Campus Technology Insider Podcast May 2026
Episode: Connecting Insight to Action in Higher Ed ERP and AI Initiatives
Host: Rhea Kelly, editor in chief, Campus Technology
Guest: Tirumala Rao Chimpiri, senior programmer analyst for enterprise applications & integrations, Stony Brook University
Episode Overview
In this episode, Rhea Kelly and Tirumala Rao Chimpiri talk about CAIP-HE, a platform-agnostic reference framework for connecting insight, decision-making, and execution across enterprise environments.
Key Questions & Takeaways
What problem is the CAIP-HE framework designed to address?
CAIP-HE examines the gap between generating insight, making a decision, and carrying that decision through to coordinated execution across ERP-centered environments.
How should institutions begin applying the framework?
Start small with a few high-impact scenarios where insight already exists but action is delayed, inconsistent, or dependent on manual follow-up. Map where the insight originates, who owns the decision, what workflow carries it forward, which systems are involved, and how accountability is maintained.
Why isn’t adding AI to ERP systems enough?
AI can identify patterns, summarize information, recommend actions, and surface risks, but it does not automatically establish decision ownership, execution processes, or accountability. Connect AI and ERP with governance, workflows, integration, and clear decision ownership.
How should governance evolve in AI-enabled ERP environments?
Make governance more "flow aware," with clear decision rights, escalation paths, transparency, and human oversight so institutions know who can act, when human review is required, and who is accountable.
What should institutions avoid when modernizing ERP or adopting AI?
Don't treat analytics, automation, integration, AI, and personalization as isolated projects or assume better insights automatically produce better action. Measure success by whether modernization improves decisions, reduces manual workarounds, strengthens coordination, and creates more reliable execution.
Topic Index
00:00 Welcome and Guest Intro
00:30 Tirumala Background and Motivation
02:23 What CAIP-HE Means
05:38 The Insight to Action Gap
07:06 How to Apply CAIP-HE
08:58 Why AI Alone Is Not Enough
10:44 Governance and Decision Rights
12:34 Common Modernization Mistakes
14:22 Key Takeaways for CIOs
15:54 Closing and Where to Listen
Transcript
Rhea Kelly 00:08
Hello and welcome to the Campus Technology Insider podcast. I'm Rhea Kelly, editor in chief of Campus Technology, and your host. And I'm here with Tirumala Chimpiri from Stony Brook University, to talk about a new framework for examining how insight, decision-making, and execution connect across ERP environments.
Tirumala, welcome to the podcast. Let's start, could you just start by telling us a little bit about yourself and your background?
Tirumala Rao Chimpiri 00:35
Sure. Thank you for having me, Rhea. I'm Tirumala Rao Chimpiri. I work in enterprise applications and integrations at Stony Brook University. My broader professional work has focused on ERP modernization, enterprise systems integration, automation, and digital transformation. I have over like 26 years of IT experience, most have been to ERP environments across human resource management, financials, and enterprise performance. My experience has also crossed several industries, including higher education, public health, banking and financial services, manufacturing, HR services, telecommunications, and transportation and logistics. Across those environments, one pattern become very clear to me: Organizations often invest heavily in enterprise platforms, analytics, automation, and integrations, now recently AI capabilities as well. But even when they have strong systems and useful insights, they can still struggle to translate those insights into timely decisions and coordinated execution. That recurring pattern is what led to me develop the CAIP-HE reference framework, which can we talk later in detail. At very high level, my work focuses on how organizations connect inside decision-making and execution across complex ERP-centered environments.
Rhea Kelly 02:23
So, can you walk me through what exactly is the CAIP-HE framework, and like what does it encompass?
