Podcast Summary: The Agile Brand with Greg Kihlström®

Episode #843: Pega's Matt Healy on the Hidden Costs of Outdated Technology
Date: April 14, 2026
Guest: Matt Healy, Senior Director, Product Strategy and Marketing at Pega
Host: Greg Kihlström

Episode Overview

In this episode, Greg Kihlström sits down with Matt Healy of Pega to explore the “hidden costs” of outdated technology—particularly legacy systems—and how they undermine enterprise innovation, AI adoption, employee experience, and ultimately, business performance. The conversation revolves around new research from Pega that uncovers powerful links between poor internal technology and employee retention, morale, productivity, and customer experience. Importantly, Matt discusses how AI and modern automation are not just the drivers but also the enablers of rapid transformation, offering a practical roadmap for leaders ready to move past IT “technology debt”.

Key Discussion Points & Insights

1. The New Urgency: Outdated Tech as a Strategic Obstacle

• Legacy Technology as a Drag on Transformation

  • Legacy systems are “not just inefficient, they're actively eroding employee morale, productivity, and could even be a major factor in employee turnover.” (Greg, 00:31)
  • While boards and executives chase AI initiatives, they often overlook that foundational systems are “actively holding people and processes captive.” (Greg, 00:31)
  • The urgency to modernize is higher than ever because AI demands clean, accessible data and flexible platforms.

• AI: Not Just Raising the Bar—Furnishing the Solution

  • "AI now increases some of the urgency where if your data is trapped in on-prem databases... you're just unable to unlock the sort of fuel you need to power AI-driven transformation now." (Matt, 04:05)
  • AI is helping accelerate the actual process of modernizing these systems—what used to take years can now happen in months or even weeks.

2. Employee Experience: Beyond the Tech, It’s a Talent Issue

• It’s Not Just an IT Problem — It’s a Business Risk

  • Over a third of employees say they’d consider leaving their jobs due to poor technology (Greg, 05:40), which compounds recruitment and training costs.
  • Employees “expect banking to be simple, insurance to be simple”—and that expectation now extends to their internal work tools. (Matt, 06:43)

• Notable Quote:

  • “When I come into work and then I log into... a terminal-based mainframe application, that's just completely disconnected from my life outside of work... I think part of that is, you know, some of what we found is around 50% of employees said... the platforms that they're given don't allow them to do their best work.” (Matt, 06:43)

3. Diagnosing and Addressing Tech Pain Points

• Don’t Just Train—Transform

  • Many organizations view outdated tech as a training problem, but Matt calls it a usability and performance problem (08:25).
  • Real modernization isn’t ripping and replacing at once; it’s strategic, phased, and pragmatic.

• Practical Steps for Modernization:

  • Step 1: Gain deep understanding of current state using AI (analyzing source code, user manuals, recordings of workflows) to “just get a sort of analysis: What are the end-to-end processes in here?... Where do things fall apart?” (Matt, 09:24)
  • Step 2: Use AI not just to duplicate—but to rethink and optimize. Instead of simply translating COBOL to Java, use AI to streamline and automate processes.

• Notable Quote:

  • “AI can really help take a lot of those next steps and not just sort of rebuild what you have today into a newer technology... [it lets you] reimagine everything that's being run through it to deploy an optimized process...” (Matt, 10:36)

4. AI Deployment: Starting with the Basics

• Automate Repetitive Tasks for Quick Wins
  • “A lot of the workers... cited rather simple things like automation of repetitive tasks as a key need.” (Greg, 12:31)
  • Matt advises pragmatism: Start with visibility via workforce intelligence tools to measure what’s actually slowing people down (13:08).
  • “It might end up being that AI is the solution... but it’s not the only solution to the problem. So it also is really important to sort of understand the problem at hand and really think through, like, what's the best tool for the job.” (Matt, 13:54)

5. Measuring Impact: Metrics That Matter

• Look for Hidden Costs and Overflow Effects
  • Beyond uptime/support tickets, track:
    • Degree of specialization (Are there “12 different teams” to serve one customer need? That’s complexity worth solving.) (Matt, 15:09)
    • Number of daily apps/switches per employee: Each switch represents time lost, higher training burden, and productivity drag.

