders at our recent DisruptED summit, it is clear that they are facing unprecedented financial pressure.

Tuition revenue is declining at many institutions. Retention rates are slipping. The demographic pipeline of traditional-age students continues to narrow. Competition is intensifying. And labor costs (often the largest line item on the budget) rise year over year.

When the top line shrinks, the immediate instinct is simple: cut expenses. Balance the budget by reducing overhead, freezing hiring, trimming programs, delaying investments, etc.

Fiscal discipline is necessary. Institutions do need to right-size expenses. But here’s the reality: You can’t cut your way to growth.

The temptation of expense control

Few colleges and universities have endowments large enough or flexible enough to offset sustained enrollment declines. When revenue drops, leaders often turn to the most direct lever: expense. It’s measurable, it can be immediate, and it creates the appearance of control.

Reducing costs can stop the bleeding, but it does not address the structural challenges driving financial strain in the first place. Enrollment headwinds are not temporary, retention pressures are not isolated, and labor costs will continue to increase.

And there is a limit to how much you can cut. There is only so much you can remove before you begin weakening the very capabilities required to compete. At some point, you’re cutting into bone.

The hidden costs of cutting your way to stability

When institutions focus exclusively on expense, they often underinvest in the very capabilities that generate and protect revenue.

There are areas in higher education that are not discretionary — they are strategic.

Enrollment infrastructure

Reducing marketing investment or enrollment operations may create short-term savings. But it weakens the pipeline that fuels future cohorts.

If institutions scale back recruitment strategy, market visibility declines, inquiry flow softens, and conversion rates slip. The downstream impact may not show up immediately, but it will compound.

Enrollment is not optional spending. It is revenue generation.

Retention and student support

Retention protects the revenue institutions have already worked so hard to earn. When student support structures are reduced or there is unnecessary friction in the student lifecycle, stop-out rates increase, students disengage, and tuition dollars disappear.

Improving retention requires intentional investment in data, technology-enabled engagement models, and proactive outreach. Cutting here may balance a line item today while accelerating revenue loss tomorrow.

Data and technology modernization

Many institutions are allocating substantial dollars to maintain outdated infrastructure. Siloed systems, inefficient processes, and disconnected data environments absorb budget without advancing growth.

You cannot compete in today’s environment with yesterday’s infrastructure.

Growth requires more than maintaining legacy systems. Institutions must invest in a modern, connected data ecosystem that brings together enrollment, retention, academic, and financial insights in real time. Without integrated, reliable data, AI initiatives stall before they scale and generate ROI. A unified data foundation is the prerequisite for innovation and sustainable growth.

IT capability and cybersecurity

Technology has become central to institutional resilience. Reducing IT capability may appear efficient, but it often eliminates critical skill sets and increases cybersecurity exposure. In an era of escalating threats, a fragmented or under-resourced IT environment carries significant risk.

Short-term savings achieved at the expense of security and resilience can create long-term consequences far greater than the dollars preserved.

Start with a clear view of where you stand

Before institutions can grow, they must understand where they are. That begins with a clear-eyed assessment of how resources are currently allocated. Leaders need visibility into where investments are going, and whether those investments are advancing institutional priorities or simply sustaining the status quo.

In our work with partners, we conduct IT and institutional health assessments as part of the discovery process. These assessments provide a comprehensive view of technology infrastructure, operational processes, and investment priorities to ensure recommendations align with each institution’s goals and desired outcomes.

Through this exercise, we often see institutions investing significant resources in outdated technologies, duplicative systems, and manual processes that no longer support their strategic direction. In some cases, they are throwing good money into bad infrastructure — continuing to fund tools and workflows that limit agility instead of enabling it.

Without that clarity, cost-cutting becomes reactive and misdirected, trimming visible expenses while inefficient systems continue draining resources behind the scenes. Sustainable growth requires more than reduction. Leaders must know what drives revenue, what protects it, and what erodes it. From there, you can streamline with precision, modernize with purpose, and reinvest where it matters most.

Shifting from stabilization to sustainable growth

Once you understand where you stand, the next step is a deliberate commitment to change.

Cost control is certainly part of the equation, but it is not the full solution. Streamlining inefficiencies and modernizing outdated systems are important steps. They are not, on their own, a growth strategy.

The real shift happens when leaders stop asking, “Where can we cut?” and start asking, “What will move us forward?”

That means:

• Bringing the right programs to market based on demand
• Using data to strengthen enrollment and retention strategy
• Aligning technology with the student experience
• Protecting and expanding revenue engines
• Leveraging automation and integration to scale impact

Growth does not happen by default. It happens when institutions intentionally build the capabilities that drive momentum across the student lifecycle.

Leadership will define what comes next

Committing to change requires decisive leadership.

Higher education is navigating structural shifts, not temporary disruption, and stability will not simply return with time. Leaders must move beyond preserving the status quo and instead shape what comes next for their institutions.

That means challenging long-held assumptions, prioritizing investments that strengthen enrollment and retention, and acting with urgency in an environment defined by constant evolution. There is no final steady state ahead. The institutions that succeed will be those that build agility into their strategy, infrastructure, and culture.

Growth does not happen by chance. It is the result of sustained investment, modern capabilities, and leaders willing to move before circumstances force their hand.

You cannot cut your way to growth. But you can build your way toward it.

Institutions are collecting more student data than ever, but more data doesn’t mean more enrollments. Action does. The institutions pulling ahead are using AI, behavioral signals, and predictive insight to cut through the noise, recognize student intent, and engage prospects with the relevance the market demands.

Building a Predictive Enrollment Engine:
Using Student Signals, Data & AI to Improve Matriculation
Thursday, March 26
1:00 pm ET / 12:00 pm CT 

What you’ll learn 

In this webinar, you’ll explore how institutions can use predictive data and AI to identify student intent and personalize engagement, sharpen recruitment strategy, and move prospective learners from inquiry to enrollment with more confidence and control.

Key topics include:

• The “Student Digital Twin” Model: How institutions can create a dynamic, evolving profile of each prospective student to understand behavior, preferences, and intent
• Shifting From Data Collection to Data Activation: Strategies for transforming institutional data into real-time enrollment actions
• Behavior-Based Engagement: How specific student activities can trigger personalized outreach across marketing, enrollment, and student experience teams
• AI-Powered Enrollment Intelligence: Using predictive insights to prioritize high-intent prospects and optimize engagement strategies

Expert speakers

Join Collegis leaders Ashley Nicklay and Chris Greene as they share insights from their work helping institutions activate enrollment and student experience data to drive smarter engagement, stronger conversion, and better outcomes across the student lifecycle.

Who should attend

This webinar is designed for higher education leaders responsible for enrollment growth and student engagement, including:

• Provosts and senior-level enrollment leaders
• Admissions and retention team leaders
• Marketing and digital strategy leaders
• Institutional leaders focused on data-driven decision making

Complete the form on the top right to reserve your spot. We look forward to seeing you on Thursday, March 26.