Knowledge Center

AI is a powerful tool - but when it comes to values, people and consequences, human judgement still matters.

AI Tokens and The Economics of AI how AI pricing actually works and how small businesses can get the most value from it

AI Vocabulary brought to you by the BBB of Southern Colorado

AI as a Productive Multiplier brought to you by the BBB of Southern Colorado

Ethics, governance and guardrails in AI

PwC’s 2026 Global AI Jobs Barometer goes beyond the question of whether AI will “take jobs.” It explores how AI is changing the structure of work itself and what those changes could mean for employers, employees and people just entering the workforce.

Teaching for Tomorrow: Closing the expectations gap What happens when teachers are asked to do the impossible? New research from the Walton Family Foundation and Gallup examines how teachers experience their job demands. The Teaching for Tomorrow study reveals just how much unrealistic expectations and lack of role clarity impact key outcomes like job satisfaction and intention to remain in the classroom. While the research finds that many teachers face unrealistic or unclear expectations, it also confirms that with improved job expectations, teachers thrive.

Learn how to build trust in AI through responsible practices. Join our programs for hands-on training & certification.

Explore AI's impact on workplaces & employee engagement. Join us for training & workshops to enhance your skills.

Explore AI adoption trends in nonprofits. Join us for insights & training to enhance your organization's impact.

Recently, I had the privilege of testifying before the U.S. Senate about artificial intelligence and its transformative impact on the modern workforce. It was an opportunity to discuss an issue that is quickly becoming one of the defining economic questions of our time: What is AI actually going to do to jobs? The conversation around artificial intelligence often gravitates toward extremes. On one side is the promise that AI will dramatically increase productivity and create entirely new industries. On the other is the fear that automation will eliminate millions of jobs. The reality emerging from the data is more complicated — and, in many ways, more interesting.  Through leading the BBB AI Hub and training thousands of business owners, nonprofit leaders and workers on the responsible use of artificial intelligence, I have come to believe that AI literacy is increasingly becoming the difference between leverage and liability. I have watched people use AI to organize complex information, improve communication, accelerate research, analyze data and turn ideas into action faster than ever before. I have also watched people enter sensitive customer information into public AI systems, accept fabricated citations as fact, rely on biased or incomplete outputs and purchase products labeled “AI-powered” without really understanding what the technology does. The opportunity is enormous. But so is the responsibility. And nowhere is that becoming more evident than in the workforce.

Someone on your team has probably figured out a good way to use AI. Maybe it helps compare requirements against a deliverable, organize closeout documents, prepare an action log, or summarize project reporting. The prompt works. The result is useful. The person who built it knows exactly what to provide, how to phrase the instructions, and what needs to be checked afterward. Then someone else tries to use it. That is usually when the team discovers that a good prompt is not yet a repeatable construction workflow. The second person uploads the wrong version of the specifications. The output comes back in a different format. A requirement is missed. Nobody knows whether the AI used the contract, the addendum, or the folder labeled: FINAL — USE THIS ONE The problem is not necessarily the AI. The process was never fully defined.

Jonathan Liebert CEO of the BBB of Southern Colorado testifies before congress on the Impact of AI on the Workforce

AI already knows a lot. That is not really the problem. The challenge is teaching it what matters to your business. It does not automatically know your customers. It does not know your tone. It does not know your standards. It does not know your process. It does not know which details are important and which ones will send your team into a group text spiral. That is where the skill comes in. Using AI well is not just about asking better questions. It is about teaching AI what you want it to know so it can give you answers that are actually useful. That is the focus of the class I am teaching through the BBB AI Hub: Teaching AI your Business: Building Context That Actually Works. We are going to talk about how to use ChatGPT settings, Projects, and Custom GPTs to give AI better business context. Not in a complicated way. In a practical way. Because most business owners do not need more AI hype. They need to understand how to make AI useful in the work they are already doing.

Most industrial organizations are not starting from zero. They are starting from systems that already work—just not in ways that scale easily. Legacy workflows often represent years of optimization under real constraints. They are imperfect, but they are functional. This is why modernization is rarely a technical problem alone—it is a continuity problem.  The goal is not to replace what works. The goal is to reduce friction while preserving operational stability.