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  • Copilot vs. ChatGPT: Choosing the Right AI Tool for Your Business

    AI tools are everywhere—and if you’re a small business leader, you’ve probably been asked (or asked yourself):

    “Should we be using Copilot or ChatGPT?”

    It’s a great question. But the answer depends on what you’re trying to do, how your team works, and what kind of experience you want to create.

    This article breaks down the differences between Microsoft Copilot and ChatGPT, including their versions, customization capabilities, memory behavior, and what to consider when choosing between them. Note – this article was written with the help of AI as a thought partner.

    What’s the Difference?

    • Microsoft Copilot is designed to work inside Microsoft 365 tools like Word, Excel, Outlook, and Teams. It’s context-aware—meaning it uses the document or email you’re working on to help you in real time.
    • ChatGPT is a standalone AI assistant that you can use for writing, brainstorming, summarizing, and more. It’s flexible, creative, and highly customizable—especially in its paid versions.

    Comparison Table: Versions, Features, and Memory

    Feature / Version Microsoft Copilot (Free) Copilot Pro Copilot for Microsoft 365 ChatGPT Free ChatGPT Plus ChatGPT Team ChatGPT Enterprise
    Platform Web, Edge, Windows Web, Word, Excel, Outlook (personal) Word, Excel, Outlook, Teams (business) Web, mobile app Web, mobile app Web, mobile app Web, mobile app
    Model Used GPT-4 Turbo (web only) GPT-4 Turbo GPT-4 Turbo GPT-3.5 GPT-4 Turbo GPT-4 Turbo GPT-4 Turbo
    Best For General AI chat Personal productivity Enterprise productivity Casual use Power users Small teams Large organizations
    Context Awareness No document context Yes (in Microsoft 365 apps) Yes (deep integration with 365 data) No No No No
    Customization (Tone, Style) None Limited (adapts to current doc/email tone) Limited (based on content/context) None Moderate (via custom instructions) High (custom GPTs, shared settings) Very high (admin-level control)
    Memory / Personalization None None Contextual only (no persistent memory) None Yes (remembers preferences, facts) Yes (team memory, shared GPTs) Yes (enterprise-grade memory)
    What Happens If You Cancel? Nothing to retain No memory to lose Data stays in your Microsoft 365 tenant Nothing to retain Memory is paused, not deleted Memory retained, inaccessible until resumed Data retained per enterprise policy
    Security & Compliance Microsoft account-level Microsoft account-level Enterprise-grade (Microsoft 365 compliance) OpenAI account-level OpenAI account-level Team-level controls SSO, encryption, admin console

    How Customization and Memory Work

    Microsoft Copilot

    • Customization: You can set preferences in some apps (like Outlook or Word) for tone, length, or style—but these are session-based or app-specific.
    • Memory: Copilot does not have persistent memory. It adapts to the content you’re working on in real time, but it doesn’t remember your preferences across sessions or apps.
    • Context Awareness: Copilot is highly effective when you give it the right context. For example, if you attach a tone-of-voice guide, branding document, or creative brief from OneDrive or SharePoint, Copilot can use that to shape its responses—without needing to “remember” anything long-term.

    If you have multiple Microsoft apps open, Copilot only accesses the one you’re actively working in. It doesn’t pull context from other open apps or documents.

    This makes Copilot especially powerful for secure, compliant brainstorming and content creation—because you can guide it with documents you control, without exposing your data to external systems or persistent memory.

    ChatGPT

    • Customization: You can set custom instructions (e.g., “speak in a friendly tone” or “write like a consultant”) and build custom GPTs with specific behaviors.
    • Memory: In Plus, Team, and Enterprise plans, ChatGPT can remember your tone, preferences, and even facts you’ve shared. You can view, edit, or delete this memory at any time.
    • Cross-Session Continuity: Memory persists across sessions, so it can feel like you’re working with a consistent assistant who knows your style.

    Risks and Considerations of ChatGPT’s Memory

    While memory in ChatGPT can be incredibly helpful, it’s important to understand the trade-offs:

    Risk / Consideration What It Means
    Misremembering ChatGPT might remember something incorrectly or apply a tone you no longer want.
    Overfitting If your tone or audience changes, ChatGPT might keep writing in your old style unless you update it.
    Data Sensitivity In Free and Plus plans, your data may be used to improve the model unless you turn off chat history.
    Team Oversight If multiple people use the same account or workspace, memory could reflect one person’s preferences over others.
    Privacy Awareness Users may not always realize what’s being remembered or how it’s being used unless they check settings.

