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Industry - Higher Education

Building the Intelligent Campus: AI, Data, and the Future of Higher Education

How AI-driven decision-making and integrated data are separating thriving campuses from those at risk of collapse.
Michael Mathews

Guest Speaker:

Mike Mathews

VP for Innovation and Technology,
Oral Roberts University

Ratnakar Nanavaty

Host:

Ratnakar Nanavaty

Chief Strategist,
Astute Business Solutions

Episode 02

Guest Speaker

Anup Ojah
Anup Ojah

Global HPC & AI - Leader, Cloud Engineering, Oracle

About Host

Ratnakar Nanavaty is a seasoned technology leader and the host of The AI-Driven Enterprise from Astute.

With a strong track record in AI, ERP, and digital transformation, he has worked closely with higher education institutions and enterprise leaders to modernize legacy systems, streamline operations, and unlock the real value of data. His experience spans cloud ERP migrations, AI-enabled process optimization, and data-driven decision making, with a particular focus on how institutions can reimagine student, faculty, and administrative experiences through intelligent automation.

Ratnakar’s work sits at the intersection of AI innovation and practical execution — helping organizations move beyond theory and hype to implement solutions that are adoptable, sustainable, and outcome-focused.

Through The AI-Driven Enterprise, he brings together CIOs, transformation leaders, and industry experts for grounded, experience-led conversations on how AI is reshaping modern enterprises and higher education — focusing on what truly works in production, at scale.

Higher education is at an inflection point. With hundreds of campuses closing or merging over the past decade, institutions can no longer afford slow decisions, fragmented data, or technology that looks impressive but delivers little impact. In this episode, Mike Mathews—Vice President for Innovation and CIO at Oral Roberts University—shares how AI has become a practical, operational force rather than a theoretical experiment.

Mike explains why AI adoption is no longer driven by IT teams alone, but by boards of trustees, CFOs, and presidents who see the urgency to act. From faculty rapidly embracing intuitive AI tools to administrators using “AskData” to get real-time answers without waiting weeks for reports, this conversation reveals how ORU has turned data into a strategic asset.

The discussion also challenges common fears about AI replacing people. Instead, Mike reframes AI as augmented intelligence—a force that enhances human judgment, removes bias, accelerates insight, and frees leaders to focus on relationships and outcomes that truly matter to students and institutions alike.

Top 10 Highlights / Takeaways

  • AI adoption in higher education is now driven by boards and executive leadership, not just IT teams.
  • Institutions that fail to integrate siloed data risk making slower, poorer decisions.
  • Faculty adoption of AI has been faster than any technology in the past 25 years.
  • AI succeeds because it is intuitive—faculty and staff can “speak” to it naturally.
  • AI will not replace people, but people who use AI will replace those who don’t.
  • “AskData” enables leaders to query enrollment, finance, and performance data in real time.
  • Data—not opinions—should guide institutional decision-making.
  • AI dramatically reduces the time needed for reporting, analysis, and benchmarking.
  • Operational AI matters more than “cool” AI demos that don’t improve outcomes.
  • The next wave of campus closures will largely affect institutions that ignored AI’s warning signs.

The Intelligent Campus: Why AI Is Now a Survival Skill for Higher Education

Higher education is facing a reality check. Over the past decade, hundreds of colleges and universities have closed, merged, or declared bankruptcy. Enrollment pressures, rising costs, and outdated systems have pushed institutions to the brink. According to Mike Mathews, Vice President for Innovation and CIO at Oral Roberts University (ORU), AI has arrived at exactly the right—and necessary—moment.

In a recent podcast conversation, Mike shared why AI is no longer an optional experiment but a critical capability for institutions that want to survive and thrive.

From Theory to Execution

For years, AI in higher education was discussed in abstract terms. Conferences were filled with panels about “what AI could do someday.” That era is over. As Mike explains, institutions are now expected to execute, not speculate.

