Key Takeaways

• AI does not replace people; it replaces busywork.
• The best AI productivity in the workplace comes from clear, contextual prompts.
• Paid AI tools protect your data and maintain compliance.
• Start small and share early successes to build momentum.
• Productivity is not the goal; purpose is.

When I began my recent presentation for Philanthropy Colorado’s Human Resources and Operations Network, I opened with a question that always breaks the ice.

“What is your favorite question to ask AI?”

The responses came quickly.

One person said, “I ask it to make my emails sound like I am less stressed.”
Another said, “I tell it to summarize my grant reports, but I never trust the answer.”
Someone else admitted, “I have never asked AI anything because I have no idea what to say to it.”

Those three answers perfectly captured the range of where most professionals are today with AI productivity in the workplace. Some are cautiously experimenting. Some are already testing how tools like Microsoft Copilot and ChatGPT can make their daily work easier. Many are still standing at the edge, curious but hesitant to take the first step.

That hesitation is understandable. For many people, AI still feels like an unfamiliar force that belongs in the world of data scientists, not in the world of HR, philanthropy, or operations. However, as I told the group that morning, the real opportunity of AI has nothing to do with replacing people or automating humanity out of work. It has everything to do with helping people reclaim their focus, energy, and creativity.

The future of work will not be defined by who uses AI. It will be defined by who learns to use it well, and who chooses a truly human-centered AI adoption approach.

The Real Fear Behind the Buzz

Before we even moved to the demonstration portion of the session, one audience member raised a hand and asked the question that surfaces almost every time I speak on this topic.

“Should we be worried that AI is going to replace our jobs?”

It was a sincere question, not a cynical one, and I respected the honesty behind it.

I told her what I have told dozens of teams before. AI does not replace the human parts of your job. It replaces the tedious parts.

AI can write a first draft, summarize a report, or analyze survey data faster than any of us ever could. What it cannot do is understand the nuance of a community, feel empathy for a coworker, or make a decision that balances compassion with accountability.

That distinction matters more than anything. Because when you remove the repetitive or administrative tasks that consume hours of your day, you do not erase the human element of work. You amplify it.

At Pisteyo, our entire philosophy is built around this balance. AI should never be the goal. It should be the tool that clears the path.

When AI takes care of the routine, people can return to purpose.

From Overwhelmed to Empowered AI Improves Productivity in the Workplace

Many of the leaders attending the session work in HR, operations, or administration for philanthropic organizations and nonprofits. These roles are complex and demanding. They involve managing compliance, communication, reporting, training, and people all at once.

During the session, I asked the group to describe the kind of work that drains their energy the most. The responses were nearly universal: endless emails, repetitive updates, data tracking, and writing reports that few people read in full.

One participant described spending half a day each week writing updates for the leadership team. Together, we opened ChatGPT, gave it a clear prompt, and within sixty seconds it generated a strong draft that captured her main points in a professional, friendly tone. She laughed and said, “That just gave me back my Friday afternoon.”

That small win is exactly what human-centered AI adoption looks like in practice.

AI does not need to reinvent your workflow or overhaul your systems overnight. It only needs to make your day a little easier. The key is to start small, solve one bottleneck, and let the time savings build from there.

The Learning Curve Myth: ChatGPT for HR and Operations

Halfway through the presentation, someone unmuted to ask a question that I always love hearing.

“Shawn, I like the sound of all this, but I barely have time to get through my emails. I do not have time to learn a new tool.”

That is one of the most common objections I hear, and it comes from a very real place.

The good news is that AI tools today are not difficult to learn. In fact, you already know how to use them because they live inside the systems you already work with.

• Microsoft Copilot integrates directly into Word, Excel, Teams, and Outlook.
• ChatGPT for HR and operations runs in your browser and communicates in plain language.
• Google’s Gemini lives inside Gmail and Docs.

You do not have to code. You just have to communicate clearly.

Using AI is not about mastering commands or memorizing technical jargon. It is about giving clear direction, the same way you would with a colleague or a new team member.