    If you’re using ChatGPT for business, consider Team or Enterprise plans to ensure your data isn’t used for training and you have full control over memory.

    Data Privacy and Governance

    Topic Microsoft Copilot ChatGPT (OpenAI)
    Data used to train model? No. Your data is not used to train Microsoft models. Free & Plus: Yes, unless chat history is off. Team & Enterprise: No.
    Where is memory stored? Not applicable (no memory). On OpenAI’s servers (encrypted, user-manageable).
    Who governs usage? Microsoft 365 privacy and compliance policies. OpenAI’s usage policies and privacy terms.
    Can you delete memory? Not applicable. Yes, at any time via settings.

    Which One Should You Use?

    If you want to… Use…
    Work inside Word, Excel, Outlook, or Teams Microsoft Copilot
    Get help writing emails or documents in your voice ChatGPT Plus or Team, or Copilot with attached tone/branding docs
    Summarize meetings or search internal files Copilot for Microsoft 365
    Brainstorm ideas or write social media posts ChatGPT, or Copilot with attached creative briefs or brand docs
    Build a custom AI assistant for your team ChatGPT Team or Copilot Studio
    Ensure enterprise-grade security and compliance Copilot for Microsoft 365 or ChatGPT Enterprise

    Final Thoughts

    Both Copilot and ChatGPT are powerful—but they serve different purposes.

    • Copilot is ideal for secure, real-time assistance inside Microsoft 365. It doesn’t need to remember you—it just needs the right context, which you can provide through the documents you already use.
    • ChatGPT is better if you want a persistent assistant that learns your style and preferences over time, especially for creative or exploratory work.

    And if you’re not sure which one is right for you? That’s okay too. We’re here to help you

    Addition Note: What guarantee is there that ChatGPT data will be deleted?

    Can You Trust That ChatGPT Memory Won’t Be Used or Transferred?

    1. OpenAI’s Current Policy (as stated)

    OpenAI has publicly committed that:

    • ChatGPT Team and Enterprise data is not used to train their models.
    • ChatGPT Plus and Free users’ data may be used to improve models unless chat history is turned off.
    • Users can view, manage, and delete memory entries.

    However, these policies are not contractual guarantees. They are governed by OpenAI’s Terms of Use and Privacy Policy, which OpenAI can update at any time.

    1. Recent Legal Developments (May 2025)

    A U.S. federal court has issued a data preservation order requiring OpenAI to retain all ChatGPT user conversations indefinitely—including those users believed they had deleted

    This order was issued in the context of ongoing litigation, including a lawsuit from The New York Times alleging copyright infringement. The implications are significant:

    • Deleted conversations are not actually deleted under this order.
    • All user-generated content is being retained, regardless of user settings.
    • This raises serious concerns about data privacy, ownership, and future use.
    1. What This Means for You

    Even if OpenAI’s current policy says your data won’t be used to train models:

    • There is no legal guarantee that this won’t change in the future.
    • Court orders can override privacy settings, as we’re seeing now.
    • Data stored on OpenAI’s servers could be subject to future use, transfer, or exposure, especially if OpenAI is acquired, restructured, or compelled by law.

    Summary: Microsoft vs. OpenAI on Legal Exposure

    Topic Microsoft Copilot ChatGPT (OpenAI)
    Data used to train model? No Free & Plus: Yes (unless chat history is off); Team & Enterprise: No
    Legal orders affecting data None reported Yes – court-ordered data preservation for all chats
    Memory behavior No persistent memory Persistent memory in paid plans
    Data governance Microsoft 365 compliance framework OpenAI’s evolving privacy policy
    Ownership of content You own the content Copilot helps generate You own your content, but OpenAI retains broad rights under its terms

     

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  • Choosing AI-First Tools: Productivity with Purpose

    AI is everywhere right now. And if you’re a small business leader, you’ve probably heard some version of this question:

    “Which AI tool should we be using?”

    It’s a fair question. Teams are already experimenting with tools like ChatGPT, Copilot, and others—often without a clear plan. Leaders feel pressure to provide guidance quickly. But the correct answer depends on what you’re trying to do—and what kind of tool you’re evaluating.

    This article is here to help you think it through. Not to slow you down but to help you move forward with clarity and confidence.

    What Are AI-First Tools?

    AI-first tools are platforms adopted primarily because of their AI capabilities. They’re designed to help you think, write, summarize, or automate tasks—often in ways that feel like magic.

    These tools aren’t just “smart features” added to existing software. They’re built around AI from the ground up.

