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From workflow optimization to round-the-clock responsiveness, industry leaders are using AI to unlock capacity, improve efficiency, and drive growth without adding headcount.
For decades, growth and hiring went hand in hand. As companies gained customers, they added employees to manage rising demand. Today, however, artificial intelligence is changing that equation. Rather than increasing payroll, many businesses are turning to AI-powered solutions to expand capacity, streamline operations, and improve customer service.
Across industries, technology leaders are helping organizations rethink how they scale. Their experiences reveal a common theme: the most successful AI strategies focus on fixing bottlenecks and strengthening workflows before introducing automation.
Diagnosing Bottlenecks Before Deploying AI
For Kristin Anderson, Co-Founder and President of Accelerant Growth Solutions, scaling challenges are often misdiagnosed as hiring problems when they are actually workflow problems.
“When you think about a hiring problem, a lot of times those hiring strategies are just departmental. But if they were to look at their workflows cross-functionally, and from an AI-first perspective, they’ll find that they could have a huge exponential amount of increased capacity within their teams without adding headcount,” Anderson said.
Her approach begins with understanding where organizations are losing time and capacity. Rather than implementing technology immediately, she advocates a thorough evaluation of processes.
“We are really, really big proponents of diagnose-first. Look at the numbers, figure out where your bottleneck really is, and then apply AI. Because if you apply AI to something, a process that’s not effective or not working, then you’re just going to get that break at scale,” she explained.
Anderson also believes AI creates opportunities for smaller businesses to compete more effectively by preserving institutional expertise.
“You can take AI and take the tribal knowledge of your best people: your longest-standing customer service rep, your most successful salesperson, the founder from 50 years ago. All that tribal knowledge can now get put into AI, and you can make something that is yours, and nobody else has. That’s a real competitive advantage.”
Process First, Technology Second
This philosophy is echoed by Neal J. McLeod, Founder of CTK Industries, who argues that technology alone cannot solve operational inefficiencies.
“I spend most of my time just pulling the bottlenecks out; they don’t know. Most of the time, they just need automation. I try to seldom use AI within the process. We’ll use it to build a process, but very seldom within the process itself,” McLeod said.
By mapping workflows and identifying operational pain points, McLeod often finds that businesses need clarity before they need AI.
“Bringing clarity to their company, their processes, and their bottlenecks; that’s where my value is. They may think they need one thing, but when I’m listening to them, they want a different type of outcome. And they say, oh wow, I didn’t even consider that.”
When AI is deployed, it uses it to uncover insights hidden within data. According to McLeod, one of the most impactful applications involves generating new performance metrics.
“The AI was able to extract the data and present it in a way the client didn’t think about, creating new ratios and new KPIs to help them perceive their data in a completely new way. That’s a really important way of applying AI.”
Capturing Opportunities Around the Clock
While some organizations focus on process optimization, Lindsay Liu, Co-Founder and CEO of Super, concentrates on responsiveness.
She recalls one client whose sales operation was missing a significant number of inbound opportunities.
“You’re literally not answering the most high-intent prospects that you have. We looked at one client’s Dialpad data and their sales line; the most important line to answer was missing 83% of calls. From a sales perspective, that is just an obvious, untapped opportunity,” Liu said.
To address this challenge, Super uses AI to provide continuous coverage, ensuring inquiries are captured and routed appropriately. The result is not only improved lead management but also better workforce allocation.
“We’re seeing folks that would have been, frankly, stuck with administrative work now able to take on more proactive work. If you had somebody whose entire job was just answering the phone, now they can be responding to a maintenance request and actually getting ahead of things before they become a problem.”
Liu cautions against overly ambitious AI rollouts and instead encourages gradual implementation.
“I really advocate for a crawl, walk, run approach. Let’s start with the lowest hanging fruit, the biggest problems that you have, and then add additional use cases from there. You don’t want to promise the world right away: you have to train it, and edge cases are going to come up over time.”
Turning Logistics Into a Scalable System
In logistics, Evandro Nadal, COO and Co-Founder of Getcho, sees AI as a way to replace operational knowledge that traditionally resided with a handful of experienced employees.
“On a very basic level, let’s say you’re a dispatcher in New York with three fleets. You know which streets have doormen, which fleets are cheapest for which routes. With AI, it’s very easy to make those calculations, because if you give it good context and good data, it is very powerful,” Nadal said.
Getcho’s platform continuously monitors deliveries and resolves issues before customers notice them.
“The AI read the image and realized the package was at the wrong door; it called the driver to move it. No one found out, because we have an agent who calls right away whenever something goes wrong. We get examples of it every day.”
This automation allows store employees to remain focused on customer-facing responsibilities despite growing fulfillment demands.
“A lot of store teams want their staff focused on customers coming in. As logistics change, people are making their stores a fulfillment center. You need to find the balance between ‘these people need to be there to help customers’ and ‘there’s work to be done, ‘ and that’s where we come in.”
Scaling Smarter, Not Larger
From consulting and operations to customer service and logistics, these leaders are proving that growth no longer requires proportional increases in headcount. They believe that AI delivers the greatest value when paired with clear processes, accurate data, and well-defined objectives.
As businesses seek new ways to grow efficiently, a thoughtful approach to AI adoption is helping them serve more customers, move faster, and create competitive advantages that are increasingly difficult to replicate.