If you can say, “Summarize this meeting into five key points and identify next steps,” you already know how to talk to AI.

The learning curve is not technological. It is psychological. It requires us to be clear about what we want and what a successful outcome looks like.

The Trust Question: Keeping Humans in the Loop

Later in the discussion, a participant shared a story that made everyone nod.

“I tried ChatGPT once,” she said. “It wrote a really nice paragraph for my grant application, but when I checked the facts, half of them were wrong. How can we trust it?”

Her frustration was valid. AI can sound authoritative even when it is incorrect. It does not understand truth the way humans do. It predicts what sounds right based on patterns in data.

This is why I always emphasize that AI is not a replacement for judgment. It is a drafting partner.

AI can do the heavy lifting, but people must still provide verification, insight, and context. The best results happen when humans and machines work together, each doing what they do best.

I told the group to think of AI as an incredibly fast intern. It can generate a first draft or outline, but it still needs your experience to make it accurate and meaningful.

AI drafts. Humans decide.

The Data Security Question and Microsoft Copilot for Nonprofits

Another audience member asked what everyone else was thinking but hesitant to say aloud.

“Is this actually safe? We handle sensitive data from employees and grantees. I cannot risk that information being exposed.”

That question gets to the heart of responsible and human-centered AI adoption.

If you are using free, consumer versions of AI tools, you should always assume that your input could be stored or used to train future models. That does not necessarily mean your information will become public, but it does mean you should not enter anything confidential.

However, enterprise-grade tools are a different story. Microsoft Copilot for nonprofits, ChatGPT Enterprise, and Google Gemini for Workspace all include strict privacy controls. They are compliant with security standards such as SOC 2 and HIPAA, and they respect your organization’s existing file permissions.

The rule of thumb is simple: if you are not paying for the product, you are the product. Paying for AI ensures your data remains your own.

Responsible AI is not only about technology. It is about culture. It means communicating openly with staff about what tools are being used, why they are being used, and how data is protected. Transparency builds trust.

Real-World Applications of Human-Centered AI

Once we addressed those foundational concerns, the energy in the virtual room changed. The questions shifted from “Is this safe?” to “What can we do with it?”

That is when the session became fun.

I shared several real examples of how organizations are already using AI to improve personal and team productivity in the workplace.

1. HR Support Chatbots

One foundation implemented a simple internal chatbot that answers common employee questions such as “What holidays do we have off?” or “How do I access the new benefits portal?” Within two months, their HR inbox volume dropped by 40 percent. The HR team was able to focus more on professional development and culture rather than administrative repetition.

2. Personalized Onboarding

A regional nonprofit used Microsoft Copilot to create customized onboarding packets for new employees. Each packet automatically included the right policies, role descriptions, and training links for that specific position. What used to take hours of manual editing now takes ten minutes.

3. Grant Report Summarization

Another organization used ChatGPT to summarize multi-page grant reports into concise executive summaries. They could quickly extract key metrics, outcomes, and quotes for board meetings. This allowed leadership to review information more effectively and make faster funding decisions.

4. Meeting Notes and Action Items

Teams using Copilot in Microsoft Teams no longer spend time taking notes during meetings. The tool automatically generates a transcript, identifies decisions, and lists next steps. Every participant receives the summary immediately after the call, which increases accountability and clarity.

5. Survey and Feedback Analysis

AI can read through hundreds of open-ended survey responses, categorize comments by theme, and highlight recurring issues. This kind of analysis used to take weeks. Now it can be done in hours, giving organizations near real-time insight into employee or grantee sentiment.

As I walked through these examples, people began sharing their own ideas in the chat:

“Could it write job descriptions?”
“Could it help organize volunteer data?”
“Could it translate policy updates for our bilingual staff?”

The answer to all three was yes.

Once people experience a single useful AI task, they start to see possibilities everywhere.

The Power of a Well-Asked Question

One of the most important lessons I try to leave with every group is that AI is only as useful as the question you ask it.