6. Building the Business Case for Modernization

• ROI Has Changed Dramatically Thanks to AI
  • “AI has changed both the numerator and the denominator of the ROI calculation.” (Matt, 17:15)
  • Hard costs (maintenance, support) and opportunity costs (innovation, growth, personalization) must both be counted.
  • Striking Example:
    • Old approach: “... cost you, you know, $25 million and the project is going to take seven years.”
    • New approach (with AI): “From COBOL to a working application in the cloud... in 90 days.” (Matt, 17:49–18:57)
  • Memorable Reaction:
    • “That's not even like seven years to seven months. That's seven years to 90 days.” (Greg, 19:17)

7. The Near Future of Work: AI as Partner, Not Obstacle

• Changing Day-to-Day for Employees

  • From convoluted mainframe workflows to intuitive, AI-assisted, conversational interfaces.
  • The role of “knowing every single code you have to pass in” will fade, replaced by guiding AI to get work done (Matt, 19:58).

• Caution on Predictions:

  • “I would be a fool if I made any like, strong predictions of where this is going... I do kind of envision that everyone will have AI assistance... Work will be a lot more of a conversational manner...” (Matt, 19:58)

8. Looking Ahead: The Conversation One Year From Now

• From ‘How Fast Can We Implement AI?’ to ‘How Do We Humanize It?’
  • “Right now the conversation is very much around how quickly can we adopt AI at scale... I think in a year the conversation will shift to how can we provide the human touch, how can we best utilize our people in the moments when our customers need it...” (Matt, 21:54)

Notable Quotes

• On User Experience:
  “Those consumers also work somewhere.” (Matt, 06:25)
• On Transformation:
  “Today, AI can offload a lot of that work and that’s really part of what we’re focused on here, is accelerating the transformation journey by using AI to help you understand your legacy systems, reimagine them and then deploy them as new systems in the cloud.” (Matt, 05:17)
• On ROI:
  “AI has changed both the numerator and the denominator of the ROI calculation.” (Matt, 17:15)
• On the Future:
  “Work will be a lot more of a conversational manner… just engaging through some sort of agent fabric with a ton of AI under the hood which can actually execute on what you’re trying to get done.” (Matt, 19:58)

Key Timestamps

• 00:31 – Problem statement: Legacy tech is undermining employee morale & productivity
• 03:21 – AI’s impact on increasing urgency to modernize legacy systems
• 06:23 – Legacy tech as a critical business risk, not merely IT’s problem
• 09:24 – Using AI to map and transform current processes
• 12:31 – Employees crave automation of repetitive tasks
• 15:09 – Suggested metrics: specialization, app-switching, and process complexity
• 17:15 – How AI has transformed the cost equation for modernization
• 18:57 – Case study: Mainframe to cloud in just 90 days
• 19:58 – The future employee experience: AI as collaborative assistant
• 21:54 – Prediction for next year: The need to ‘add back the human touch’ to AI-driven CX

Closing Notes & Tone

The episode is pragmatic yet optimistic, emphasizing that leaders must not only be bold in adopting AI but courageous in confronting and dismantling legacy systems. Both guest and host deliver actionable advice rooted in new research and real-world case studies, stressing that employee experience and business ROI are inextricably linked to internal technology choices.

Matt Healy’s advice: Start with understanding your current tech stack, don’t assume AI is always the answer, and leverage new AI-driven tools to accelerate transformation holistically.

Central takeaway: Modernization is no longer a years-long, high-risk exercise—AI has re-written the playbook and now, both transformation speed and payoff potential are dramatically higher.