Artificial Intelligence Podcast: "Is AI Going to Take Over For Outsourcing?"

Host: Jonathan Green
Guest: Thomas Daugherty (AI/outsourcing expert)
Release Date: December 15, 2025

Episode Overview

This episode delves into the evolving relationship between Artificial Intelligence (AI) and traditional outsourcing, particularly for small and medium-sized businesses. Jonathan Green welcomes Thomas Daugherty to explore whether AI is set to replace global outsourcing, what practical impacts this shift is already having, and how businesses can best leverage AI—without losing sight of workflow nuance, company morale, or the real needs that drive change. The discussion remains practical and candid, drawing on real experiences with process automation, change management, and the value of hybrid (human + AI) models.

Key Discussion Points & Insights

1. The Evolution of Outsourcing and AI's Role

[01:01 – 02:59]

• Jonathan observes a shift in perception—mistakes in social posts once blamed on virtual assistants (VAs) are now attributed to AI.

• He proposes that AI is a "great equalizer," letting non-native English speakers compete on better footing.

• Thomas shares trends in global outsourcing: movement from traditional locations (India, Philippines) to new frontiers like Africa, enabled by affordable labor and agentic AI that can, for example, remove accents or process tasks more efficiently.

• The core of outsourcing remains business process optimization, but AI now automates those steps.

  "The basis of outsourcing really is to get to business process outsourcing. So how do you get to the main source of the process and then let the AI roll through that? That's all the AI is doing—it's just going through process step by step. Where it gets curveballs is the nuance."
  — Thomas Daugherty [02:27]

2. The Critical Importance of Process Clarity

[04:05 – 08:22]

• Success with AI (or outsourcing) hinges on well-defined, mapped-out processes.

• Failures often stem from neglecting this groundwork, skipping over documentation, or not clarifying measurements for success.

• Both hosts share experiences where clients or managers lack clear KPIs or overload on metrics (100+!), which causes confusion and inefficiency.

  “If you know what it is and you can show me an example of good and bad input and output, then I can build that. But we sometimes assume that because we're hiring, it goes back and forth. We're hiring an AI, so it's smart, it'll figure out. Or we're hiring a human, they're smart to figure out. But it's really hard to work a job if you don't know the measurement of success."
  — Jonathan Green [05:45]

  "I've had clients that have had over 100 metrics. To me, that's just too much. Right. So we try to dial it back. In my experience, there's usually eight to 12 metrics that really drive the success of that particular group."
  — Thomas Daugherty [07:39]

3. Human-AI Competition—or Collaboration?

[08:22 – 09:53]

• Jonathan questions whether AI is a true competitor to outsourcing, or if outsourcers will simply adopt and adapt to AI the fastest.

• There's a recognition that both models face similar labor-driven inflection points, and those who pretend AI isn’t happening “get left behind.”

  “I feel like outsourcers, people in other countries, have the most incentive to become AI masters the fastest.”
  — Jonathan Green [09:39]

  "The outsourcers will become the agentic AI. They'll build the tools and build the models for these folks to plug in and use for their organizations."
  — Thomas Daugherty [09:56]

4. AI Implementation Failures: Change Management & Sabotage

[12:18 – 15:50]

• Jonathan and Thomas discuss real-life project failures caused by poor user onboarding, lack of pilot programs, and top-down decisions made without ground-level insight.

• There's a vivid anecdote about a botched weekend systems upgrade with no user testing, causing client fury.

  "If you try to onboard a new AI or agentic AI and you have all kinds of issues with it within the first couple of weeks, what are you going to do? You're going to bail."
  — Thomas Daugherty [10:21]

  "There's nothing worse. They make a change and then tech support's not there on the weekend... To me, the best thing about outsourcing is you could have 24/7 tech support."
  — Jonathan Green [12:20]

  • They also address fears about “training your replacement” (i.e., AI taking over jobs), which leads to active or passive sabotage as team morale collapses.

5. AI Tool Selection, Adoption, and Overhyped Solutions

[15:50 – 22:44]

• Many firms don’t see ROI on AI investment (cited as high as 95%) due to skipping pilots, poor training, or buying based on hype instead of needs.

• Jonathan underscores the necessity of aligning any new tool with existing workflows and assessing whether the magnitude of change is worth the payoff.

