Practical AI

Episode: The Impact of AI on the Workforce: A State-Level Case Study

Date: October 9, 2025
Host: Daniel Whitenack
Guest: Chelsea Linder, VP of Innovation & Entrepreneurship, Tech Point

Overview

This episode delves into the practical impacts of artificial intelligence on the workforce, spotlighting Indiana as a rich case study for state-level innovation. Daniel Whitenack hosts Chelsea Linder from Tech Point to discuss building collaborative AI networks, lessons from Indiana’s statewide initiatives, and recent findings from Tech Point’s report on workforce trends, skill gaps, and AI adoption. The conversation offers tangible insights on building community, fostering best practices, handling workforce transitions, and what the data says about where things are headed.

Key Discussion Points & Insights

1. Building an AI Innovation Network in Indiana

[00:49 – 06:55]

• Chelsea’s journey: From UX research at Angie's List, to venture capital investment at Generator, to Tech Point’s nonprofit mission of driving Indiana’s digital economy through talent, innovation, and community.
• The origin story: Indiana’s stakeholders expressed a clear need for sharing AI best practices. Resulted in the launch of the AI Innovation Network (funded by SBA’s Growth Accelerator Fund Competition).
  • Launched in January 2025; nearly 400 members as of the episode's recording ([04:35]).
• Intentional statewide focus: Designed as a hybrid (in-person & virtual) network to reach members from urban tech hubs to rural manufacturing floors.

Quote:

“We wanted this to be hybrid and we've been navigating what that means...It has given us the opportunity to serve people in the middle of the cornfields, in the manufacturing floor...that has been a really powerful impact.”
— Chelsea Linder ([06:35])

2. The Importance of Open Community and ‘Helper Culture’

[06:55 – 10:47]

• Hoosier hospitality: Indiana’s unique willingness to share, transparency, and lack of ego create a thriving, supportive community.
• Role of imposter syndrome: Sharing openly helps members see their value and overcome feelings of inadequacy.
• Format experiments: Live coding, open project reviews, and collective problem-solving make learning more relatable.

Quote:

“We have a strong community of helpers...I think it's the power of having a strong community of helpers. And I don't know the secret to building a strong community of helpers, but I do think that that's really the foundation that we were able to build off of.”
— Chelsea Linder ([08:23])

3. Building Effective Events: What Works

[11:50 – 13:49]

• Three main event types:
  • Pure networking (making professional friends)
  • Quarterly case studies (deep dives with group analysis & documentation)
  • Open sharing/project feedback sessions
• Example: Baker Hill’s reskilling case study—practical guidance on adoption and change management.

Quote:

“One of the key topics…was a feeling of imposter syndrome...So we've started to try to democratize the opportunities within the network, doing more live prompting or live coding activities, again just to help with that feeling of imposter syndrome and make everyone see they're not the worst person in the room at whatever they're doing.”
— Chelsea Linder ([09:27])

4. Lessons Learned in Community-Building

[16:00 – 17:51]

• Advisory council is crucial: Do not assume one-size-fits-all—let active practitioners shape network content and direction.
• Maintain momentum: Capture early energy, double down on high-value activities, and be willing to let some initiatives go.
• Flexibility is key: Some approaches may not work in every community; start with deep listening.

Quote:

“I am not an in the weeds AI practitioner...So we built an advisory council and they've been instrumental in helping us identify where the knowledge gaps are, how we can help fill those...”
— Chelsea Linder ([16:41])

5. Shifts in AI Adoption, Workforce, and Skill Demands

[19:14 – 34:51]

• New democratization: AI access is no longer just for large enterprises like Eli Lilly—small businesses are embracing AI, leveling the playing field.
• “Must do” factor: Even businesses without tech teams are reaching out to join the AI movement.
• Contradictory dynamics: Surging demand for gen AI engineers and AI-enabled IT roles (up 7x and 35%, respectively), alongside layoffs and workforce anxiety.
• Upskilling and reskilling: Critical challenge for all organizations, regardless of size or industry; Tech Point’s new report identifies integration into training, sector-specific skills, and cross-sector knowledge-sharing as fundamental.

Notable Data (from Tech Point’s report, [22:24]):

• Gen AI engineer postings up 7x year-over-year.
• Job postings requiring AI skills in other IT roles up 35%.
• Overall, only about 10% of businesses officially report using AI as of July 2025 (based on U.S. Census BTOS survey).

