AI: Friend, Foe, or a Faster Intern?
"If nature teaches us anything, it’s that growth without balance leads to collapse. RevOps can harness AI as one element in a broader ecosystem: integrated, intentional, and human-centered.
—Jenny Kelley, Fractional Revenue Operations Officer & Co-founder, Synthesis RevOps
Why Organizations Can't Afford to Ignore Artificial Intelligence (Even If It Freaks Us Out a Little)
AI is having a moment. Depending on who you ask, it’s either the future of business, the end of humanity, or a really good way to never have to write another follow-up email again.
And here at Synthesis RevOps, we get it, really. We’re system people and people people. We build ecosystems that blend tech, team, and tone in ways that feel organic (yes, even when they’re automated). So we’re not jumping on the AI bandwagon for fun, we’re walking alongside it, cautiously optimistic, ethically grounded, and fully aware it could veer off a cliff if we’re not paying attention.
So let’s talk about it...the pros, cons, and bottom-line, why AI has to be part of your operational future, especially if you care about doing good work and growing in ways that don’t burn everyone out.
First, a Gut Check: Why AI Feels So Loaded
We’re not just talking about tools here, we’re talking about trust.
AI pokes at a primal nerve:
Will it replace my team?
Will it make me irrelevant?
Can we still be creative if some of the work is done by a machine?
Here’s our take:
AI isn’t replacing your team, it’s replacing the parts of their job they secretly (or loudly) hate.
Used well, it unlocks capacity, sharpens focus, and frees up human energy for human work, the kind that requires empathy, creativity, strategy, and nuance.
The Pros of AI (Especially When You’re Growing Smarter)
It scales your time without scaling your team
Draft emails, transcribe meetings, summarize notes, schedule workflows… in seconds.
That’s not soulless, that’s leverage.
It makes your data actually usable
Most teams are drowning in data and starved for insight.
AI can surface patterns, forecast trends, and help you act before things break.
It boosts creativity (yes, really)
AI is a first-draft machine, not a finished-product generator.
When used intentionally, it helps teams explore more ideas, faster.
It supports equity
Thoughtful automation creates consistency across experiences, no more luck-of-the-draw customer support or sales follow-up.
It enables truly personalized experiences at scale
When you combine AI with solid RevOps infrastructure, your emails, workflows, and campaigns feel human, even if they’re partially generated by machine.
The Cons (Because We’re Not Here to Hype, We’re Here to Help)
Garbage in, garbage out
AI reflects the systems (and biases) it’s trained on. If your data is messy or your values aren’t baked into your prompts, expect noise, not magic.
It can depersonalize if misused
Automation ≠ disconnection. Poorly designed AI flows feel robotic, intrusive, or worse, out of touch.
It can widen the digital divide
Not every team has equal access or understanding of AI tools. Without thoughtful implementation, you risk deepening inequities.
It threatens trust if not transparent
People want to know when they’re talking to a bot. Transparency builds confidence; trickery breaks it.
It’s not impact-free
Behind the magic, AI still relies on energy-hungry servers and water-intensive cooling. While cloud infrastructure is evolving, the environmental toll of training and running large models is real—and easy to overlook. Responsible use means balancing automation with sustainability, not just scalability.
Did you know the term Artificial Intelligence was coined in 1956. AI’s origin story began at a college workshop with a few brilliant minds, some big ideas, and probably way too much black coffee. So, chatbots might be cutting-edge, but the concept of AI is older than Post-it notes and the moon landing.
The Synthesis POV: Cultivate AI, Don’t Just Deploy It
In nature, healthy ecosystems are adaptive. They don’t over-optimize for speed or scale, they balance growth with resilience, interdependence, and renewal. That’s how we view AI:
AI should be woven into your revenue ecosystem like a mycelial network: unseen but vital, constantly learning, and always in support of the whole.
At Synthesis, we help you:
Use AI to amplify human creativity, not suppress it
Design workflows that are automated and empathetic
Build systems that reflect your brand’s voice and values, even when machine-assisted
Because technology doesn’t create disconnection, misaligned systems do.
