AI isn’t just for tech companies or developers anymore. It’s for leaders, the kind that work in underserved communities, mission-driven teams, and nonprofits trying to stretch every dollar and hour.
That’s why, when we speak to non-technical leaders, we don’t focus on automation charts or development roadmaps. We show them what they can actually use right now without hiring a team of engineers.
In our work with purpose-driven organizations, we’ve noticed a pattern. Leaders are deeply aware of the challenges in their operations like the inefficiencies, the manual loops, the endless admin but feel stuck when it comes to solving them with technology.
Especially with AI.
They ask: Where do we start? What’s worth automating? What if we don’t have the team or the budget to go all-in?
Our answer is almost always the same: Start with discovery.
Before you jump into automation or AI tools or building custom systems, it’s essential to get clarity on what’s actually happening inside your organization. That means mapping out how your processes work today, not just how you think they work. That’s where the real value begins.
This article is about that first, crucial step: discovery.
Helping Nonprofits Use AI Without the Overwhelm
Most nonprofit teams we meet are curious about AI but don’t know where to start.
They’ve heard of ChatGPT or Claude. They’ve seen flashy demos. But the reality is:
- Their team is small.
- Their processes are messy.
- Their capacity is maxed out.
So exploring automation or AI just feels… unrealistic.
At Bitcot, we’ve started helping nonprofits in a different way, by showing what’s possible without pressure to build anything yet.
Recently, we’ve been engaging with multiple nonprofit leaders through speaking sessions and workshops. Not to pitch software or build workflows, but to demonstrate what’s available today with nonprofit AI tools.
These sessions focus on introducing accessible, powerful tools:
- Showing how ChatGPT or Claude can write better SOPs
- Using tools like napkin.ai to structure messy ideas
- Sharing pre-recorded agent demos to imagine “what good could look like”
- Offering prompt templates to use today with zero tech skills
These aren’t technical workshops. They’re practical “aha” moments that help teams realize:
“Wait… we can actually use this right now.”
Instead of training people on how to “build with AI,” we start with: “What are your three most repetitive, high-effort tasks?”
From there, we build prompt examples. For instance:
- “Create a Standard Operating Procedure (SOP) for volunteer onboarding based on these five bullet points.”
- “Analyze this donor list and suggest patterns in donation frequency by region.”
- “Turn this 20-minute board meeting transcript into a two-paragraph summary with action items.”
Tools like Claude and ChatGPT make this almost effortless. When you pair them with prompt libraries or pre-recorded agent demos, it becomes immediately obvious how accessible this technology really is.
Also Read: The AI Technology Shift is Here: What It Means for Your Business
These examples are intentionally non-technical – not about building, but about using. It’s a practical, human-first introduction to what AI can do for everyday processes.
What’s Next
And once leaders see what’s possible, the next step isn’t always “let’s build.”
It’s usually:
- “Let’s figure out what our process actually is.”
- “Let’s get everything documented.”
- “Let’s find out where automation makes sense.”
- “Let’s identify high-volume, high-value processes that are ripe for AI.”
That’s what our Discovery Engagement is for.
It’s a structured (and budget-friendly) way to help nonprofits go from messy processes to clear documentation so they can eventually automate with confidence.
These opportunities often start small. A nonprofit might want help documenting a process or identifying pain points or figure out what’s worth automating. Here, the goal is to extract what’s currently done manually, so it can be transformed over time.
Even if they don’t build with us right away, they leave with real value:
- Better estimates for development or automation
- Documentation that can be reused, even if budgets shift
- Clarity around exceptions, edge cases, and human decision points
- A shared understanding across the team
Who This Is For
- Nonprofits that want to explore AI but aren’t ready for development
- Organizations with manual processes they can’t quite describe or map
- Teams who need clear, visual documentation before starting automation
- Leaders who are using AI like ChatGPT and Claude but want more structure
- Anyone trying to understand where AI could fit without the pressure to build today
Bitcot’s Discovery Process
At Bitcot, an AI automation agency, we offer a valuable discovery process for potential clients. We take time to understand the systems you use, who touches what, where delays happen, and what success looks like if things just worked.
It’s not glamorous. But it’s effective.
Our process is structured but flexible. We’ve seen how hard it is for organizations to even articulate how a process works when it lives across email threads, verbal handoffs, or outdated manuals. That’s why we guide clients through it step by step.
Here’s what our discovery phase typically includes.
1. Stakeholder Interviews & Process Walkthroughs
We start with conversations:
- What’s the top process that’s painful or repetitive?
- What takes too much time? Who’s involved? What systems do they use?
- Where are the bottlenecks or repetitive tasks?
Then we ask your team to show us what they actually do, live in their systems.
