Podcast Summary

Podcast: B2B Agility with Greg Kihlström™
Episode: #78 — AI in the 'Real Economy' with Bassem Hamdy, Briq
Date: December 9, 2025
Host: Greg Kihlström
Guest: Bassem Hamdy, CEO and Co-Founder, Briq

Episode Overview

This episode explores the meaningful, real-world impact of artificial intelligence beyond the usual examples, focusing on its practical applications in foundational industries such as construction, energy, and manufacturing—the so-called "real economy." Greg Kihlström and guest Bassem Hamdy dive into how AI-powered digital workers are transforming these sectors, the opportunities and sensitivities around human replacement, and the organizational readiness needed to adopt these technologies.

Key Discussion Points & Insights

1. Defining "The Real Economy" and Digital Workers

• What is the "real economy"?
  Industries that are responsible for building and producing tangible goods—construction, manufacturing, energy—are at the heart of what Hamdy calls the "real economy."
  • “Everything that’s around you is built by these companies.” (03:13, Hamdy)
• Digital Worker Concept:
  Rather than being just a tool, a digital worker is designed to function more like an employee—performing tasks, learning from feedback, and enhancing operational capacity.
  • “We're like the Roomba of workers...we want something that wakes up and goes, is something dirty? Let me go clean that.” (09:23, Hamdy)
• Resistance to Change:
  Hamdy challenges the myth that these industries are technology-averse. Instead, they’re quick to adopt tech built specifically for their use cases.
  • “I don’t think construction and these industries are slow to pick up technology. I think technology companies are slow to understand these industries.” (05:33, Hamdy)

2. Low Friction Adoption Areas

• Back Office Automation:
  The easiest entry for AI has been in the back-office functions (accounting, payroll) where there are chronic labor shortages and repetitive, unattractive tasks.
  • “There are 300,000 open positions in white collar swivel seats in these industries...these seats are empty.” (06:34, Hamdy)
• Transition to Operational Roles:
  As expertise ages out and is not replaced, AI is moving from basic clerical tasks to supporting, and sometimes replacing, deep operational knowledge (e.g., reading construction drawings).

3. The Debate: AI’s Effect on Jobs

• AI as Job Replacement and Elevation:
  While AI can automate "inhumane" repetitive tasks, it enables people to focus on higher-value, creative contributions. The episode notes the importance of reframing the narrative—from job loss to job improvement and transformation.
  • “If your job can be replaced by a machine, your job is not rewarding as a human.” (09:00, Hamdy)
  • “Maybe those were shitty white collar jobs and we should find better ones.” (11:20, Hamdy)
• Long-Term Tech Evolution:
  Roles will inevitably change, and some may disappear—similar to switchboard operators and bank tellers. Coding itself may become less central due to AI advancement in code generation.
  • “I don’t even know if coding is going to be a job in five years.” (13:49, Hamdy)

4. Real ROI and Positioning AI’s Value

• Framing the Value Proposition:
  Hamdy advises balancing sensitivity around “human replacement” with the pragmatic business need to scale, reduce overhead, and prevent costly mistakes.
  • “If you’re talking to CEO of $100 million company that's trying to grow, can’t hire fast enough and is drowning in paperwork, they're not as interested in the ethical story.” (14:45, Hamdy)
• Beyond Labor Savings:
  True ROI comes from AI’s capability to reduce errors and risk—sometimes saving significantly more than the cost of a couple of salaries.
  • “Last year we missed an insurance certificate, there was a loss on a project, and that cost us $500,000 in a deductible.” (16:23, Hamdy)
• AI Detects Fraud and Risk More Effectively:
  For example, AI can detect subtle PDF manipulations in insurance docs far better than humans, preventing fraud proactively.

5. Readiness for AI Adoption

• Organizational Process Clarity Required:
  The major roadblock is companies’ inability to clearly articulate their business processes; alignment and documentation are key.
  • "They work in the same company, they cannot just write their process." (18:27, Hamdy)
• First Steps:
  Train the AI as you would an employee:
  • Upload standard operating procedures (SOPs)
  • Clarify systems and workflows
  • Provide example videos or flowcharts for machine learning
• Continuous Learning and Instinct:
  AI starts “60% effective” but improves with every feedback loop as new “edge cases” are handled, ultimately developing a sense of “instinct.”
  • “Instinct comes from experience...teaching AI to have instinct is really cutting edge.” (21:14, Hamdy)

6. Agility—Personal and Organizational

• On Staying Agile:
  Hamdy talks about his penchant for rapid change and how he manages that by imposing structured time horizons, like one-week sprints, to avoid chaos.
  • “I am the king of agile. I can change my mind six times in an hour...I’ve had to go the other way...one week sprints.” (22:24, Hamdy)

Notable Quotes & Memorable Moments

• On Technology Adoption:
  “Maybe these industries adopt technology faster than we think. They just adopt technology that is built for them.” (04:54, Hamdy)
• On AI's Impact on Work:
  “People are creative beings, they are social beings. A robot will never, ever replace something that can make a sale...Physical industries have these amazingly creative people, but we bogged them down with processes.” (10:22, Hamdy)
• On Paradigm Change:
  “It’s an inevitability. Don’t be the guy or girl sitting in a seat with the wrench, putting the Ford car together when that robotic arm is rolled in.” (12:58, Hamdy)
• On Agility:
  “I love inputs...making decisions and molding my decisions based on inputs...That’s great as a human, not great as the organization.” (22:34, Hamdy)

Important Segment Timestamps

• [03:13] — Hamdy defines "the real economy" and digital workers
• [05:33] — Technology adoption in foundational industries
• [06:34] — Low friction AI entry points and labor shortages
• [09:00] — AI’s impact on jobs and quality of work
• [11:20] — Reframing “white collar job” loss
• [13:49] — The future of coding jobs with AI
• [14:45] — Framing AI’s value proposition to traditional businesses
• [16:23] — Real-world risk mitigation examples (insurance, fraud detection)
• [18:27] — The need for process clarity before automation
• [21:14] — Teaching AI “instinct” through experience
• [22:24] — Hamdy’s personal approach to agility

Conclusion

This episode offers a grounded, candid discussion on how AI is transforming industries central to the real economy, not by replacing people wholesale, but by relieving them of repetitive, error-prone, "inhumane" work, and enabling organizations to scale and mitigate risk in smarter, faster ways. The path to success isn't just about tech—it's about organizational clarity, willingness to adapt, and a continuous feedback loop for AI and humans alike.