    Some common examples:

    • ChatGPT: A conversational assistant that can help you brainstorm, write, or research.
    • Microsoft Copilot: Embedded in tools like Word, Outlook, and Teams to help generate content, summarize meetings, and more.

    These tools support individual productivity or team collaboration. AI-first tools can be a great fit if you aim to help people work more efficiently or think through ideas.

    When to Use Them

    Here are a few everyday use cases where AI-first tools shine:

    • Writing and editing: Drafting emails, reports, or proposals.
    • Meeting summaries: Capturing key points and action items.
    • Research and ideation: Exploring new ideas or gathering information.
    • Task automation: Helping with repetitive or time-consuming tasks.

    If your team is already using Microsoft 365 and you don’t have time to define specific use cases, Copilot is often a good starting point. It’s integrated, secure (assuming your 365 environment is configured correctly), and works across familiar tools.

    For example:

    • Copilot in Word or Outlook can help generate content.
    • Copilot in Teams (with Premium) is great for summarizing meetings.
    • You can even build a custom Copilot agent to search SharePoint or help retrieve internal knowledge.

    How to Choose the Right Tool

    Even with AI-first tools, defining what you want to achieve is important. Are you looking for:

    • A thought partner?
    • A writing assistant?
    • A meeting summarizer?
    • A research tool?

    The more precise you are about your goals, the more value you’ll get from the tool—and the easier it will be to guide your team.

    Here are a few questions to ask:

    • What problem are we trying to solve?
    • Who will use this tool, and how?
    • What kind of data will it access?
    • Does it integrate with our existing systems?
    • What are the security and compliance implications?
    • How much training will our team need?

    Avoiding the Most Expensive Mistake

    The most expensive mistakes we see aren’t in the build—they’re in skipping the diagnostic and design steps.

    If you don’t clearly define the problem and how the tool should support your process, you risk creating something that looks good on paper but doesn’t solve the issue.

    Implementation without insight is just guesswork with a price tag.

    No two tools are exactly alike. If there’s a feature you love in one, ask:

    “What problem is this solving?”

    Then, see if the new tool can solve that problem—even if it does it differently.

    Because solving the problem is what matters, we can all build new muscle memory. If we’re not solving the right problem, making something easy to do 100 times doesn’t help.

    You Don’t Have to Figure It Out Alone

    These tools are powerful, but they’re not magic. They require specialized expertise—not just to implement and configure them but also to assess what’s needed.

    That’s where we come in. We help you clarify your goals, evaluate your options, and make smart decisions that move the needle. And we can help you get it running, too!

    Ready to Explore What’s Possible?

    Let’s talk if you’re curious about AI tools but unsure where to start. We’ll help you think it through—so you can choose the right tool for the right reason at the right time.

    The fundamental transformation happens when you pair the right technology with the right thinking.

    TechHouse

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  • AI Inside: Choosing Business Systems with Embedded Intelligence

    By now, you’ve probably seen AI appear in almost every tool you use—from your inbox to your accounting software. And if you’re a small business leader, you might be wondering:

    “Do I need to rethink our tools—or just learn how to use them better?”

    The answer depends on what kind of tool you’re talking about.

    Our last article discussed AI-first tools—platforms like Copilot or ChatGPT adapted specifically for their AI capabilities. But many of the tools you already use—like QuickBooks, Business Central, or your CRM—now include AI features, too.

    This article is about those tools. The ones you choose for their core business value, where AI is a bonus—not the main event.

    What Are AI-Embedded Business Systems?

    You’d likely be using these tools anyway because they help you run your business. Think:

    • Accounting software
    • CRMs
    • ERPs
    • Project management platforms

    Business applications support your core processes. And now, many include AI features to make those processes smarter, faster, or more efficient.

    For example:

    • QuickBooks uses AI to categorize transactions and forecast cash flow.
    • Business Central can automate workflows and detect errors using AI.
    • Dynamics 365 Sales uses AI to draft emails, score leads, and summarize meetings.

    These features can be beneficial—but they’re not why you bought the tool in the first place. That’s an important distinction.

    What to Look For

    When evaluating these systems, AI is just one piece of the puzzle. You still need to make sure the tool meets your core business needs.

    Here are a few questions to guide your evaluation:

    1. What problem are we solving?

    Start here—always. If you don’t know what you’re trying to fix or improve, it’s hard to know if the tool is a good fit.

    1. How is the AI embedded?

    Is it a native feature or an add-on? Does it work out of the box, or does it require configuration?

    1. What data does it use?

    Is it using your internal data? Does it integrate with other systems like Outlook or SharePoint?

    1. What level of control do you have?

    Can you customize how the AI behaves? Can you review or override its suggestions?

