Your Company is Using AI — Here’s Why It’s Not Moving the Needle
By Toni Mays, Founder of Mozman AI Consulting
The promise is everywhere: AI will increase your profitability, boost efficiency, and take your revenue to new levels. And yet, you've probably also seen the headlines saying that 95% of organizations implementing AI aren't seeing returns. Even Jeff Bezos recently said we're in an AI bubble where it's hard to tell the good ideas from the bad ones.
So what's the truth? And more importantly, how do you make AI work for your business instead of becoming another expensive experiment?
The Real Problem Isn't the Technology
Here's what I've learned working with businesses like yours: when AI initiatives fail, it's rarely because the technology doesn't work. It's because of how it was implemented.
The gap between what leadership wants and what gets adopted is where most AI projects die. Your team might resist the change. The solution might not fit how work gets done. Or nobody takes ownership of making it work.
The good news? This is fixable. You just need to think about three things before you start:
1. Business Outcomes: Know What Problem You're Actually Solving
Don't start with "let's add AI to our business." Start with "what's slowing us down or costing us money?"
Look for the cascading effects of broken processes:
Revenue delays – Proposals sitting in someone's inbox for days while a potential customer waits
Customer frustration – Slow response times that cost you deals
Employee burnout – Your best people stuck doing repetitive work instead of growing the business
Inconsistent quality – Different results depending on who handles it
Hidden costs – Time spent redoing work, fixing errors, or managing handoffs between people
Yes, repetitive tasks are good candidates for automation. But the real ROI comes from fixing processes where these cascading effects are costing you real money and real opportunities. When you focus on business outcomes first, it's much easier to measure whether your AI investment is actually paying off.
Start small. Pick one specific problem, solve it, validate that it's working, then expand. Don't try to automate everything at once.
2. The Tech: Choose Tools That Meet You Where You Are
Once you know what problem you're solving, you need to figure out how to solve it. There's no single right answer here, but there is a right approach: run the numbers first.
Calculate how much revenue or time you'll gain from automation. Then compare that to what it will cost to build and maintain. This isn't complicated math – it's just being honest about the investment versus the return.
A few questions to ask yourself:
Do we have technical capability in-house to build and maintain this, or do we need outside help?
Who will monitor and adjust the solution once it's running?
Are we building something flexible enough to change as we learn what works?
Don’t overengineer your initial solution: you probably don't need to build something custom from scratch right out the gate. Low-code and no-code automation tools are getting better and more accessible every day. The barrier to entry keeps dropping. Don't assume you need to spend hundreds of thousands of dollars to get meaningful results.
3. The People: Get Your Team on Board (Or It Won't Work)
This is the most important pillar, and it's where most initiatives fall apart.
Having executive vision isn't enough. You need buy-in from the team members who will use the tools. That means:
Identifying a champion in each department where you want to implement AI
Including your team in the process of building or choosing the solution
Providing comprehensive training that addresses their concerns
Making them feel like part of the decision, not victims of it
People are hesitant. They worry AI will replace them. They'll find reasons why "this specific task must be done by a human." These concerns need to be addressed, or they have the potential to become your biggest roadblock.
I've seen this play out in real time. One client was looking to scale their sales team quickly - a potential $20M increase in annual revenue. They were getting multiple resumes daily, but the screening process bottlenecked through one person who was also responsible for other operational areas.
We built a solution to help them filter resumes faster and give them time back for their other work. But instead of embracing it, they continuously requested changes to the requirements and singled out specific resumes, arguing why each one needed their judgment. The solution worked fine - the person was protecting their territory.
Moving Forward: Slow Down to Speed Up
If you try to move too fast, skip steps, or overlook any of these three pillars, you'll end up with a solution nobody uses or one that doesn't really solve your problem.
Ironically, all the talk about an AI bubble is helpful right now. It's a reminder to slow down and do this right. Organizations that rushed in are struggling to justify their investments. You have the advantage of learning from their mistakes.
This is an excellent time to move thoughtfully – to identify the right problems, choose the right tools, and bring your team along with you. Do that, and you'll see the efficiency gains and revenue growth that AI promises.
Start with one small, yet high-impact use case. Get it right. Then expand from there.
Want to Go Deeper?
At Mozman AI, we help companies avoid the AI implementation trap by focusing on what matters: solving real problems with the right tools and getting your team on board.
Want to learn more? Click here (link: https://www.mozmanconsulting.com) to find out how we can help you join the 5% that see real ROI.
Toni Mays is the Founder of Mozman AI Consulting and expert in Artificial Intelligence. She has 20+ years of experience in technology, with the last 6 years focused specifically on helping organizations use AI effectively. As the founder of Mozman AI Consulting she's helped everyone from small nonprofits to large companies find practical ways to save time and money with automation.
All written content is for information purposes only. Opinions expressed herein are solely those of Mozman AI Consulting. Material presented is believed to be from reliable sources; however, we make no representations as to its accuracy or completeness. All information and ideas should be discussed in detail with your individual adviser prior to implementation. Advisory services are offered by Summit Hill Wealth Management, LLC a Registered Investment Advisor in the State of Colorado. Mozman AI Consulting and Summit Hill Wealth Management, LLC are owned and operated independently of one another and are unaffiliated entities.