  "We have to be strategic with what moves we make. Because you also have to factor in the emotion of the team or the positivity—morale. If you input these projects, especially with language like, we're going to outsource you, everyone's getting replaced with AI—and I've killed morale."
  — Jonathan Green [16:50]

6. The Mirage of Out-of-the-Box Solutions & Feature Overload

[22:44 – 26:00]

• Both agree that “one size fits all” solutions rarely work; successful AI/outsourcing projects are built with partnership, client involvement, and by automating low-touch, repetitive tasks.

• Jonathan and Thomas critique unnecessary feature bloat in AI tools, and onboarding that is either too extensive (long, boring tutorials) or nonexistent.

  "People buy an out of the box solution and they wonder why it doesn't work. Because you didn't do any of the work, you didn't do any of the analysis, you didn't do any of the real stuff that makes this tick."
  — Thomas Daugherty [24:15]

  "There are so many tools I have where I use one of the features, and sometimes the companies don't realize... they keep adding features no one wants or uses. Just do one thing really well."
  — Jonathan Green [24:26]

7. Best Practices for Effective AI Adoption

[26:00 – 27:32]

• Focus on identifying the actionable benefits of a tool—what problem does it solve, why is it important, does it fit the team’s workflow?

• Involve the ground-level team in both tool choice and adoption to avoid top-down mismatches and morale pitfalls.

• Jonathan praises newsletters that clearly summarize features and significance, making adoption decisions much easier.

  "They tell you what the product is, what the breakthroughs were... at the end they really summarize it up, why this is important, what does this actually solve, what does this fix... that format, because I think people learn better that way."
  — Thomas Daugherty [26:30]

8. The Future: Hybrid Models & Human Touch

[22:44 – 24:26]

• Thomas advocates for hybrid models—not full replacement, but empowering remote/human teams with AI.

• There is skepticism about "accent hiding" or deceptive approaches, and a clear argument that customer trust must be preserved through transparency and genuine human-AI collaboration.

  "I'm not so much into the accent hiding... it creates a really bad starting point because now you have deception as the first thing you've done. That's why I don't like AI phone calls for sales, because it's trickery and it creates a bad starting point. Once you've lied to someone, you can never recover that trust."
  — Jonathan Green [20:59]

Memorable Quotes & Moments

• On pseudo-metrics:
  "You get caught up in these pseudometrics... like, I had one social media manager who thought the measurement was reach. I was like, no, the measurement is money. The coming sales are we making? That's how I pay you. I can't pay you in reach. It's not a real thing."
  — Jonathan Green [05:51]

• On software updates gone wrong:
  "He ignored me. And they flipped the switch that weekend. You can guess whose call center team was getting blown up 9,000 ways to Sunday."
  — Thomas Daugherty [11:31]

• On pilots and training:
  "95% of companies are not seeing an ROI on their AI investment. And my belief is that those are the companies that did not do a pilot program or that kind of skipped over the training."
  — Jonathan Green [15:51]

• On partnership and best practices:
  "What a great opportunity to go to them and say, I want to partner with you because you're one of our most valuable clients. How do we partner together to build a solution that works best for you and your organization? That way there is that morale, that buy-in, that team part."
  — Thomas Daugherty [22:54]

Timestamps for Key Segments

• 01:01 – 02:59: Outsourcing evolution, Africa and agentic AI
• 04:05 – 08:22: Importance of process clarity and metrics
• 08:22 – 09:53: Is it AI vs. outsourcing, or a blend?
• 12:18 – 15:50: Change management, sabotage, onboarding pitfalls
• 15:50 – 22:44: Hype vs. practical adoption, morale, emotional costs
• 22:44 – 24:26: The danger of feature overload and out-of-the-box solutions
• 26:00 – 27:32: Tool onboarding best practices, communication
• 20:59 – 22:44: Transparency, trust, and the role of hybrid models

Closing & Resources

• Thomas Daugherty’s main platform: LinkedIn (Thomas Daugherty Jr.) [27:32]
• He highlights the value of cross-industry experience – issues are strikingly similar in legal, higher ed, finance, tech, etc.
• Jonathan promises links in the show notes for listeners to connect.

Key Takeaways

• Successful AI adoption is not about replacing people, but supplementing teams with AI to amplify productivity and focus, especially for repetitive tasks.
• Process mapping, clear success metrics, and end-user involvement in tool selection and onboarding are absolute musts.
• Beware hype, overcomplicated solutions, and neglecting company morale—the human element remains vital.
• Hybrid, transparent approaches that empower employees with AI are the most sustainable path forward.

This episode is a must-listen for business leaders considering a shift to AI or pondering the future of outsourcing, with highly actionable advice on change management, tool selection, and aligning technology to real business goals.