Jared Pilon
You have likely experimented with AI tools like ChatGPT. Maybe you have asked it to draft an email or summarize a document. But if you are like most professionals, you have probably found the results underwhelming, generic, robotic, and far from what you'd actually use.
The problem is not AI itself. The issue is that most of us are treating AI as a fancy search engine rather than a collaborative partner that learns from us and our expertise.
I have been exploring AI implementation at my accounting firm and recently spoke with Taylor Arancibia, founder of Unveiling Innovations, on the Tax Talk Podcast. Taylor specializes in helping businesses adopt AI strategically, and he introduced me to a framework that has changed how I think about this technology.
What is the LEARNED Framework?
The LEARNED Framework offers a practical, step-by-step approach to AI integration in your business that prioritizes learning, experimentation, and ethical use. Instead of jumping straight to full implementation, it guides you through seven stages:
L – Leveraging AI: Start with initial exploration and experimentation
E – Extracting its Depth: Understand the capabilities and boundaries of AI
A – Asking Better Questions: Develop advanced prompting and context-building skills
R – Retention Through Repetition: Practice consistently across different use cases
N – Navigating Misuses and Misinformation: Recognize AI limitations and the need for human oversight
E – Experiment: Test AI in live work environments
D – Document Everything: Capture wins, losses, and insights to build your own playbook
This framework acknowledges that AI adoption is not a one-time decision. It's a learning process that requires intentionality, patience, and a willingness to make mistakes.
Shifting From Tool to Teammate
When you approach AI as a teammate, you begin to provide it with context. You engage in back-and-forth dialogue. You provide feedback on its responses instead of accepting the first draft. This shift in mindset is what separates basic AI use from strategic AI integration.
AI is predictive intelligence. When you give it vague or generic information, it predicts what you are looking for based on patterns it has seen before. That is why so many AI outputs feel formulaic.
The solution is to invest time in crafting detailed, context-rich prompts. Yes, this might mean writing what feels like a wall of text. But the payoff is content, analysis, or ideas that actually align with your needs.
For example, instead of asking AI to "write an article," you might say: "Here's my goal. Here are writing samples that reflect my voice. Here's the audience I'm speaking to. Now, help me craft content aligned with my mission." The more intentional you are with your prompts, the better your results.
Think of it this way: if you hired a new employee, you would not just say, "Do some bookkeeping." You would provide background, explain your brand, share examples, and clarify expectations. AI deserves the same level of context.
The Importance of Closed AI Environments
When I first started exploring AI, I was cautious about rolling it out to my team. I wanted to understand the risks before everyone started using ChatGPT for client work.
That instinct was correct. Early AI platforms learned from all user inputs, which posed a significant security risk for professional services firms handling sensitive client information. Fortunately, modern closed AI environments provide safe "playgrounds" where proprietary and client data remain secure.
Before implementing AI in your business, ensure you have a robust usage policy. Establish clear boundaries around what information can and cannot be entered into AI tools. Your brand reputation depends on it
Building a Culture of Experimentation
One of the most significant barriers to AI adoption in your business is cultural. Employees need encouragement to experiment, make mistakes, and learn. If your team fears failure, they will not take the risks necessary to discover how AI can genuinely improve their work.
Taylor recommended starting with a pilot group of interested employees. Have them document repetitive, time-consuming tasks—what he calls "dead tasks"—that drain energy. These are prime candidates for AI automation.
As your team experiments, track everything: time saved, lessons learned, successes, and failures. This documentation serves as your internal AI playbook and helps you measure ROI.
The Human Element: What AI Can't Do
It is important to remember that AI is not a thought leader. It curates information from everywhere, but it still needs strategic thinkers to implement learning and guide its application.
AI will not replace expertise. Instead, it will augment those who are willing to adapt and learn. For employees looking to advance their careers, now is the time to develop adaptability as a core skill.
And for business owners, this presents an opportunity. Use the time AI saves to offer growth opportunities, additional responsibilities, or skill development for your team, rather than just increasing workload.
Taking the First Step
If you are considering AI integration for your business, do not rush the process. Try following the LEARNED Framework. Start small, document your process, and build from there.
Work with your accountant and advisors to ensure your strategy aligns with your broader business goals. At Aimarkand Consulting Inc., we're actively exploring how AI can improve efficiency while maintaining the personalized service our clients expect.
Aimarkand Consulting Inc. is here to help you navigate technological change with the same strategic approach we bring to your financial planning. Contact us at to discuss how we can support your business.
Want to hear more about this topic? Check out the Tax Talk Podcast
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Posted: 1/26/26