2. Live Observation
People often forget key steps. Not because they don’t matter, but because they’re second nature. That’s why we observe these tasks as they happen, ideally with all stakeholders in the room. Nothing gets missed.
3. Flow Mapping
After listening in on how your team currently works, we flow it all out visually. Our team maps the entire workflow using tools like Lucid, Miro, or Eraser.
This does two things:
- Gives your team a clear, shared understanding of what’s really going on
- Becomes the foundation for future automation or AI-assisted support
Then we go back to your team and say: “Here’s what we saw. Did we get it right?”
If not, we update it until it matches how your work really flows.
4. Document & Tool Collection
From there, we can explore what tools could reduce friction, whether that’s an AI transcription tool, a chatbot, or a lightweight Power App to replace a shared Excel sheet.
If the workflow involves documents, third-party apps, or tools, we’ll request sample files or access. This helps us understand:
- Inputs and outputs
- Format and structure
- Integration opportunities for automation
5. Optional Proof of Concept (POC)
Sometimes a POC can be developed in parallel, depending on what’s needed.
Depending on the workflow, we may build a lightweight proof of concept behind the scenes using:
- Power Automate
- Azure AI
- Custom APIs or internal tools
We’ll walk through how automation could look, even before full implementation.
6. Interface Wireframes (If It Makes Sense)
If the workflow touches software that needs a user interface, like a chatbot, mobile app, or internal portal, we design wireframes showing:
- What users will see
- What actions they can take
- How it fits into the flow
Especially useful for Power Apps, chatbots, or custom dashboards.
7. Clarifying Edge Cases & Exception Paths
After we’ve mapped the happy path, we circle back to capture exception paths: “What happens when things don’t go as expected?”
This ensures the automation won’t fail at the first fork in the road.
What You Get Out of It
The discovery work typically runs for about three weeks as a paid engagement, giving your team the clarity to make informed decisions before diving into build mode.
This isn’t just paperwork and diagrams. It’s a collaborative working session that connects your team’s knowledge with our process expertise.
Our goal in this stage is simple: Reflect back what your team already knows but hasn’t fully documented, and organize it into something visual, structured, and ready for what’s next. We help you uncover where AI, automation, or smarter tooling can make a measurable difference, and show you how.
We know how a structured discovery process can completely change the trajectory of a project. It turns assumptions into facts and lays a foundation that makes every step that follows smoother, faster, and more aligned.
Also Read: How to Hire AI Developers for Your Business: A Practical Guide for 2025
Even if you don’t automate tomorrow, the clarity you gain today is foundational.
- A visual map of how things actually work
- Clarity on what’s causing the most drag
- A clear direction on what to fix, and how
- Optional wireframes or proof of concept to build momentum
- A structured, visual foundation for long-term improvement
This kind of upfront clarity saves time, money, and internal misalignment down the line.
Also, the type of organization doesn’t really matter. Nonprofits are just one example. Across the board, the challenges are similar: people are stretched thin, juggling too many tasks, and trying to figure out better ways to work without adding complexity.
Most of the audiences we speak to are in non-technical leadership roles, and the core challenges are the same.
For Businesses, Time is a Resource. AI Discovery Gives You More of It.
We’ve seen the impact firsthand.
One organization we worked with saved over 200 hours every month (mostly in repetitive admin and transcription work) using just Power Automate and a few off-the-shelf AI integrations.
Discovery made it real.
We don’t just build; we help you think through it.
So, if you’re a leader wondering how to get started with AI (without the pressure to become a technologist), here’s what we recommend:
- Start small. Pick one process you wish could run smoother.
- Use tools like ChatGPT and Claude to explore what’s possible.
- Document it. Diagram it. See what you’re really doing.
- If you need help translating that into automation or a custom tool, we’re here.
You don’t need to become an AI company. You just need to use AI like a modern organization.
Enterprises already know this. That’s why many of them spend $250,000 to $500,000 just on discovery. Big consulting firms can charge more than that just to map out what a company already knows about itself. That’s not realistic for most organizations, and honestly, it doesn’t need to be.
Also Read: Difference Between AI, Machine Learning, and Deep Learning
At Bitcot, we believe businesses shouldn’t have to spend enterprise-level budgets just to understand their own processes.
That’s why our discovery engagement is intentionally designed to be lean, focused, and accessible, without compromising on depth.
We offer a smaller version of it, designed to surface opportunities, especially around AI and automation, without overwhelming your team or your budget.
For a fraction of what big firms charge, we’ll help you:
- Deliver better, tighter estimates
- Avoid scope creep
- Create reusable assets, even if development is delayed
- Improve internal alignment
- Spot process gaps and inefficiencies
Here’s how we approach it:
We Start Light, Then Get Direction
If you’re not sure where to begin, we offer a lighter version of discovery to help identify high-impact opportunities. You’ll leave this initial session with direction, not just ideas.