Putting Sustainability Concerns in Context
It’s true, AI, especially during training, can be resource-intensive, using large volumes of water and energy. But so is everything else we rely on: video streaming, cloud storage, and even daily email use.
Water Use: AI vs. the Internet
Training large AI models like GPT-3 has drawn criticism for water use. One estimate found GPT-3 consumed over 700,000 liters (185,000 gallons) of water—roughly equal to what four U.S. households use in a year during its training phase (University of California Riverside, 2023).
But it's important to note:
Most of this usage comes from initial training, not daily use.
AI inference (day-to-day use like generating emails or insights) uses far less water than training
This water use is often for evaporative cooling, which is more energy-efficient than traditional cooling systems.
By comparison, streaming one hour of Netflix can use up to 100g of CO₂ emissions (International Energy Agency, 2020)—and streaming adds up continuously, unlike the front-loaded AI training process.
Energy Use: Efficiency Is Improving
Early studies (such as Strubell et al., 2019) noted that training large AI models could emit carbon comparable to five gas-powered cars over their lifetimes. But here's the good news:
Cloud providers are rapidly transitioning to greener data centers. Google Cloud and Microsoft Azure both aim to operate on 100% carbon-free energy by 2030.
Many newer AI models are trained more efficiently and require far less compute power.
As AI migrates to cloud-native, shared infrastructure, it may actually be more sustainable than current fragmented systems.
In other words, using AI responsibly today—especially in the cloud—can be comparable to, or even better than, many traditional digital systems, especially when paired with smart automation that reduces human inefficiency.
The Synthesis View: Use with Intention, Design for Balance
At Synthesis RevOps, we think of AI the way we think of any system:
Not good or bad—just powerful. And power needs stewardship.
Ways to make AI more sustainable:
Use AI for leverage, not laziness | Don’t run 10 prompts when 1 thoughtful one would do.
Choose partners with green data centers | Some cloud providers offer carbon-neutral or water-conscious hosting.
Balance automation with simplification | Sometimes, streamlining a process without AI is the most sustainable move of all.
Bottom Line: AI Isn’t Optional. But How You Use It Is.
The businesses and nonprofits that will thrive in this next era won’t be the ones that just use AI. They’ll be the ones that use it intentionally, to reduce friction, increase focus, and make more space for meaning.
So don’t be afraid of AI. Be curious. Be careful. And most of all, be human about it.
Wondering How AI Can Help Your Organization? Small Org, Big Impact: How AI Boosts Capacity on a Budget
AI isn’t just for enterprise. It’s a powerful tool for small businesses and nonprofits that want to punch above their weight, especially across lean teams. Here’s how:
Marketing
Scenario: A small nonprofit with one marketing coordinator
Use Case: Use ChatGPT or Jasper to write blog posts, social captions, or fundraising emails in minutes instead of hours.
Result: Increases content output 3–5x without hiring a copywriter. Source: https://www.jasper.ai/
Sales
Scenario: A 2-person sales team in a small B2B startup
Use Case: Use AI-powered CRM tools like Go High Level or HubSpot AI to automatically follow up with leads, summarize sales calls, and qualify prospects based on intent data.
Result: Reduces admin time by ~30%, allowing reps to focus on closing. Source: https://blog.hubspot.com/sales/ai-sales-tools
Operations
Scenario: A nonprofit that manages multiple grant deadlines and reporting cycles
Use Case: Use AI-powered project managers like Notion AI or ClickUp AI to draft grant reports, generate task lists from meeting notes, or send automated reminders.
Result: Saves hours in task planning and documentation, reduces burnout. Source: https://www.clickup.com/blog/ai-tools/
Customer Success / Support
Scenario: A small service business with one part-time support rep
Use Case: Use a chatbot trained on your FAQ + CRM to answer basic inquiries, escalate complex issues, and summarize conversations for follow-up.
Result: 24/7 support availability without 24/7 staffing. Source: https://intercom.com/blog/ai-in-customer-service/
Whether you’re writing emails or managing relationships, AI doesn’t replace your team, it multiplies their impact.
Want help integrating AI into your CRM or campaign workflows without losing your soul (or your sanity)?
Let’s design something intentional together. Contact us.