Tirumala Rao Chimpiri 02:30
Yes, absolutely. At very high level, CAIP-HE is a platform-agnostic reference framework I developed to help leaders think about how intelligence should move across ERP-centered enterprise environments. So the name stands for four interdependent dimensions: cognitive automation, advanced analytics, integration, and interoperability. And the last one is personalization. The basic idea is that most organizations already have many of these capabilities. They have ERP platforms, analytical tools, dashboards, automation, integration, and user-facing experiences. But these capabilities often operate separately, I mean, siloed. Analytics may generate insight. Automation may improve one workflow. Integration may move data between systems. And personalization may tailor information to a particular user. The problem is that if those pieces are not connected as a system, the organization may still struggle to move from insight to decision to execution. So the framework asks a structural question: Are these capabilities working together in a way that helps the organization turn intelligence into coordinated action? It is also important to say what CAIP-HE is not. It is not a product. It is not a soft, software platform, and it's not a implementation methodology. Organizations do not install CAIP-HE. They use it as a leadership lens or evaluative framework to assess ERP modernization, AI initiatives, governance, operating models, and decision flow. For higher education CIOs, this is especially relevant because campuses are complex enterprise environments. A single issue may touch student systems, finance, HR, CRM, learning platforms, and advising. CAIP-HE gives leaders a shared language to ask where does insight originate, who owns the decision, how does that decision move into execution, and where are we still relying on manual coordination or informal workarounds.
Rhea Kelly 05:25
So you were trying to solve kind of a gap between the insights that are arising in, in data and being able to translate that into decision-making. Is that, is that right?
Tirumala Rao Chimpiri 05:36
Yes, that is correct.
Rhea Kelly 05:38
So can you give a practical example of how that gap kind of shows up in higher education. What, what does it look like?
Tirumala Rao Chimpiri 05:47
So that's a great question, right? The main problem is the gap between knowing something and acting on it. So across industries, organizations have invested heavily in ERP platform, analytics, automation, and now, you know, AI capabilities, but many still struggle with a very practical question: Once insight appears, how does it become a decision, and how does that decision become coordinated execution? That is the problem CAIP-HE is designed to examine. In higher education, the gap can appear in areas like student success, finance, operation, workforce planning, compliance, and institutional planning. A signal may appear in one system, but the decision and execution may depend on several teams, workflows, and governance structures. If those steps are unclear, the institution may have strong analytics but struggle with execution. So the framework help lead us to ask a practical question: Are we only generating more insight, or are we improving how the institution act, acts on that insight?
Rhea Kelly 07:06
How do you recommend that institutions sort of set out to apply the framework?
Tirumala Rao Chimpiri 07:13
So I would suggest starting as small and practical. Institutions do not need to begin with an enterprise-wide redesign. A good starting point is to identify a few high-impact scenarios where insight already exists, but action is delayed, inconsistent, or too much depending on manual follow-up. For example, pick a student successful, success scenario, a finance operation scenario, or workforce planning scenario. Then map it from the beginning to end. The questions I would ask are: Where does the insight originate? Who receives it? Who owns the decision? What workflow carries the decision forward? Which systems need to be connected? How is accountability maintained? Once leaders map that flow, the gaps usually become very easily visible. The solution may not require a new system. Sometimes it may involve clarifying ownership, improving integration, fixing a workflow, or sometimes, you know, strengthening the governance. So the practical value is that the CAIP framework helps institutions move from a broad technology conversation to a specific operational conversation.
Rhea Kelly 08:46
So, especially right now, I think there's a lot of talk about how AI can help sort of streamline decision-making. It can help gather or, you know, integrate insights from a lot of different sources. So, how is this framework different from just adding AI tools, for example, into ERP or student systems?
Tirumala Rao Chimpiri 09:07
That's an important distinction. AI is important, but AI by itself does not solve the decision flow problem. So AI can improve how institutions generate insight. It can identify patterns easier, summarize information, recommend action, or surface risk. But it does not automatically define who owns the decision, how the decision should be executed, or how accountability should be maintained. In some cases, AI actually makes the gap more visible. Institutions may suddenly have more signals, more alerts, and more recommendations. But if there is no structure for acting on them, the organization can become overwhelming. This is why I think institutions need to think about AI and ERP together with governance workflow integration and decision ownership. The question is not just can AI generate a better insight. The bigger question is can the institution act on that insight in a clear, timely and accountable way. So that is where the CAIP-HE fits in. It helps leaders to evaluate whether AI-enabled insight is connected to institutional action.