We Ask the Right Questions
Whether your pain points are in marketing, operations, sales, or admin, we start by asking targeted, high-level questions about your current processes. As the conversation evolves, we dig deeper, uncovering gaps, delays, redundancies, or missed handoffs that slow your team down.
We Connect the Dots to Automation & AI
Once we understand where time is being lost or manual effort is dragging things down, we pinpoint where AI or automation can step in. You don’t need to figure out the tech, that’s our job. You just need to help us understand the friction.
We Make It Visual
Your process won’t live in a Word doc. We translate your current workflows into simple visual maps or flowcharts. These help your team align internally, see the inefficiencies more clearly, and build momentum toward fixing them.
We Deliver Clarity, Not Complexity
At the end of this 2–3 week engagement, you’ll walk away with a clear view of how your operations really work, where things can improve, and what a smarter, more modern system could look like.
That’s how you go from “we should do something with AI” to “this is exactly what we’ll fix first.”
Know What to Build and What Already Exists
One of the most common moments we see in early discovery calls is this: A business leader explains a challenge they’re facing. Halfway through, we realize there’s already a tool for that.
It’s not that they’re wrong. It’s that they don’t know what’s out there.
If there’s a problem, like struggling to train new hires effectively, it’s tempting to jump straight into solution mode. But often, the smartest first move isn’t solving the problem at all. It’s documenting it.
More often than not, people are trying to build something that already exists. Maybe they want a dynamic onboarding experience with quizzes and progress tracking. They might not realize that tools like Trainual or other purpose-built platforms already handle that brilliantly.
In the beginning, it’s not about the tech. It’s about understanding how you currently work, what your ecosystem looks like, and how open you are to adopting new tools.
Some people are burnt out on “yet another app.” In those cases, plugging automation into tools they already use, like Power Automate or integrations within Microsoft 365, can be more effective than introducing something completely new.
When you bring a challenge to Bitcot, our first move isn’t to pitch a custom app. Instead, we listen, document your workflows, and help uncover what’s actually happening inside your business today. We start with questions because those open the door to relevance.
From there, we go into live demos, real use cases, and our favorite productivity and AI tools.
During our sessions, we often walk through:
- Business Use Cases: Strategy, content, sales, operations, HR, customer support
- Personal Productivity Boosters: Time management, smarter research, decision-making
- Tech Stack Insights: Claude, ChatGPT, Power Automate, Notion, Google tools, and more
- Customization Tips: How to personalize AI tools for specific departments or goals
- Visualizations: Turning processes into editable flowcharts or AI-powered SOPs
Here’s where we really add value: we help you understand not just what tools could work, but how well they’ll fit into your ecosystem.
A big part of our work includes educating non-technical leaders, especially operators and decision-makers, understand what AI can actually do for them.
They don’t need more theory. They need 10-12 practical things that make them say:
“Wait. I didn’t know I could do that.”
This is the part that surprises people the most.
They don’t know that Claude can upload and reference hundreds of pages of Google Docs. They don’t know you can set up persistent memory in ChatGPT. They don’t know there’s a canvas mode. Or why toggling web search or enabling certain modes makes a huge difference. Or that you can customize the behavior of your assistant completely.
These seem like small hacks to experienced users, but for many people, it’s a game-changer.
If we’re working with business owners, we go deeper into Claude. We show how to build custom projects like:
- A marketing assistant that pulls from real company data
- A training SOP builder with live company documents
- A strategy bot that knows their business goals and can suggest campaigns
Also Read: How AI Workflow Automation Can Modernize Your Business in 2025
Uploading docs, creating instructions, and building persistent workspaces is something Claude does better than most platforms, and it really clicks with audiences once they see it live.
You don’t need to be technical. You just need to be curious and ready to rethink how work gets done.
Final Thoughts: Your Process Is the Product and We Help You See It
We tell every team this: You don’t need to automate today. But you do need to understand your process clearly for the first time because that’s where digital transformation starts. You just need to take the first intelligent step.
That’s what discovery gives you: the confidence to move forward, knowing you’ve grounded your vision in real operational insight.
And when the time comes for something more, we want to be their first call.
Whether it leads to a custom chatbot, a Power App, or a workflow built on Power Automate, Bitcot offers full implementation as a next step. Our philosophy is simple: start where the team is, and help them move forward with confidence.
If this speaks to you, or if you want help documenting your process or exploring what’s possible, we’d love to chat.
If you’re a non-technical leader curious about what AI can actually do, without building anything yet, Bitcot is here to help you explore that.
Let’s map your process, explore real tools, and show what’s possible.
Start your discovery with Bitcot. We’re here when you’re ready.
