AI Adoption Evolves: Companies Shift From Efficiency to Driving Real Business Growth

AI is ready to drive growth

The Fast Company Executive Board is a private, fee-based network of influential leaders, experts, executives, and entrepreneurs who share their insights with our audience. A few weeks ago, a senior marketing executive walked me through the various ways her company was approaching AI. She had reason to feel good about it. Her teams had Microsoft Copilot. They had an approved, locked-down version of ChatGPT. One of her groups even went off, did AI training abroad, and came back with a briefing document recommending new tools worth a look. Then we started talking about where the technology is heading. We watched demos of agents built to tackle specific business problems, then discussed the surprising workflows companies built around them. By the end of the conversation, her expression had changed. "Oh boy," she said with a sigh. "I don't even know what to tell my team now." The briefing document her people were so proud of suddenly seemed written for a bygone time. She'd walked in thinking she was current and walked out realizing she'd been running to catch a train that had already left the station. I think a lot of leaders are about to have that same meeting with themselves. For two years now, I've seen most organizations look at AI through a single lens: efficiency. How do we automate this? What can we cut? Where can we squeeze out more productivity? Those are fair questions, and they've paid off -- McKinsey's 2025 global AI survey found that most companies using generative AI report cost savings across business functions. But the problem with efficiency is that it eventually runs out. You can only automate a process once. You can only trim a budget so far. And honestly, using a technology this capable purely to shave overhead is a little like buying a Ferrari to sit in traffic. Sure, it works, but you could be getting much farther, much faster. The question that changes everything The companies getting the most out of AI right now aren't the ones using it to do what they already do, just a little cheaper. They're using it to do what they couldn't do before. That starts with a different brief. Not "How do we make this process more efficient?" but "What are we trying to grow?" Which customer needs are we missing? Which accounts are we underserving? Which product could we get to market in a quarter of the time? Those questions take you somewhere completely different -- and in my experience, AI rewards ambition more than almost any tool that came before it. The bigger the question you bring, the more it hands back. It's no mystery why everyone started with efficiency. It's easy to scope, measure, and sell to a CFO. Growth is messier. It asks for experimentation, judgment, and a tolerance for chasing things that won't pan out. But those questions decide whether a company simply gets leaner or actually gets more valuable. We've seen this most clearly in product innovation, through the work in our Uncommon Growth Lab. Take a process that used to run nine months -- research, concept development, the full gauntlet of testing and focus groups and squinting through two-way glass. With AI, a team can now reach a high-confidence answer in about five weeks. But speed is the least interesting part of the story. The real change is in what the speed buys you. Instead of testing a single product direction, a team can seriously explore five. Instead of betting the year on the lemon vinaigrette, they can hold it up against the ranch, the packaging, the positioning, and two formats they'd never have had the time or the nerve to consider, then pressure-test all of it before anyone commits real money. Hand your best people the sword Once growth becomes the goal, something shifts in how you think about your people. The question stops being "How many of these jobs can I replace?" and becomes "How much more could my best people do with this tool in their hands?" In our work, AI delivers the most when talented people use it as a multiplier -- a way to chase more ideas, collaborate across functions they rarely touch, and push a promising concept further than they could alone. Used that way, it stops looking like cheap labor and starts looking like a superpower you can hand to the people who already know what they're doing. But -- and this is the part most leaders skip -- it can't stop at the staff level. It has to reach the corner office. In my experience, the companies moving fastest on AI are almost always the ones where the CEO is among the heaviest users. Because AI is not a spectator sport. Leaders who use these tools ask sharper questions than those who only hear about them in a briefing -- and you can't delegate your way to that kind of understanding. Ride the next wave The first wave of AI was good at cutting costs because that's what we asked it to do. But the next wave won't arrive just because the technology suddenly gets smarter. It'll arrive when leaders start aiming it at bigger targets: new markets, deeper relationships with the customers who matter most, and better products shipped faster. By the end of our meeting, the senior marketing executive had stopped asking about tools and started talking about her business -- how she might finally get her sales and marketing teams coordinated around a handful of key accounts she'd been fighting to crack for years. That's the whole shift, right there. She didn't leave with a better answer to the question she came in with. She left with a better question. One that AI, in the right hands, is more than ready to tackle. Michael Dunn is chairman and CEO at Prophet.

The Next Wave of Business Growth Won't Come From AI Software Alone. It Will Reshape Real-World Operations

I've watched wave after wave of technology emerge, form, and then be replaced. Each time, there's a progression I've noticed. The initial focus is on software. It isn't until later that you start to see more practical, fleshed-out applications emerge. Artificial intelligence is no different. We've had a few years now of "bigger, better AI models." But talking to an LLM is already an old experience (and in many ways, it's not enough). There is a new wave of innovation coming that will push the boundaries of AI beyond software. I can already see signs of a new shift. Many of the biggest opportunities for driving revenue and gaining a competitive edge are emerging at the intersection of AI software, logistics, and infrastructure. For forward-thinking brands, this means moving past mere automation and leveraging AI-powered solutions for real-world operations that scale business growth. Turn customer insights into growth Customer behavior is becoming more complex, making it increasingly difficult to know which marketing messages, website experiences and content will drive conversions. Fortunately, AI is helping businesses surface insights that would be nearly impossible to uncover manually. Marketing teams can use data to better understand customer behavior, identify opportunities for improvement and make faster, more informed decisions. AI can analyze how visitors interact with websites, campaigns and digital content, revealing patterns that help marketers improve engagement and conversions. Platforms like Optimizely combine experimentation, personalization and AI-powered insights to help teams test ideas, optimize digital experiences and deliver more relevant content to different audiences. Instead of making broad changes and hoping they work, businesses can continuously learn what resonates and refine their approach over time. Even if you're not using an enterprise experimentation platform, the takeaway is the same: make testing a regular part of your marketing strategy. A/B testing can be implemented anywhere from email campaigns, social posts, or CTA placements on your website. Small adjustments could produce big results. Start by measuring how customers engage with your website, test one meaningful change at a time and use the results to guide future decisions. Maximizing revenue beyond the checkout page One of the most practical ways I've seen AI used in real-world scenarios is with business operations after the point of sale. This is critical retention territory, and it's notorious for being a mixed bag for customer lifetime value. The obvious AI improvement here is chatbots that actually work to save a sale. They can carry on a conversation, provide nuanced answers, that kind of stuff.