Two years ago, Michael Weening reached a crossroads, realizing AI could be more than just an operational add-on. While other CEOs failed to grasp AI’s potential and hesitated to adopt it, Weening perceived a watershed strategic imperative and existential threat. One hundred million dollars later, he’s glad he went all-in.
“I became a big believer that if we didn’t do this, we’d get run over,” says Weening, CEO of Calix, a publicly traded provider of cloud-based software, platforms and services to 1,100 broadband service providers in more than 60 countries. Instead, Weening went full throttle toward making Calix an AI-first enterprise—where AI is its fundamental infrastructure.
The San Jose, California-based company partnered with vendors like Salesforce and Oracle to activate AI capabilities across core systems, integrating AI directly into the flow of work. At the same time, it deployed Microsoft Copilot to its 1,800 employees globally, empowering them to build their own AI agents to streamline processes. “The culture here embraced the opportunity, generating 725 AI pilots, of which 40 are now scaled across the business,” Weening says.
In October 2025, Calix announced the next generation of its broadband platform, purpose-built for customers to realize agentic AI. Agent2Agent communication, in which autonomous AI agents collaborate on tasks, share information and coordinate actions without human intervention, will be enabled in 2026. “While enterprise integration is underway, product teams here remain focused on customer-facing agentic AI scenarios, with plans to weave internal AI platforms into enterprise systems as readiness grows,” the CEO projects.
Calix is just one of a fast-growing number of companies building AI-driven business models from the ground up, for both offensive and defensive reasons. Alex Singla, a senior partner at McKinsey & Co. who co-leads QuantumBlack, the consulting firm’s AI and analytics arm, says such organizations have grasped that AI isn’t about continuous micro-improvements, it’s about doing business differently. “The question every CEO should be asking every time a person does something is, ‘Would AI do it differently?’” he says.
The answer, of course, is yes. “If you want to provide a better customer experience, a better employee experience and the best products and services that are consistent with most organizational values, then AI is the way to do that offensively,” says Singla. “The flip side is the need to deploy AI defensively, before the competition leapfrogs you. Much smaller competitors and even startups can suddenly leverage a cost-effective technology that in the past would have been hundreds of millions of dollars.”
First-Mover Advantage
This existential reality is prompting CEOs like Eric Vaughan to transform global enterprise software solutions provider IgniteTech into an AI-first company. Vaughn’s strategy took root two years ago, when he gave each employee $1,200 to take courses in the use of AI tools. Eighty percent of employees passed on the opportunity, concerned over their job security. “I didn’t have all the answers, but I was convinced that this technology was changing ‘everything, everywhere, all at once,’” he says, borrowing the title of the 2022 Oscar-winning film.
Vaughan was adamant about his intent to restructure the entire workforce around AI and launch new AI-powered solutions. Hundreds of employees who remained steadfast in their objections were replaced with new employees skilled in using AI. Such AI innovation specialists, as the CEO calls them, joined the enterprise in sales, marketing, HR, finance and other domains. Vaughan declared Mondays to be AI Monday, a day in which employees could work only on AI projects, and sponsored a competition with cash prizes for employees coming up with the most innovative AI ideas.
By 2025, the CEO felt he had put together a world-class AI team of employees. “For us, this was never about cutting a process down by 30 percent to save time and money; we wanted to free people up to do their most creative and innovative work,” he says, noting that this work has produced two new, patent-pending AI software solutions.
One AI solution, MyPersonas, gives customers the ability to create on-demand digital clones of key employees, making their specialized knowledge available 24/7 in a video chat format. The other AI solution, Eloquens AI, manages inbound email inquiries, generating knowledge-based responses in 160 languages within five minutes. “We’re a 30-year-old company today that looks and acts like an AI startup,” he says.
The CEO’s difficult decisions were vindicated in May 2025, when he heard Nvidia CEO Jensen Huang state at the Milken Institute’s Global Conference, “You are not going to lose your job to an AI, but you are going to lose your job to somebody who uses AI.”
“Change is inevitable. I wanted to lead, not follow and get run over by other companies that saw the light first,” he says.
Experiments in Workflow
Imagine having no background or experience in coding and suddenly finding that one can do that? This was the self-described “Aha moment!” that led CEO Eric Laughlin to transform Agiloft into an AI-empowered business. “The fact that I could use AI and learn how to code made me realize that it could help every one of our 400 employees ideate, collaborate and make decisions, recreating our business to learn and adapt faster,” Laughlin says.
Agiloft is a provider of Contract Lifecycle Management services that streamline the complex, manual processes associated with contracts, from their creation to their renewal or termination. Following his sudden coding insight, Laughlin gave each employee generative AI tools that included AI agent capabilities to perform their respective tasks. “An AI agent could review a contract and evaluate whether it needed or didn’t need a more comprehensive security review, making this human-led process much faster,” he says.
As teams become adept at using their AI agents, Laughlin’s goal is for them to think about the cross-functional work their AI agent could perform to understand the breadth and scope of the company’s workflow and speed up these processes.
“Once they know this, they can create cross-functional use cases streamlining processes, reducing errors and improving overall efficiency,” he explains. “That’s Phase Two for us, getting employees to experiment and come up with great ideas on how to build an AI agent to map our workflow. Experimentation is the root of all this. We’re not layering AI on top of the business; we’re rebuilding the business with AI.”
At MyCOI, founder and CEO Kristen Nunery was also struck by an epiphany. At a weeklong series of courses on AI taught at Stanford University in 2024, she grasped for the first time the degree of transformation that AI would have in her industry. “I recognized it would completely disrupt the outsourced model for compliance and made the decision to implement AI to fully transform what we had been doing for the past 16 years,” Nunery says.