    1. What are the security and compliance implications?

    Where is the data processed? Does it align with your organization’s data governance policies?

    1. What’s the learning curve?

    Will your team need training? Is the AI intuitive, or does it require technical support?

    Examples of AI in Action

    Here’s how AI shows up in some of the most common business systems:

    QuickBooks Online

    • Transaction Categorization: AI suggests categories for expenses based on past behavior.
    • Cash Flow Forecasting: Predicts future cash flow based on historical data.
    • Invoice Reminders: Automatically nudges customers about unpaid invoices.
    • Receipt Capture: Uses OCR to extract data from uploaded receipts.

    Dynamics 365 Business Central

    • Copilot Agents: Automate tasks like processing sales orders directly from customer emails.
    • AI-Powered Forecasting: Predicts inventory needs, cash flow, and demand trends.
    • Error Detection: Spots unusual data patterns or values that break defined rules.
    • Natural Language Queries: Business central users can ask questions like “How many customers did we add last month?” and get answers in plain English.

    Dynamics 365 Sales & Service

    • Email Drafting: AI helps write replies based on CRM context.
    • Meeting Summaries: Automatically generates summaries and action items from team meetings.
    • Lead Scoring: Prioritizes leads based on past performance and defined criteria.
    • Customer Insights: Surfaces relevant data from Outlook, SharePoint, and Teams to personalize interactions.

    The same Rule Applies: Define Before You Decide

    Whether you’re evaluating an AI-first tool or a business system with AI built-in, the principle is the same:

    Define what you need before you choose.

    If you skip the diagnostic step and choose based on features alone, you increase the risk of misalignment. You might need to pivot later—and that’s okay—but it’s better to go in with your eyes open.

    Implementation Without Insight Is Just Guesswork

    These tools require specialized expertise—not just to implement and configure but also to assess what’s needed in the first place.

    The most expensive mistakes we see aren’t in the build—they’re in skipping the diagnostic and design steps. If you don’t clearly define the problem and how the tool should support your process, you risk ending up with something that looks good on paper but doesn’t solve the issue.

    You Deserve More Than a Feature List

    You deserve a solution that works for your business—not just a list of impressive features.

    That’s why we always start with thoughtful discovery. We help you clarify your goals, evaluate your options, and make smart decisions that move the needle.

    Let’s Think It Through—Together

    If you’re wondering whether your current systems are working for you—or if it’s time to explore something new—we’re here to help.

    Let’s talk about what’s possible. We’ll meet you where you are and help you move forward with clarity and confidence.

     

    TechHouse

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  • AI Security: Essential Tips for Everyday Users

    This isn’t your parents’ software security – Why AI Models are Different

    AI software is different from traditional software. In the past, we wrote instructions called code; if our instructions were off, we would encounter a bug. We then adjusted the instructions to fix the bug. However, AI software has a brain called the model, which comprises both stored knowledge and neural pathways to access that knowledge. There is no way to see which pathways were used when using AI software. You cannot “step-by-step debug” an AI model as you could with macros or other instruction-based(code) software.

    Protecting Your Information

    Your Knowledge is Valuable – Don’t Give it Away.

    The value of an AI model is in its knowledge. A model is “trained” on data to answer more questions and be a more powerful intelligence. Models are hungry for more information so they can become more intelligent. Ready sources of information are users’ conversations with the LLM. Just like we learn when we converse with each other, AI learns when we converse with it. When you ask the model a question and converse on a topic, the AI model can remember that it can converse and use it to inform its answer to the next person it talks with. This means your questions and responses to the AI model could be shared with others. Here are a few things to consider:

    • Nothing is free: Models need data to grow their intelligence. Check if your AI provider commits to not using your interaction with the model to train it. Most free AI is being paid for not in currency but with your data. Anything you do not want to share with the entire world on a billboard, you would not want to enter into an AI that incorporates it into its model.
    • How to address Data Protection: The version of Copilot that comes with most Microsoft core subscriptions, such as Microsoft 365 Basic, Standard, Premium, and their Enterprise counterparts, includes data protection, so your data is not used to train the AI model.
    • Sensitive Information: Copilot uses the security measures you already have to protect your internal content from unauthorized access. This means that your existing security protocols, such as restricting access to specific SharePoint libraries, remain in place to keep your data safe.

    Accuracy and Validation

    No One is Perfect, and Accuracy is not guaranteed.

