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FROM THE AI DESK

Welcome to our fifth issue!

In this issue, we look at why AI adoption may be moving faster than past technology shifts, what businesses should consider when employees use personal AI accounts for work, and how leaders can compare tools like Claude, ChatGPT, Gemini, and Copilot based on how they fit into daily workflows. We also explore the participation gap that can happen when employees are not included early in AI-related changes.

Together, these articles offer a closer look at how AI is showing up in business, where common risks and questions are emerging, and what leaders may want to consider as usage becomes more common.

What Changed in AI

The Fourth Curve: What PCs, the Internet, and Smartphones Tell Us About AI Adoption

AI adoption is starting to look familiar. PCs, the internet, and smartphones all followed the same path: early skepticism, growing use, business expectation, then daily dependence.

This article explains why AI is following that same curve, but on a steeper slope. Because AI does not require new hardware, is already being built into existing software, and uses plain language as the interface, adoption is moving faster than previous technology shifts. The bigger lesson for leaders is that adoption alone is not fluency. Companies need to start redesigning real workflows, not just giving employees access to tools.

See why this curve is steeper →

 

Why Businesses Should Move from Personal AI Accounts to Company-Managed AI

Free and personal AI accounts are useful for learning, but they are not a strong foundation for business use. When employees use personal tools for company work, leaders may not know what information is being uploaded, which connectors are enabled, how access is managed, or what happens when an employee leaves. This article explains why business and enterprise AI plans matter for data protection, user management, governance, employee enablement, and adoption measurement. The goal is not to slow people down. It is to give employees better tools while giving the company enough visibility and control to manage risk responsibly.

Read the managed AI guide →

 

Claude, ChatGPT, Gemini, or Copilot: Which One Should You Commit To?

Choosing an AI tool is no longer just about picking the “smartest” model. The better question is which AI ecosystem fits how your employees already work. This article compares Claude, ChatGPT, Gemini, and Copilot based on where each tool shows up in the workflow, what it is best suited for, and how it supports reusable assistants, projects, agents, file analysis, research, coding, and automation. For many companies, the right choice depends less on model rankings and more on adoption friction, existing systems, governance needs, and the type of work teams need AI to support.

Compare the platforms → 

AI in Action

“Nobody Asked Us”: The Participation Gap Your AI Transformation Might be Facing

AI rollouts often focus on the platform, timeline, training plan, and executive goals. But the people closest to the work are sometimes brought in too late — or not at all. This article looks at the “participation gap” that can quietly weaken AI adoption when employees feel the change is being done to them instead of built with them. It explains why front-line input matters, how “humble inquiry” can uncover risks and opportunities leaders may miss, and what participatory AI change can look like in practice through pilots, visible feedback loops, and early listening sessions.

Learn how to close the participation gap → 

Shadow AI

Shadow AI

Shadow AI is when employees use AI tools for work without the company officially approving, managing, or even knowing about them.

Shadow AI usually does not start with bad intent. It starts with someone who wants to summarize a meeting, rewrite an email, analyze a spreadsheet, or speed up a proposal, so they use a personal AI account. It is easy and familiar – and they become more efficient at the work they do for the company. The problem is that the company may not know what information is being uploaded, what settings are turned on, or whether the tool meets internal security and privacy expectations. The employee might also not know what is safe to provide into an AI tool.

As a company, the goal should not be to stop people from using AI. It should be to bring AI use into the open, in a governed and responsible way. When companies provide approved tools, clear rules, and practical training, employees can still get the productivity benefits of AI without creating unnecessary risk for the business.

If AI is changing every two weeks, won't anything you build for us be outdated in six months?

If AI is changing every two weeks, won't anything you build for us be outdated in six months?

The models change fast — your business problem doesn't. When we build an AI workflow, the model underneath is a swappable component; the solution keeps running no matter what version powers it. In practice, only two things force a change: you switch core systems, or your inputs change format — the same things that would require retraining an employee. More often, these builds get cheaper over time, since older models drop in price as new ones launch.

📬 Got a question for next month?

Each month we answer a real question from a real business — anonymously. Wondering something about AI? Submit a question and it might be next month's feature.

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SPECIAL INVITATION

There's Still Time to Register for the AI Roundtables!

There’s still time to join us for our next AI Roundtable. Two dates to choose from:

    • Tuesday, July 28th at Nakoma Golf Club in Madison
    • Thursday, August 13th at Boerner Botanical Gardens in Hales Corners

Save Your Spot in Madison →

Save Your Spot in Hales Corners →

This in-person session is designed for business leaders who want a practical, no-jargon look at where AI is showing up in real work — and where it may fit next inside their own organizations. We’ll walk through fresh use cases, talk through common adoption questions, and give attendees a chance to compare notes with peers across industries.

You do not need a technical background to participate. The goal is to make AI clearer, more approachable, and easier to connect to the work your teams are already doing.

Seats are limited, but there’s still time to reserve yours.

Save Your Spot in Madison →

Save Your Spot in Hales Corners → 

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