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Instructional DesignState University System

AI-Powered Instructional Design Across Every Campus

ibl.ai unifies instructional design workflows across your entire state university system — from course development to accessibility compliance — with AI agents your institution owns and controls.

The Problem

State university systems face a persistent challenge: instructional design teams on different campuses operate in silos, producing inconsistent course quality and duplicating effort across the system.

Faculty support is reactive and unscalable. Designers spend hours on manual LMS tasks, accessibility audits, and content updates instead of strategic course improvement.

With no shared AI infrastructure, each campus reinvents the wheel. ibl.ai provides a unified, compliant AI operating system that standardizes excellence without sacrificing campus autonomy.

Cross-Campus Data Silos

Course templates, accessibility records, and assessment data live in disconnected systems across campuses, making system-wide quality assurance nearly impossible.

73% of multi-campus systems report inconsistent course quality across institutions

Manual LMS Administration

Instructional designers spend up to 40% of their time on repetitive LMS tasks — course shells, enrollment configurations, and content migrations — instead of design work.

Up to 40% of ID time lost to manual LMS tasks

Accessibility Compliance Gaps

Meeting ADA and WCAG standards across hundreds of courses is labor-intensive. Manual audits miss issues and create legal exposure for the entire system.

Only 30% of higher ed courses fully meet WCAG 2.1 AA standards

Inconsistent Faculty Support

Faculty at smaller campuses receive far less instructional design support than those at flagship institutions, creating unequal course quality across the system.

Smaller campuses average 1 ID per 200+ faculty vs. 1 per 50 at flagships

Slow Content Development Cycles

Building and updating course content manually slows time-to-launch and leaves outdated materials in active courses longer than acceptable.

Average new course development takes 6–9 months without AI assistance

AI Capabilities

AI-Assisted Course Design

Agentic Content generates course outlines, learning objectives, module content, and assessments aligned to institutional standards — reducing design time by up to 60%.

Automated Accessibility Auditing

AI agents continuously scan LMS content for ADA and WCAG compliance issues, flag violations, and suggest remediation — keeping every campus audit-ready.

System-Wide LMS Standardization

Agentic LMS enforces consistent course templates, navigation structures, and quality rubrics across all campuses while integrating with Canvas, Blackboard, and more.

AI Faculty Support Agents

Purpose-built MentorAI agents provide 24/7 faculty guidance on course design best practices, LMS usage, and instructional strategies — scaling your ID team's reach.

Intelligent Assessment Design

AI agents generate aligned assessments, rubrics, and question banks mapped to learning outcomes — ensuring consistency and rigor across departments and campuses.

AI Video Production for Instruction

Agentic Video enables instructional designers to produce, caption, and analyze instructional videos at scale — with auto-transcription and accessibility built in.

Implementation Timeline

1

Discovery & System Audit

2–3 weeks

Map existing LMS environments, content repositories, accessibility gaps, and ID workflows across all campuses to establish a system-wide baseline.

  • Cross-campus LMS integration inventory
  • Accessibility compliance gap report
  • ID workflow analysis and bottleneck map
  • Data governance and FERPA compliance review
2

AI Agent Configuration & Integration

3–4 weeks

Deploy and configure Agentic LMS, Agentic Content, and MentorAI agents on your infrastructure, integrated with existing SIS and LMS platforms.

  • Agentic LMS connected to Canvas/Blackboard instances
  • Agentic Content configured with institutional style guides
  • MentorAI faculty support agent deployed
  • SSO and Banner/PeopleSoft integration complete
3

Pilot & Standardization

4–5 weeks

Run a pilot across 2–3 campuses, validate AI-generated content quality, refine accessibility workflows, and establish system-wide course design standards.

  • Pilot course designs reviewed and approved
  • System-wide course quality rubric deployed
  • Accessibility audit automation live
  • Faculty support agent usage report
4

System-Wide Rollout & Optimization

3–4 weeks

Scale AI agents to all campuses, train instructional design staff, and establish continuous improvement loops using analytics and outcome data.

  • Full system deployment across all campuses
  • ID staff training and certification complete
  • Analytics dashboard for system-wide course quality
  • Ongoing AI agent optimization schedule

Expected Outcomes

-65%
Course Development Time
6–9 months average2–3 months average
+207%
Accessibility Compliance Rate
30% of courses fully compliant92% of courses fully compliant
+96%
Faculty Support Tickets Resolved
48-hour average response timeUnder 2-hour average response time
+42%
ID Team Capacity for Strategic Work
~60% time on administrative tasks~85% time on strategic design work

Before & After AI

Before

Designers manually build course shells, write objectives, and source content — taking weeks per course with no shared templates.

After

AI agents generate aligned course structures, objectives, and draft content in hours, using system-approved templates and standards.

Before

Periodic manual audits catch issues late, creating remediation backlogs and legal risk across the system.

After

Continuous AI-powered accessibility scanning flags and remediates issues in real time, keeping all campuses compliant.

Before

Faculty wait days for ID support; smaller campuses are chronically under-resourced with no consistent guidance available.

After

MentorAI agents provide instant, 24/7 faculty support on design, LMS use, and pedagogy — equally available on every campus.

Before

Each campus configures LMS differently, creating a fragmented student experience and making system-wide reporting impossible.

After

Agentic LMS enforces shared standards and templates while preserving campus flexibility, enabling system-wide quality reporting.

Before

Faculty create assessments independently with no alignment checks, leading to inconsistent rigor and unmapped learning outcomes.

After

AI agents generate and validate assessments against defined learning outcomes, ensuring rigor and alignment across all courses.

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Frequently Asked Questions

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