Boards of trustees—many of whom run banks, manufacturing firms, and technology-driven companies—are asking direct questions: How are we using AI? Where is it improving outcomes? The pressure is unavoidable. Institutions that fail to respond are falling behind fast.

Why Faculty Adoption Is Different This Time

Unlike past technologies that required extensive training and resistance management, AI has been embraced rapidly by faculty. Mike points out something unique: AI speaks the same language as educators. It responds conversationally, understands context, and adapts to disciplines naturally.

This intuitive interaction removes friction. Faculty no longer need to learn complex systems or workflows. They simply ask questions, test ideas, and see immediate value—making AI the fastest-adopted technology Mike has seen in over 25 years.

Data Silos Are the Real Threat

One of the most powerful insights from the conversation centers on data integration. Many campuses still operate with disconnected systems—student information, finance, housing, dining, learning platforms—all speaking different languages.

ORU addressed this challenge years ago, enabling leaders to correlate seemingly unrelated data points, such as student behavior and academic success. According to Mike, institutions that fail to fix data silos now may create a far bigger mess once AI is layered on top.

Data is the fuel for intelligent campuses. Without clean, connected data, AI cannot deliver meaningful insight.

AI as Augmented Intelligence

A recurring myth around AI is job replacement. Mike reframes this fear clearly: AI does not replace people—people who use AI replace those who don’t.

Rather than removing human judgment, AI enhances it. It strips away emotional bias, accelerates analysis, and provides evidence-based insight. Leaders can then focus on relationships, strategy, and mission-driven outcomes.

This is why Mike prefers the term augmented intelligence. AI amplifies human capability rather than diminishing it.

Ask the Data, Not the Opinions

One of the most compelling use cases discussed is the concept of “AskData.” Instead of waiting weeks for reports from institutional research or IT teams, leaders can ask direct questions:

  • What is enrollment today?
  • How does it break down by gender or geography?
  • Which programs are trending up or down?

AI enables real-time answers with visual clarity. This shift changes how decisions are made—faster, more accurate, and less influenced by internal politics or assumptions.

Operational AI Beats ‘Cool’ AI

Mike issues a clear warning: looking cool with AI is easy. Making a meaningful difference is hard.

Digital twins, dashboards, and demos mean little if they don’t improve student success, reduce administrative costs, or enable smarter decisions. ORU’s long-term growth, Mike argues, has been driven by operational AI—tools that quietly but consistently improve outcomes behind the scenes.

What Comes Next

Looking ahead, Mike predicts a shakeout in higher education. Institutions that ignore AI will struggle. Vendors that sell systems without intelligence will lose relevance. The future belongs to organizations that deliver insight and outcomes—not just software.

The intelligent campus isn’t a futuristic vision anymore. It’s a present-day requirement. And for leaders willing to embrace it, this may be one of the most exciting eras in the history of higher education.

Episode Number: 02

13:14

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Top 10 Podcast Highlights / Takeaways

1. AI success starts with a leadership mindset, not technical expertise.

Executives don’t need to “speak AI”—they need to think AI-first.

2. Most enterprises are overwhelmed by AI noise.

Clear frameworks help cut through hype from hyperscalers and vendors.

3. AI should always be tied to ROI.

If it doesn’t solve a business problem, it’s just a shiny object.

4. A six-agent framework simplifies AI adoption.

Business tasks, conversational, research, analytics, domain-specific, and developer agents cover most use cases.

5. Trusted data is the foundation of effective AI agents.

Especially for deep research and analytics-driven insights.

6. AI-driven strategy days are becoming common.

Enterprises want focused sessions to understand AI strategy, demos, and next steps.

7. Live demos accelerate understanding and buy-in.

Seeing agents in action sparks practical ideas across finance, operations, and customer support.

8. Most organizations are early or mid-journey.

Very few are truly mature in agentic AI adoption.

9. The AI skills gap is real—and growing.

Self-learning, partner ecosystems, and internal AI councils are key solutions.

10. BI tools, as we know them, may fade away.

AI-driven, self-service analytics will soon be available to every business user.