    Like the human brain, an AI model provides the most likely accurate response, but accuracy is not guaranteed. Think of AI as a thought partner, an intern, advisor, or consultant. In those scenarios, you would know to converse with them with the expectation that some of what they say will be wrong or inaccurate due to misunderstanding, ineffective sources of information, bias, etc. If you met that consultant, advisor, or intern for the first time, you would probably reference check their background and inspect what you expect – delegate but don’t abdicate.

    How to Address Accuracy

    It’s essential to test the validity of your AI model and continue to validate each response. First, for the model itself, look for documentation and reliable sources that support the model’s accuracy. Working with known or trusted vendors whose business model is based on something other than buying and selling data is another good step.

    In our daily work, our best defense against AI’s inevitable errors is to use a tool that includes citations. By providing links to the source documents that the AI model is using to derive its answers, you can judge whether or not that source is reliable and evaluate the source itself for capability.

    Poisoning an AI Model

    Even if the model was created with care and there are excellent citations, a model can be poisoned. Data poisoning happens when threat actors target the training data the model uses. Here are some examples:

    • Malware: Corrupting the model by inserting malware into it. This happened when 100 poisoned models were uploaded to the Hugging Face AI platform. Each one could deliver malicious code onto a user’s machine.
    • Phishing Attacks: For example, having a bot that uses the AI model to provide a phishing link to users rather than the correct link.
    • Inserting Bad Data: A threat actor trains the model to provide inaccurate results or conspiracy theories or to create backdoors into the model for more damage.

    Next Steps:

    How do we stay safe in an AI world? Opt for paid subscriptions to protect your data, leverage your existing security protocols, understand the AI models you’re using, be aware of model poisoning, and test the validity of your models with citations. If this sounds familiar, our team at TechHouse is happy to help.

    TechHouse

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  • How to Get Started with AI Using Microsoft Copilot: A Simple Guide for Everyday Users

    If you use Microsoft Word, Excel, Outlook, or Teams, you might have noticed a new helper called Copilot. It’s part of Microsoft’s AI tools and makes your work easier, faster, and even more fun.

    But what exactly is Copilot? And how do you use it if you’re not a tech expert?

    Let’s break it down.

    Copilot Is More Like a Brain Than a Program

    Think of Copilot like a smart coworker, not a robot that always knows the correct answer. It’s designed to help you think, write, plan, and solve problems, but it doesn’t always get things perfect.

    That’s why it’s best to treat Copilot as a thought partner. It can help you:

    • Draft emails
    • Summarize documents
    • Create presentations
    • Brainstorm ideas
    • Analyze data

    But you’ll still need to review and guide what it gives you.

    Which Copilot Do You Have?

    There are different versions of Copilot depending on your Microsoft license. If your workplace uses Microsoft 365, you might already have access to:

    • Copilot in Word, Excel, Outlook, and Teams
    • Copilot in PowerPoint to help build slides
    • Copilot in OneNote to organize your thoughts

    You can check with your IT team or visit Microsoft’s Copilot overview to see what’s included in your plan.

    Be Smart About AI Advice

    AI is exciting, but there’s also a lot of misinformation out there. Some people claim there’s “no risk” in using AI or training it with your data. That’s not true.

    Here are a few things to keep in mind:

    • Training AI on sensitive data can be risky—it might remember things it shouldn’t.
    • Check the sources of any information Copilot gives you.
    • Be cautious about who you learn from—some “AI experts” may not have real experience.

    If someone is giving you AI advice, ask about their background. Just like you wouldn’t take legal advice from someone who’s never studied law, you shouldn’t take AI advice from someone who’s never worked with it.

    Learn for Free—No Extra Cost

    You don’t need to pay for expensive courses to learn how to use Copilot. Microsoft offers free training that’s easy to follow:

    • Get started with AI on Microsoft Learn
    • Copilot for Microsoft 365 Training Hub

    These are included with your Microsoft license—no extra fees.

    Want to Get Better with Copilot? Build These Skills

    To get the most out of Copilot, focus on:

    • Critical Thinking – Don’t just accept the first answer.
    • Asking Good Questions – The better your prompt, the better the result.
    • Creative Problem Solving – Use Copilot to explore new ideas and solutions.

    Yes, Copilot can help you write a quick email. But it can also help you plan your day, solve tricky problems, and develop new ideas—if you know how to work with it.

    Final Tip: Start Small

    Try asking Copilot to:

    • Write a summary of a long email
    • Help you draft a meeting agenda
    • Create a to-do list from a Teams chat

    Once you get comfortable, you’ll see how powerful it can be.