We spent the last two decades learning how to Google. We type a few words, hit search, and hope we find something relevant. AI works differently. It is not a search engine. It is a collaborator.

When you prompt an AI tool, you need to give it a role, a goal, and some context. For example:

“Act as an HR manager at a mid-sized foundation. Write a three-paragraph memo explaining the new hybrid work policy to employees. Keep the tone friendly and clear.”

That is a good prompt. It sets direction, tone, and purpose. The more detail you provide, the more accurate and personalized the output becomes.

One audience member said, “So it is like having a really smart assistant, but only if you give it a good briefing.”

Exactly. That is what prompt engineering really is: clarity of thought.

When you practice explaining what you want to an AI tool, you also become clearer about what you need for yourself. It sharpens your thinking and forces you to prioritize outcomes.

Where to Begin with AI Productivity in the Workplace

As we moved into the final part of the session, one participant asked a practical question that summed up the mood of the group.

“If I want to introduce AI to my team, where do I even start?”

I told her the same thing I tell every leader who asks. Start small, start safe, and start with something that actually makes your day better.

Choose one process that is repetitive but necessary, such as writing weekly updates, organizing notes, or creating templates. Test AI on that one process and measure the result.

• Did it save time?
• Did it maintain quality?
• Did it free your team to focus on higher-value work?

If the answer is yes, share that success with others. Small wins are contagious.

The goal is not to implement AI everywhere overnight. The goal is to build a culture of experimentation and learning.

When people see AI as a helpful teammate instead of a looming threat, adoption happens naturally.

From Efficiency to Meaning: Human-Centered AI Adoption

As the conversation wound down, one of the attendees shared a comment that perfectly captured why we were there.

“If AI can give me back time, I want to use it for the human parts of my job: coaching, connecting, and building trust.”

That is the essence of it.

Efficiency is valuable, but efficiency without meaning just makes you faster at being busy. The real purpose of AI is to remove the noise so we can focus on what matters.

In the nonprofit and philanthropic sectors, that means spending less time formatting spreadsheets and more time listening to communities, mentoring staff, and advancing missions.

When AI handles the tasks that weigh us down, we regain the mental space to think strategically, creatively, and compassionately.

At Pisteyo, we call this the human advantage. AI is not here to make people irrelevant. It is here to make people indispensable.

How to Begin Your AI Journey

If you are wondering how to get started, here is the roadmap I shared with the Philanthropy Colorado group.

1. Identify Your Pain Points
   Start with the tasks that feel repetitive or time-consuming. AI thrives on routine and structured work.
2. Experiment with Purpose
   Do not delegate critical decisions to AI. Use it to draft, summarize, organize, and analyze so humans stay in charge of judgment.
3. Choose Secure Tools
   Invest in enterprise-grade AI platforms that prioritize privacy and data protection, such as Microsoft Copilot for nonprofits or ChatGPT Enterprise.
4. Empower Early Adopters
   Identify curious team members and let them lead small pilot projects. Capture their stories as proof points.
5. Measure the Results
   Track time saved, accuracy improved, and satisfaction gained. Use those metrics to inform broader rollout and to tell a compelling story to leadership and boards.

Transformation does not happen from a single workshop or a single software purchase. It happens when curiosity turns into confidence and confidence turns into culture.

About the Author

Shawn Mills is the CEO of Pisteyo, a management consulting firm that helps organizations harness the power of artificial intelligence to improve operational efficiency, drive innovation, and enhance human impact. With more than two decades of experience leading technology and management transformations, he believes the future of AI is not about replacing people with machines, but about giving people the tools to achieve extraordinary outcomes.

A Note of Thanks

A heartfelt thank you to Sophie Stewart-Lopes and Erika Fukahara of Philanthropy Colorado for inviting me to speak with your incredible network of HR and Operations professionals. Their thoughtful questions, openness to learning, and commitment to collaboration made the conversation truly meaningful. It is always inspiring to see professionals who care deeply about using innovation not only to improve efficiency, but to expand impact and strengthen community. I am grateful for the opportunity to be part of it.