Two Models, One Company
MyCOI is a leading global provider of third-party insurance compliance on an outsourced basis, flagging non-compliant insurance policies, coverage gaps and expired Certificates of Insurance (COI, hence its name). Clients are companies in industries like construction, trucking, retail and healthcare where insurance tracking is crucial. MyCOI manages insurance compliance for over one million contracts and 200,000 third parties. By having myCOI assume the administrative burden, organizations can focus on running their businesses.
All was well, good and profitable, until Nunery suddenly understood that AI could perform a compliance review process that took days and weeks in minutes. Rather than shy away from this existential realization, she embraced it head-on. “I wasn’t afraid to be very bold and candid, to call out the challenges that AI posed to the outsourced model that we had provided for 16 years,” she says.
Her approach involved the creation of an entirely separate operational company, Illumend, which made its debut in May 2025, following a highly successful preview of the beta version at an industry trade show six months earlier. The AI-native compliance platform, developed in partnership with Left Field Labs, is peopled by a separate team with AI skillsets to drive innovations forward. “It’s an open door to current and future clients to reach a new level of empowerment,” she says, noting that one executive team oversees both companies.
Among the AI platform’s singular features is a conversational intelligence guide called Lumie, which can read and interpret insurance documents, flag risks in real time, draft communications and steer client administrators through issue resolution. “Typically, there’s some nervousness bringing a new platform to market, but the customer response has been phenomenal,” Nunery says.
A More Productive Workforce
CEOs at midsized and larger companies aren’t the only leaders thinking bigger about the power of AI to operationally and culturally transform their businesses. At Redmond Waltz Electric, an 80-year-old full-service shop with 20 employees who repair large electric blowers, fans, gearboxes, pumps and motors for high-volume customers like flat-rolled steel producer Cleveland Cliffs, CEO Jennifer Ake Marriott sees AI as “a once-in-a-century innovation like electricity, with the potential to positively impact how we live and work, a story that is under-reported in my view.”
Redmond Waltz is integrating AI into strategy, customer experience and operations to open up new revenue opportunities, accelerate decision-making and democratize expertise. She pointed to the use of AI to train mechanics in often delicate, hands-on repairs. “While the gearboxes, pumps and other mechanical devices may share similar components, the significant variability in their manufacturers, horsepower, frame sizes and types require extensive, time-consuming and costly manual training,” she says.
To bridge this divide, mechanics are using Meta glasses and AI transcription tools. By narrating a repair in real time, explaining what they’re doing and why, and simultaneously capturing photos or videos of their hands performing the work, Redmond Waltz can create a more comprehensive, logically sequenced training program. “The process is seamless and minimally disruptive to their workflow,” Ake Marriott says.
From a labor standpoint, the CEO equates the use of AI to additional headcount. Baby Boomer and Gen X mechanics, she explains, are retiring in droves, and Millennials didn’t get the vocational training their predecessors received in high school, leaving a big hole. She would increase the workforce by 25 percent today if she could, she says, but every manufacturer is vying for the same depleting pool of employees.
“There’s this inherent risk in a small manufacturing company that when someone walks out the door, they take along with them their institutional knowledge, making it incumbent for small companies to continually create their own skilled labor,” she says. “AI gives us an opportunity to make that infinitely easier.”
Redmond Waltz also uses AI administratively to review contracts, improve the quality of business emails and extract sophisticated insights from two decades’ worth of this correspondence. Next year, Ake Marriott plans to leverage AI to access the company’s history, strategic plan, corporate policies, customer data, financial data, employee résumés and job descriptions in the employee handbook. “When someone asks me how much the stipend reimbursement is for steel-toed boots, I can say ‘ask AI,’” she says.
Scaling at Less Cost
Bethany Ayers, CEO at UK-based data security platform provider Metomic, is redesigning the business architecture around AI—not as a support tool but as a workforce. “By the end of the year, every one of our 25 employees will manage at least four AI employees,” says Ayers.
AI employees are akin to AI agents but have a broader meaning, emphasizing a more human-like, role-based service. At Metomic, people give their AI employees gender-neutral personas like Darcy, who designs data sheets. Two of Ayers’ AI employees are Taylor, who helps her create demos, and Charlie. “I run all the marketing content through Charlie to tell us what’s grounded in reality and not too salesy,” she says.
The hundred or so AI employees are integrated into Metomic’s workflows and trained to handle repeatable, operationally critical tasks. This valued assistance frees up human employees to think strategically and innovatively. “We have a very talented organization and want to retain that density because money isn’t as cheap as it once was. By adding more AI employees, we don’t have to hire more people,” Ayers says.
Founded in 2018, Metomic’s customers include digital bank Revolut, global employment platform Oyster HR and Leroy Merlin, the third-largest home improvement retailer in the world. Prior to joining the company as its CEO in August 2025, Ayers scaled two businesses. The fundamental problem she encountered at both was the need to hire more and more people and effectively train them.
“The future is building a business with as many or more AI employees as humans,” she says. “Everybody becomes a manager supervising a team of AIs. Having already done this at Metomic, the team is in a fantastic position to make their careers.”
Realizing this potential is not a slam dunk, Ayers acknowledges the importance of training AI employees: “Just like people, you don’t get value from a tool you haven’t trained. You have to articulate what you want, why it matters and what success looks like. The better you teach it, the more valuable it becomes.”
Added up, the intrepid moves by these and other CEOs suggest the days of using AI purely for superficial improvements are, well, so last year. Bolder investments in AI agents and multi-agent systems are what will separate the AI winners of the future from those left behind.
