AI Transformation in Practice: Small Steps, Big Impact

What does AI adoption actually look like for organizations that don’t have massive tech budgets or dedicated innovation teams? That was the central question behind the “AI Transformation in Practice: Small Steps, Big Impact” panel at the Boise Metro Chamber’s 2026 Regional Leadership Conference.
 
Moderated by Michael Ballantyne of TOK Commercial, the panel brought together leaders from three very different sectors: Mayor Trevor Chadwick of the City of Star, Christina Hardesty of Amalgamated Sugar, and Rachel Attebery of Diode Ventures. What emerged was not a conversation about cutting-edge AI breakthroughs, but something more practical: how organizations are actually getting started, where they are seeing value, and what it takes to move from curiosity to implementation.
 
Start Small, but Start
Across industries, the panelists described a similar entry point into AI: not a sweeping transformation, but a single, practical use case.
 
At Diode Ventures, Attebery shared how she used Microsoft Copilot to build a full presentation—complete with audience-specific messaging and interactive elements—in a fraction of the time it would normally take. The value was not just speed, but perspective. AI helped tailor the content to what early-career engineers actually care about, drawing on patterns far beyond any one person’s experience.
 
For the City of Star, the starting point looked different. Chadwick described using AI to sift through hundreds of pages of development documents, pulling out the critical information needed for decision-making. In a resource-constrained environment, that kind of efficiency matters.
 
His takeaway was simple: the barrier to entry is lower than most people think. Start anywhere. Even basic tools can unlock meaningful time savings.
 
Legacy Systems Meet Modern Tools
For Amalgamated Sugar, the challenge is not whether to adopt AI, but how.
 
Hardesty offered one of the most grounded perspectives of the panel. The company operates facilities that are decades old, some more than a century. Before AI can even be considered at scale, there is a more fundamental issue: connectivity and infrastructure.
 
“We have to build the foundation before we can even move up,” she explained.
 
That reality shapes everything. Rather than pursuing large-scale transformation, the company is embedding AI into existing capital projects—like upgrading equipment or control systems—where the investment is already planned. It is a slower path, but a more realistic one.
 
Efficiency Is the Common Driver
Despite their differences, all three panelists pointed to the same underlying motivation: efficiency.

• For local government, it is about doing more with limited staff and shrinking budgets. 
• For agriculture, it is about surviving a difficult market while controlling costs. 
• For infrastructure developers, it is about enabling entirely new capabilities at scale. 

 
AI promises efficiency, but it also requires upfront investment. The challenge is determining where that investment delivers meaningful return.
 
Infrastructure Is the Limiting Factor
Attebery shifted the conversation from applications to what makes AI possible in the first place: infrastructure.

Three components stood out:

• Power: AI systems require enormous amounts of energy. 
• Data centers: Physical facilities are needed to house computing hardware. 
• Fiber: Connectivity is essential to move data between systems. 

Her message was clear: the future of AI is not just about software. It is about whether regions like Idaho can support it.
 
Culture Matters More Than Tools
One of the most practical insights had little to do with technology itself.
 
Hardesty emphasized the importance of identifying internal champions—people willing to take ownership of AI efforts. Without that, AI remains an abstract idea.
 
Chadwick echoed that sentiment, noting that adoption in Star was driven by team members bringing ideas forward.
 
A Shift That Feels Familiar
Chadwick compared AI today to the early days of Wikipedia. The information is powerful and fast—but it still requires human judgment. Outputs need to be checked. Critical thinking becomes more important, not less.
 
The Advice Was Consistent

• Start small 
• Be realistic 
• Focus on problems, not tools 
• Learn from others 
• Just start 

 
Michael Ballantyne, Trevor Chadwick, Christina Hardesty, and Rachel Attebery delivered these remarks at the Boise Metro Chamber’s 2026 Regional Leadership Conference on April 21, 2026. This blog post was prepared from a transcript using the help of AI.
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