    TechHouse

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  • AI, Now What? Thought Starters for Your AI Strategy

    AI is changing how we solve problems, make decisions, and run our businesses. But as AI becomes more powerful, the key question isn’t just “What can AI do?”—it’s “What should people do?” What role do humans play in a workplace shaped by AI? And how do we prepare our organizations to use AI wisely?

    This article highlights key areas to strengthen your AI strategy—especially the human skills that make AI more effective. They may not be technical tools, but they’re just as essential. If you’re building or updating your AI strategy, these are the conversations to start now.

    1. Ask Better Questions

    AI is only as helpful as the questions we ask. Tools like the “5 Whys” help uncover root causes, but good questions also need context, judgment, and experience—things only people bring.
    Help your team ask sharper, more strategic questions. This leads to better answers from AI and stronger decisions overall.
    Want to go deeper? 

    2. Build Wisdom Through Diverse Perspectives

    AI delivers data. People bring wisdom. That wisdom grows through experience and by listening to different points of view.
    One way to build this into your culture is silent brainstorming. Give each person 5–15 minutes to write down ideas without discussion. Then, meet the next day to reflect and plan. Over time, your team will get better at turning ideas into action.
    For example, our team uses a structured creative problem-solving process. Each member is trained to work through challenges using this framework—often bringing in a colleague to gain a fresh perspective. At our most recent strategic retreat, this approach helped the team align department objectives with company goals in a focused, half-day session.

    3. Strengthen Community and Communication

    Strong teams challenge each other. Weak teams say, “Whatever you like.” While that kind of agreement may seem polite, it can block innovation and lead to poor decisions.
    Create a culture where people feel safe speaking up. Help your team understand different communication styles and their pros and cons. This will make the above problem-solving sessions more effective. If they gather answers from AI, they will have the tools to discuss and evaluate those responses for accuracy and effectiveness.

    A helpful resource: Being assertive: Reduce stress, communicate better – Mayo Clinic

    4. Don’t Confuse Confidence with Accuracy

    AI can sound confident—even when it’s wrong. That’s why human oversight is essential.
    Ask yourself:
    – What checks are in place to review AI-generated content?
    – Which tasks can run without human review—and which ones can’t?
    These are policy decisions, not just technical ones. Make those decisions intentionally.

    In our own work, we developed an AI agent to respond to customer inquiries using senior-level engineering knowledge. While many responses were accurate, some missed the mark—or worse, felt off-putting. We added a human review step, and the quality of responses improved significantly. So did our team’s confidence in using AI responsibly.

    Final Thought: Keep the Human in the Loop

    AI can boost your team’s abilities—but only if your team knows how to use it well. That means investing in human skills like questioning, collaboration, communication, and critical thinking.
    These skills aren’t just nice to have—they’re what make AI work in the real world.
    Need help building your AI strategy?
    We help small and mid-sized organizations design and implement AI strategies that work—both technically and culturally. From training and workshops to full implementation, we’re here to help.
    👉 Let’s talk about what’s next for your organization.

    TechHouse

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  • AI, Now What? Good Questions for Good Answers

    Success depends on having the right tools and asking the right questions. AI is powerful, but it doesn’t replace human insight. To get the most from AI, leaders must focus on the human side: curiosity, collaboration, and critical thinking.

    This article asks business leaders: What do I do about AI in my organization? The answer starts with better questions.

    Why Good Questions Matter

    Good questions drive better decisions. They help us:

    • Uncover root problems
    • Challenge assumptions
    • Generate new ideas

    But asking good questions isn’t just a skill—it’s a mindset. It comes from experience, diverse perspectives, and a willingness to think beyond the obvious.

    10 Question Types for Your Team

    Here are ten questions that can sharpen your thinking and improve your outcomes. Each has a time and place—knowing when to use them is as important as knowing what to ask.

    1. Clarifying Questions

    Use when: You need to understand a situation more clearly.

    Example: “Can you walk me through what success looks like for this project?”

    Avoid when: The answer is already clear or has been repeated.

    1. “Why” Questions (Root Cause)

    Use when: You’re digging into the cause of a problem.

    Example: “Why are customers dropping off after the first purchase?”

    Avoid when: It may sound accusatory—try “What’s contributing to…” instead.

    1. Open-Ended Questions

    Use when: You want to spark discussion or creativity.

    Example: “What other options could we consider?”

    Avoid when: You need a quick, specific answer.

    1. Strategic Questions

    Use when: You’re aligning actions with long-term goals.

    Example: “How does this initiative support our mission?”

    Avoid when: The team isn’t ready for big-picture thinking.

    1. “What If” Questions

    Use when: You’re exploring innovation or risk.

    Example: “What if we had to deliver this with half the budget?”

