Key ideas from the conversation include:
- Technology alignment is ultimately a governance issue. When systems introduce operational friction or financial unpredictability, the impact extends beyond IT into institutional performance, leadership oversight, and board accountability.
- Pricing models determine where risk resides. Consumption-based pricing structures can shift financial uncertainty to institutions, influencing how and whether mission-aligned work scales.
- AI works best when it is architectural, not simply layered on top. Layering intelligence onto fragmented systems does not resolve structural inefficiency. Integration at the architectural level matters more than surface features.
- Institutional complexity is not a flaw to simplify away. Retention, enrollment, and student success are ecosystem outcomes influenced by policy, culture, funding, and people. Technology should support that complexity rather than attempt to simplify it away.
Why We Built Canyon GBS: Fixing the Friction in Higher Education Technology
After decades of leading technology inside colleges and universities, our founder and CEO, Joseph Licata, had seen how institutional systems functioned under pressure. He had negotiated seven-figure vendor contracts, managed enterprise deployments, and sat in cabinet meetings explaining cybersecurity risk to presidents.
Over time, what stood out most was what Joe describes as “accumulated friction.” He saw enrollment teams running exports every weekend to build call lists out of their Customer Relationship Management (CRM). He saw advisors sitting with a student while twelve browser tabs remained open during a single session. He saw IT departments running millions of batch jobs just to keep systems integrated. At the same time, vendor case studies claimed retention gains as if they were product features, even though countless faculty and staff worked tirelessly using many tools to produce those outcomes.
After enough renewal cycles in which prices rose faster than innovation, Joe began asking why institutions were doing so much work to keep systems functioning at all.
The issue was alignment. When institutions absorb integration burden, pricing risk, and workflow inefficiency simply to maintain core operations, the problem is structural. For leaders responsible for governance, budgets, and institutional performance, that distinction is strategic.
Higher Education Technology Strategy: Enterprise Suites vs. Point Solutions
When institutions try to address this friction, they often encounter the same structural choice in the market. On one side is the large enterprise suite. These systems serve multiple departments and often multiple industries. They are expensive, complex, and intentionally generic. Out of the box, it doesn’t really do anything for you. It needs to be heavily customized to meet an institution’s unique needs. Customization requires time, consulting support, and sustained internal coordination across governance structures that are rarely simple.
On the other side are narrowly focused point solutions. Each may solve a specific problem, but institutions are left to stitch them all together to try to make something that works. What begins as targeted optimization becomes operational exhaustion. Every additional integration introduces data synchronization risk, additional security review, and another contract cycle to manage.
Neither option fully addresses the structural reality of higher education. Enterprise platforms often require institutions to adapt to the software. Point solutions require institutions to act as system integrators. When staff spend time compensating for gaps between systems, that time inevitably shifts away from students and strategic priorities.
As Joe describes it, institutions “don’t have a good option for a purpose-built enterprise solution that does the things they need to do.” Leaders evaluating technology investments must look beyond feature breadth and consider whether the architecture reduces complexity or institutionalizes it.
“We didn’t layer features. We rebuilt workflows. We didn’t add modules. We redesigned motion,” Joe says.
Technology Pricing Models and Institutional Risk in Higher Education
Shared governance, board oversight, accreditation reviews, and fixed fiscal cycles define the operating environment for institutional leaders. Financial exposure has to withstand scrutiny, budgets are set in advance, and renewals are expected to be clearly justified.
“Colleges and universities operate on mission and accountability. Vendors operate on growth targets and exceeding shareholder expectations,” Joe says.
Per-user, per-message, per-token, and modular pricing structures tie revenue to consumption. From a vendor’s perspective, that aligns growth with usage. Institutions budget on planned allocations, not open-ended consumption curves. In practice, that can make it difficult for leaders to predict what next year’s technology costs will actually look like.
When next year’s cost depends on how much a system is used, financial uncertainty shifts to the campus. For institutions operating within fixed budgets and governance cycles, that uncertainty can complicate long-term planning.
Joe notes that institutions should never find themselves limiting student outreach because increased engagement drives up cost. When pricing models discourage mission-aligned activity, they influence institutional behavior.
Incentive structures built into contracts often determine where financial risk ultimately lands. Technology strategy must account for whether the economics support the mission leaders are responsible for protecting.
AI in Higher Education: Architecture, Integration, and Long-Term Impact
Artificial intelligence has quickly entered higher education, and many leaders are now being asked to evaluate AI capabilities across their technology stacks. “Every edtech player in the market existed before AI was where it is today,” Joe says. “So every single one of them had to take the approach of bolting AI onto a legacy system.”
He notes that nearly every major vendor serving this market existed before AI reached its current maturity. It often becomes “decorative, more than it is functional.” If staff still have to navigate multiple systems and reconcile disconnected data, the underlying friction remains.
Joe is clear about what needs to change. “AI shouldn’t sit on top of your system. It really should power it more quietly.” When artificial intelligence is embedded within architecture, it becomes part of the workflow rather than an overlay.
Higher education outcomes are not features. As Joe puts it, “Student retention isn’t a button. Enrollment isn’t a feature.”
For institutional leaders, the evaluation standard should not be whether AI is present. It should be whether AI is structurally integrated in a way that reduces complexity and respects governance realities, supported by a phased AI governance framework.
Purpose-Built Technology for Higher Education Institutions
Higher education is complex by design. Shared governance, policy nuance, compliance requirements, and local context shape how decisions are made and how work gets done. That complexity shows up in daily operations.
Spreadsheet culture. Endless tab switching. Artificial user caps. Workflows that feel as though they are working against the people responsible for serving students. Joe describes wanting to eliminate “the quiet frustrations of the systems you use that feel like they’re working against you.”
Purpose-built design begins with institutional realities rather than abstract market categories. It accounts for shared governance and compliance requirements.
Security and compliance sit at the center of institutions’ responsibility. Colleges hold financial aid data, health documentation, and academic records at enormous scale. “Security and compliance aren’t marketing bullets. They’re a responsibility,” Joe says, one that requires adherence to enterprise-grade security and compliance standards, including ISO 27001-certified and SOC 2-compliant infrastructure designed to protect institutional data.
Affordability follows the same logic. For Joe, it was non-negotiable. Not as a pricing strategy, but as a design principle. Institutional access to capable infrastructure should not depend on whether a campus can absorb escalating cost structures or maintain large integration teams.
Institutions succeed because of their people. Technology should remove friction, stabilize operations, and respect the complexity of the environment it serves. When it does, leadership attention can return to what matters most: advancing student success within the constraints that define higher education.
Restoring Alignment Between Mission and Technology
“Higher education is really filled with extraordinary people working under unbelievable constraints,” Joe says.
Technology cannot resolve those pressures on its own. When systems fragment workflows or shift financial risk, institutions absorb the burden. Over time, incentives drift from the institutional mission.
Joe describes the problem plainly: “Incentives drifted away from your college’s mission.”
Restoring alignment means evaluating how systems behave within institutional constraints, not simply what they promise. Institutions succeed because of their people. Technology should function as infrastructure that quietly supports their work. Alignment is a condition for sustainable performance.