Rhea Kelly 10:33
That's so interesting. So it really just, it comes down ultimately to the people making the decisions. So yeah, that brings up governance, of course. So can you talk more about how, like, do institutions need to be re-evaluating their governance processes, you know, in light of these, these gaps that that you're seeing?
Tirumala Rao Chimpiri 10:58
Yeah. So I feel like, you know, governance is the central to this because in many institutions governance is often thought of as approval, oversight, or compliance. Those are important, but AI-enabled ERP environments governance is also needs to be connected to how decision actually moves through the institution. For example, if an analytics tool identifies a student at risk, so the questions, right, ask, who has the authority to act if an automated workflow recommends an intervention? When does a human review it? Or if a financial signal triggers a response, who is accountable for the decision and the, how to follow through? So governance should help answer those questions before problems occur, not only after something goes wrong. I think governance needs to be become more flow aware. It should clearly decision rights, escalation paths, transparency, and a human oversight. This is especially important in higher education because decisions can affect student access, student success, financial outcome, compliance, and equity. So institution needs to move faster, but they also need to maintain trust and accountability.
Rhea Kelly 12:34
What mistakes do institutions often make when they're modernizing ERP or adopting AI?
Tirumala Rao Chimpiri 12:42
One mistake I see often is treating each capability as a separate project. For example, analytics become one initiative, automation becomes another, integration becomes another, AI becomes another, right? And also personalization becomes another. Each may deliver value locally, but the institution may still struggle if those efforts are not connected. Another mistake is assuming that better insight automatically leads to better action. In reality, insight has to travel through people, process, systems, and governance structures. A third mistake is focusing too much on go live or tool deployment and not enough on what happens afterward. The question should not only be did we implement the system, rather it should be: Are we making better decisions, reducing manual workarounds, improving coordination, and creating more reliable execution? That's why I keep coming back to the phrase "insight to decision to execution." So, in that flow, if the flow is not clear, modernization can fall short even when the technology itself is strong.
Rhea Kelly 14:08
In a way, it sounds like closing that gap between the insights and the execution is, is really a way of better ensuring ROI on these massive investments.
Tirumala Rao Chimpiri 14:19
Yeah, that is correct.
Rhea Kelly 14:22
So, what, what would you say that CIOs or institutional leaders should remember from our conversation here and the framework in general?
Tirumala Rao Chimpiri 14:32
So, the main thing I would want CIOs and institutional leaders to remember is that more intelligence does not automatically create better outcomes. AI analytics, ERP modernization, and automation all matter, but their value depending, depends on whether they are connected to decision-making, workflow governance, and execution. CAIP-HE is meant to help leaders to examine that connection. It encourages institutions to look at cognitive automation, advanced analytics, integration, and interoperability, and personalization as connected capabilities rather than separate efforts. For higher education CIOs, the opportunity is to move beyond systems of record and towards systems that help people understand, decide, and act more effectively. So that is the future I think institutions should work towards: not just more data, not just more AI, but clear decision pathways and more accountable execution.
Rhea Kelly 15:46
I really like that: not just more data or more AI, but actual decisions that make a difference.
Tirumala Rao Chimpiri 15:53
Yeah, that's correct.
Rhea Kelly 15:54
Well, thank you so much. Thank you for coming on.
Tirumala Rao Chimpiri 15:57
Yeah, thank you, Rhea, for having me.
Rhea Kelly 16:02
Thank you for joining us. I'm Rhea Kelly, and this was the Campus Technology Insider podcast. You can find us on the major podcast platforms or visit us online at campustechnology.com/podcast. Let us know what you think of this episode and what you'd like to hear in the future. Until next time.