    Avoid when: The team needs clarity before brainstorming.

    1. Reflective Questions

    Use when: You’re reviewing a project or learning from experience.

    Example: “What would we do differently next time?”

    Avoid when: The team is in crisis mode.

    1. Prioritization Questions

    Use when: You’re making trade-offs.

    Example: “Which of these goals is most critical this quarter?”

    Avoid when: All options are still being explored.

    1. Stakeholder Questions

    Use when: You’re considering impact or buy-in.

    Example: “How will this change affect our frontline staff?”

    Avoid when: The internal plan isn’t clear yet.

    1. Risk and Obstacle Questions

    Use when: You’re planning or troubleshooting.

    Example: “What could prevent us from hitting this milestone?”

    Avoid when: The team is in a creative phase.

    1. Vision and Purpose Questions

    Use when: You want to reconnect with the “why.”

    Example: “What impact do we want on our customers?”

    Avoid when: The team needs tactical direction.

    AI’s Confidence Isn’t Always Accuracy

    AI can sound sure of itself—even when it’s wrong. That’s why:

    • Human oversight is essential
    • Critical thinking is non-negotiable
    • Verifying sources is a must

    Final Thought

    AI is a tool. The real power lies in how we use it, which starts with the questions we ask. The future belongs to organizations that combine innovative technology with wise leadership.

    Let’s keep asking better questions—together.

    Let’s Talk Strategy

    If you’re thinking about bringing AI into your organization—or how to rethink your tech strategy—we’re here to help. From planning to implementation to support, we partner with leaders to build smarter, more resilient organizations.

    Reach out to start the conversation.

    TechHouse

    Innovative Solutions. Practical Software. Friendly Support.

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  • Top 5 Copilot Prompts for Beginners: Get More Done with Less Effort

    If you’re just starting with Microsoft Copilot, you might wonder: What exactly should I ask it to do? The good news is that you don’t have to be a tech expert to start seeing real benefits.

    Here are five simple prompts you can try today to boost your productivity and confidence with AI.

    1. 📨 “Summarize this email thread for me.”
    • Where to use it: Outlook
    • Why it’s helpful: Ever scanned the first paragraph of a long email chain only to find out later that the real message was buried three replies earlier? Copilot can quickly summarize the entire conversation, so you stay on track and on point.

    Try it:

    “Summarize this conversation and highlight any action items.”

    1. 📝 “Help me write a professional response to this email.”
    • Where to use it: Outlook
    • Why it’s helpful: Whether you’re replying to a client or a colleague, Copilot can help you sound clear, confident, and professional.

    Try it:

    “Write a polite response confirming the meeting and asking for the agenda.”

    1. 📊 “Analyze this Excel data and give me key insights.”
    • Where to use it: Excel
    • Why it’s helpful: Copilot can spot trends, calculate summaries, and suggest charts—no formulas required.

    Try it:

    “What are the top 3 products by sales this quarter?”

    1. 🧠 “Give me three ideas for a new marketing campaign.”
    • Where to use it: Word, Teams, or OneNote
    • Why it’s helpful: Copilot is great for brainstorming. Use it to get unstuck or spark new ideas.

    Try it:

    “Suggest three marketing campaigns for children’s clothes via online markets in the US that would appeal to mid-market consumers of sustainable brands. Provide each one’s strengths and weaknesses.”

    1. 📅 “Create a meeting agenda based on this Teams chat.”
    • Where to use it: Teams or Word
    • Why it’s helpful: Turn casual conversations into structured plans without starting from scratch.

    Try it:

    “Make a 30-minute meeting agenda from this conversation, including time estimates.”

    Final Tip: Start Small, Then Explore

    These prompts are just the beginning. As you get more comfortable, you’ll discover new ways to use Copilot to save time, reduce stress, and get more done.

    TechHouse

    Innovative Solutions. Practical Software. Friendly Support.

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  • Automation is More Than Emails: Part 2 –Driving Improvement with Proven Frameworks

    Efficiency is Essential

    Efficiency isn’t just a goal—it’s a necessity. This post will explore practical ways to boost business process efficiency. We will briefly discuss five common frameworks, their attributes, pros, and cons. We will provide examples of where they are commonly used. We’ll also discuss how TechHouse integrates these principles to drive our unique approach to business process efficiency.

    Common Ways to Tackle Process Improvement

    Reducing Waste and Variation: Focus on your data to make decisions that cut waste. This helps you find inefficiencies. Once in place, gathering enough data to spot issues and areas for improvement takes time. We often see this in large organizations with lots of data, like manufacturing, healthcare, and finance. This is a good approach to cut costs and boost quality. It can be complex and take time to set up.

