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Businesses are using artificial intelligence to compress timelines, streamline back-office operations, and make lean teams more productive, without removing humans from critical decisions.
Companies across industries are discovering that AI’s most immediate value is not replacing headcount, but compressing the time between a problem and an answer. From automating manual data entry to restructuring production pipelines, artificial intelligence is helping lean teams accomplish more with existing resources. The organizations making the biggest gains are treating AI as an amplifier of human effort rather than a substitute for it.
Noble33: Scaling Without Scaling Overhead
For Noble33, a fast-growing hospitality group known for “vibe dining,” AI has become central to building a scalable back-office operation. Before AI, complex questions about guest trends, labor benchmarks, and venue performance often required rigid BI tools. Mahdiar Karamooz, President and CFO at Noble33, now uses AI-generated dashboards and custom local agents to surface insights in real time while restaurant teams remain focused on guests.
As Noble33 expanded from three locations to seven, including a partnership with Patrick Mahomes and Travis Kelce, AI helped the company optimize the output of its existing team rather than simply increasing headcount.
Karamooz stated: “We have implemented AI in pretty much every single department to improve back office processes so that we can support the restaurants better; getting them quicker reporting, better analytics. We are not working with canned reports anymore.”
The shift also opened access to information that had previously been difficult to process.
“We are getting answers to questions that we have had for years that we were never able to parse through because of large data sets. For us, it is really understanding our guests better; what they like, what they do not like, what trends are looking like, helping us get benchmarks in the industry,” shared Karamooz.
Karamooz sees adoption itself as increasingly important to productivity.
“You have to adopt it. It is kind of like an employee back in the ‘80s who was not going to adopt Excel; you get to a point where you have to evolve with it. The faster you adopt it and learn how to use it, the more productive you become, the more valuable you also become.”
LightSail VR: Turning Weeks Into Hours
At LightSail VR, Matthew Celia and his team produce immersive media for Google, Apple, and Meta while maintaining the structure of an independent studio. When commercial software could not address specialized production requirements, AI allowed the team to build solutions internally.
Matthew Celia, Co-Founder of LightSail VR, revealed: “Stuff that would take me normally two, three weeks to bang my head against a wall could be done in an hour or two. It was insane. I have a specialized business with specialized workflows. I need tools. Software companies are not making them. I have to build them myself.”
One documentary project demonstrated the scale of the time savings. AI processed 10 hours of interviews and organized them into a paper edit with time codes in minutes.
“I had 10 hours of interviews to turn into a 30-minute documentary in one week. The AI went through all of it, pulled the lines with time code, and structured a story beat in like a minute. I was blown away. I found my use of AI sped up my entire workflow by weeks,” Celia added.
Yet Celia stresses that speed cannot replace creative judgment.
“I showed the film to my client, and she wrote back one word: underwhelming. An AI is not going to have taste. You are going to agree with it or disagree with it, but at the end of the day you have that taste as a creator. We have to remember it is just an assistant, and we have to put our own touch on it.”
Cota Capital: Finding Value in Existing Data
At Cota Capital, Vikram Venkat faces a different challenge: finding and connecting information efficiently. AI can index, summarize, and correlate information across board decks, emails, and market reports, reducing the hours required to navigate separate repositories.
Vikram Venkat, Partner at Cota Capital, explained: “A lot of the information exists and is in various digital repositories, but it is not necessarily easy to find, access, or summarize. AI can plug into a bunch of the systems, scan through them much faster than a human can, and correlate trends or themes that we may not necessarily have thought of.”
Venkat applies greater human oversight as risk and complexity increase.
“I think it varies based on a few factors: the complexity of the process, how much of it is rule-based versus judgment-based, and the level of risk associated with the process. If it is higher liability, higher chances of impacting a business or an individual, you want to be much, much more careful,” Venkat added.
He also sees AI changing the economics of software.
“AI has moved towards better understanding full processes rather than microtasks, and that allows you to deliver a full outcome rather than just solve a minor aspect. And it has changed the way pricing works — SaaS was typically seat-based pricing, and now it is much more outcome-based or usage-based.”
Data & AI Literacy Academy: Rebuilding Work
Greg Freeman, CEO of Data & AI Literacy Academy, argues that organizations cannot simply place AI tools on top of inefficient processes. Companies seeking meaningful gains must rethink how work is performed.
“Everybody wants the AI-native state, but that takes a huge job of almost burning down your current processes and rebuilding them from scratch to work in an AI-first fashion, rather than just layering on more technology on top of already bad processes,” said Greg Freeman.
His approach combines AI-native junior workers with experienced employees who can validate outputs.
“If you can get a really AI-native young person who is full of ambition and energy, and augment them with that intelligence, you have almost got the perfect employee. But you have got to have the human in the loop at first principles level — those experienced people who validate the AI outputs.”
Without that process-focused approach, Freeman warns that investment may not translate into results.
“I do fear we might find ourselves in 10 years with AI where the data industry has been; it promised loads but did not fully deliver because it was implemented as a technology rather than a process embed. A subset of organizations will do this correctly and dominate their markets, and the rest might find they invested a lot without realizing the value they expected.”
Absolute Exhibits: Automating the Work That Consumed Time
At Absolute Exhibits, Jean Ly confronted a task that had resisted automation for more than two decades. Companies often struggle to maintain a live database of trade shows, exhibitors, dates, locations, and regulations. Three part-time employees previously handled the work manually. An AI agent now uses web scraping to update the database and flags unusual cases for human review.
As the Director of Marketing at Absolute Exhibits, Jean Ly explained: “We have been manually updating a database of trade shows and exhibitors for the past 20-plus years. A human has been checking websites, confirming dates, confirming location, confirming rules and regulations. The AI is really going to save us three part-time employees that we can shift to doing more strategic, thinking-type work.”
AI has also shortened research timelines for content production.
“It has changed the way we develop our blogs — it allows us to do a lot of the research much more quickly. It probably would have taken me weeks to do a well-researched blog in the past, and now it is down to a couple of days, with the research happening much more quickly than that.”
For Ly, the broader impact is a change in how employees spend their time rather than a simple reduction in jobs.
“A lot of people are thinking AI is going to take away jobs, but I really think it is shifting how we work instead. If you think about what an AI output is, it is the average of what is already out there. It is up to us, the human creatives, to think outside of what that average is.”
The Cost Advantage Comes From Better Processes
Across these businesses, the common thread is not the sophistication of AI alone, but how deliberately it is deployed. Noble33 uses it to strengthen reporting and analytics while scaling operations. LightSail VR uses it to build specialized tools and compress production timelines. Cota Capital applies it to information discovery and process-level outcomes. Data & AI Literacy Academy emphasizes rebuilding workflows around AI, while Absolute Exhibits uses automation to move employees toward more strategic work.
The emerging model is therefore less about eliminating human involvement than reallocating it. AI handles repetitive, time-consuming, and data-heavy work, while people remain responsible for judgment, creativity, and accountability.