Quote:

“It's becoming clear that it's a competitive advantage...especially with Gen AI...this is really just the tip of the iceberg when it comes to truly implementing AI, not just gen AI within your business.”
— Chelsea Linder ([27:00])

• Software Engineering Endures: Despite AI advances and the rise of “vibe coding,” classic software dev roles remain the highest in demand, though the roles and workflows are evolving.
• Orchestrator roles vs. classic engineers: The transition to more coordination, prompting, and oversight, not outright replacement.

Quote:

“This is a transition in what those jobs look like, not a complete removal of those jobs from our workforce.”
— Chelsea Linder ([33:20])

• On the enduring foundation:

“The number one skill you need to vibe code well is to already know how to code.”
— Chelsea Linder ([34:51])

6. Counting Who’s Really “Using” AI—The Hidden Usage Challenge

[36:26 – 40:31]

• Only 10% of U.S. companies report official adoption, but far more people use AI informally (sometimes without employers realizing it).
• Case in point: AI-generated daycare status reports—employees using AI apps informally.
• Urgent recommendation: All businesses need AI acceptable use policies, even non-tech ones, to provide safe and productive guidance.

Quote:

“The best thing that a business owner can do is regardless of whether you think people are using it or not, you need to have a policy. You need to set up the appropriate guide rails so people can do it safely.”
— Chelsea Linder ([40:11])

7. Looking Ahead: AI Drives Hard Conversations—and New Innovation

[41:38 – 42:47]

• The next wave: Hard challenges and moral dilemmas—data center sustainability and energy efficiency, materials innovation, and more.
• Pressure and challenge as an engine for “a new crop of amazing innovations.”

Quote:

“I'm really excited about how AI is pushing people to be even more innovative and think about things in even more uncomfortable ways than they did before...challenges drive innovation.”
— Chelsea Linder ([41:38])

Notable Quotes & Timestamps

• “Our members are extremely willing to share and be transparent about their work…that is only to the benefit of the other members.”
  — Chelsea Linder ([07:45])
• “A little bit of willingness to be an open book or like show your work just to combat those feelings of imposter syndrome.”
  — Chelsea Linder ([09:27])
• “I think we're really uniquely positioned...we've witnessed...a democratization of access...small business may be able to grow exponentially more quickly, increase their productivity, et cetera, in a way that they really never would have been able to before.”
  — Chelsea Linder ([19:14])
• “I will hold fast forever that the number one skill you need to vibe code well is to already know how to code.”
  — Chelsea Linder ([34:51])
• “It's one thing to say, yes, I'm doing it, and it's a completely different thing to say we're doing it successfully.”
  — Chelsea Linder ([36:26])
• “The best thing that a business owner can do is regardless of whether you think people are using it or not, you need to have a policy.”
  — Chelsea Linder ([40:11])

Key Timestamps (Content Segments)

• [00:49] – Daniel Whitenack introduces Chelsea Linder, Tech Point’s mission & origin of Indiana’s AI Innovation Network
• [06:55] – Community values: Transparency, sharing, Hoosier hospitality, and fighting imposter syndrome
• [11:50] – Format of network events: Networking, deep-dive case studies, and open project feedback
• [16:00] – Lessons in building/maintaining momentum & importance of advisory council
• [19:14] – Data & insights from Tech Point’s new workforce skills report
• [27:00] – The shifting nature of in-demand skills: AI engineers vs. classic IT roles
• [33:20] – Evolving roles: Software engineering’s future & the lived experience with AI-powered workflows
• [36:26] – “Who really uses AI?” Official usage stats vs. much broader untracked adoption
• [40:11] – The need for clear, company-wide AI usage policies
• [41:38] – The climate of innovation fostered by technical and ethical challenges (especially data centers)

Conclusion

This episode is a masterclass in state-level AI innovation and workforce transition. Chelsea Linder and Tech Point provide a blue-print for how local ecosystems—regardless of their “tech hub” status—can drive adoption, upskilling, and meaningful community by focusing on inclusive transparency and ongoing feedback. The Tech Point report highlights how job roles are shifting (but not disappearing), and that “helper” culture mixed with structured peer learning is invaluable for navigating AI’s accelerating impact on the workforce.

For more resources and to access the workforce report:

• Practical AI: PracticalAI.fm
• Tech Point Report: Tech Point Website