    Iterative Development: Sometimes, knowing where to start is hard. We know there are problems, but it’s not clear where they are. This is common in fast-growing organizations where many people are new to the process. An iterative process lets us shift priorities as we learn more. This approach is common in small and fast-growing organizations. It is often used in areas with creative problem-solving skills, like product development and marketing. It requires a collaborative culture that can pivot quickly.

    Performance Measurement: This approach uses a scorecard to combine performance data from many areas and align it with set metrics. Mid-sized and large companies in finance, healthcare, and education use it. They have set their performance metrics but need help combining the data. Multiple departments must dedicate resources to set up and ongoing maintenance, which can be costly.

    Continuous Improvement: This approach focuses on ongoing improvement and customer satisfaction. The customer can be internal or external. Ensuring customer satisfaction requires engagement from all departments during setup and ongoing operations. For this reason, it’s often used in large enterprises or upper mid-market organizations and can be costly.

    Incremental Improvement: This framework is adaptable and collaborative. It focuses on small, ongoing changes. It’s used in mid-sized and large enterprises to achieve ongoing improvement across all organizational layers. It’s also effective in small, flat organizations that empower end users. Significant training and independent decision-making at all levels are needed, with controls to manage the freedom to make changes.

    The Right Fit for the Best Outcome

    At TechHouse, we know there’s no one-size-fits-all solution. Focusing on the most essential elements is critical, especially when working with small—to mid-sized businesses growing from a few employees to hundreds. Our Empower My Data division delivers process efficiency by using the key parts of each framework right for your organization. Our SafetyPlus team helps ensure those digital assets are safe. Contact us to work together toward better efficiency for your organization.

    TechHouse

    Innovative Solutions. Practical Software. Friendly Support.

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  • Automation is More Than Emails: Part 1 – Getting Started

    Efficiency is critical, but where do you start when juggling a million things? Let’s break down the process and roles needed to ensure it’s done right, efficiently, and in a way that makes sense for your organization.

    Four key concepts to understand before getting started are Project Triangle, Framework, Glossary, and the RACI model. Below is a summary of each.

    Project Triangle: Every project has three competing interests—time, budget, and features. Define the highest priorities and rank them 1, 2, and 3. Adjust as needed throughout the project, but remember that adjustments can increase cost and timeline and reduce features.

    Framework: Choose parts of frameworks that make sense for your business. You may have heard about Lean, Agile, and Balanced Scorecards – pick what fits your needs without overcomplicating things. Each provides a method to think about and solve problems (see our next post for more details on choosing the framework). For instance, Lean is great for manufacturing environments where waste reduction is key, while Agile is ideal for software development due to its iterative nature. Balanced Scorecards align what needs to be done with measures of what happened and how it affected the business.

    Glossary: Create a glossary of key terms for your business. Make sure everyone is on the same page. Even terms like “Total monthly sales” can mean different things to different people.

    RACI Model: Assign roles and enforce accountability. Early and often, communication is key. Clarifying R (Responsible) and A (Accountable) in smaller organizations can be tricky. R can have A, but A’s don’t always have R for that area – it’s more of an oversight role. C is a Consultant, and I is Informed. Changes in roles can affect the project triangle, so try to keep these stable.

    Real-World Examples: Over the years, we have found some common areas for improvement. One is refining the quote-to-cash process. This often involves a custom estimating process that starts highly manual, is not widely understood, and has poor visibility. By improving this process, multiple team members can see where the pipeline is, and operations can better understand what sales have committed to. Another common area is consolidating operational data to create meaningful invoices for clients. This often involves consolidating data from multiple entry points and systems. The process is typically manual and high-risk, again with limited visibility. By improving efficiency, there is more controlled transparency, accuracy, and efficiency – and clients are happier to receive richer invoices in a more timely fashion. These are just two examples of common improvements we see.

    Starting an efficiency or automation effort can seem daunting, especially when busy. To get started:

    • Identify the general area you would like to tackle
    • Work with an advisor to choose a practical framework
    • Prioritize your efforts with the project triangle
    • Clarify roles with the RACI Model

    Check out the next blog on this topic, where we dive into some of the different frameworks you can use to work through the efficiencies your organization needs. Ready to get started? Let’s make efficiency happen! Contact us today to learn how we can help you streamline your processes and achieve your business goals.

    TechHouse

    Innovative Solutions. Practical Software. Friendly Support.

    Schedule a call  |  View Upcoming Events  |  Access our TechHouse Library of Articles