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AI strategy consulting helps companies identify where AI can add real value.
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Focus on solving problems and pain points, not the technology.
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Focus on automating repetitive tasks and ensuring team alignment.
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Use solutions that fit your existing systems, not the other way around.
AI is everywhere. You can’t scroll through LinkedIn without seeing another post about how it’s “transforming business” or “revolutionizing workflows.” But here’s the thing, most companies are still trying to figure out where to actually start.
AI strategy consulting is exactly what we tackled in our recent webinar with Jeff Maynard, VP of Administration at Cope Plastics and Scott Litman, SVP of GTM here at Capacity. Together they sat down to talk about the real challenges of bringing AI into your business and how to identify opportunities that actually move the needle.
What are we talking about when we say AI?
When we talk about AI today, we’re really talking about generative AI, the technology that can create content, answer questions, and automate complex tasks. This isn’t the AI that’s been powering Google searches for the past 20 years. This is the stuff that can draft emails, analyze documents, and handle customer inquiries in real-time.
The shift happened fast. ChatGPT launched, and suddenly everyone realized that AI wasn’t just for tech giants anymore. It’s accessible, powerful, and ready to solve real business problems. Plus, the AI market is expected to grow over 30% every year and reach a whopping $1,811.75 billion by 2030.
Do I need AI strategy consulting?
Here’s where most companies get stuck. AI sounds great in theory, but when you’re staring at your business operations, it’s hard to know where it fits.
Jeff put it perfectly: “AI has become the buzzword, the topic of conversation, the topic of a lot of consternation.” He’s been in IT for 35 years, and even with that experience, figuring out how to implement AI strategically was a challenge.
The problem? Everyone’s trying to force AI into their business instead of finding where it naturally fits.
Scott shared a framework that changes this approach entirely: Start with the problem, not the technology.
How do you find new opportunities for AI tools at work?
While it can be difficult to conceptualize exactly how new AI tools can help you lower costs or work more productively, there are emerging AI strategy consulting frameworks like Capacity’s AI Assessment that can help you think about where to start and how to scale. Here’s how to think about it:
1. Identify pain points first
Don’t start by asking “Where can we use AI?” Start by asking “What’s slowing us down?” or “Where are we losing time and money?”
For Cope Plastics, one of those pain points was customer service. They were getting the same questions over and over, questions that didn’t require a human expert but were eating up valuable time.
2. Look for high-volume, repetitive tasks
AI excels at handling repetitive work. Think about:
- Customer inquiries that follow similar patterns
- Data entry and document processing
- Internal knowledge searches
- Routine approvals and workflows
Jeff mentioned that after attending a conference and seeing what AI could do, he came back thinking, “We gotta start formulating a plan on how we’re gonna bring these things in. But we don’t want the tail wagging the dog. We want to find those places where we need a solution.”
3. Consider organizational alignment
This is huge. You can have the best AI solution in the world, but if your team isn’t on board, it’s going to fail.
Scott emphasized that digital transformation requires alignment across the organization. That means:
- Getting buy-in from leadership
- Training your team on new tools
- Setting clear expectations about what AI will and won’t do
- Addressing concerns about job security head-on
4. Start with a technology-agnostic AI strategy
One question from the webinar audience was particularly insightful: “Is the assessment technology agnostic, or is it capacity-centric?”
Jeff’s answer? Technology agnostic.
He explained that Cope Plastics is a huge Microsoft shop, heavily invested in Copilot and Azure. He wasn’t looking to rip and replace everything, he needed solutions that would work with their existing infrastructure.
The lesson? Your AI strategy should fit your business, not the other way around.
The Cope Plastics story
So what did this look like in practice?
Jeff’s journey started when their VP of Operations attended a CFO conference and met Scott. They began with an assessment, not a sales pitch, but a genuine evaluation of where AI could help.
Jeff was upfront about his concerns: integration costs, time investment, and making sure any solution would play nicely with their Microsoft ecosystem.
The result? They identified specific use cases where AI could deliver immediate value without disrupting their existing workflows. They focused on customer service automation and internal knowledge management—areas where the ROI was clear and the implementation was manageable.
How should I build a new AI strategy?
1. Don’t chase the hype. Just because AI is hot doesn’t mean you need to implement it everywhere. Focus on solving real problems.
2. Start small and strategic. Pick one or two high-impact areas and prove the value before scaling.
3. Get your team involved early. Change management is just as important as the technology itself.
4. Be technology agnostic. The best solution is the one that works with your existing systems and processes.
5. Think long-term. AI implementation isn’t a one-time project—it’s an ongoing evolution of how your business operates.
AI isn’t about replacing humans or jumping on the latest trend. It’s about identifying opportunities where technology can free up your team to do more meaningful work.
Ready to meet with our AI strategy consulting experts? Try an AI Assessment today.
