Trust
at
Scale
A Strategic Perspective for Unum Leadership
Unum is not changing what the business does. It is changing how the business delivers it.
For more than 175 years, Unum has helped people navigate some of life’s most uncertain moments. The mission has not changed. Customers still expect clarity. Employers still expect dependable administration. Brokers still expect confidence. Regulators still expect responsible decision-making. Investors still expect disciplined execution.
What is changing is how those outcomes are delivered. Customers increasingly expect the speed and convenience of digital experiences while still wanting the reassurance that a knowledgeable person is available when empathy and judgment matter most. AI is changing how work gets done. Digital tools are changing how people interact with the business. Automation is changing how routine work moves through the organization.
The bet is not that Unum becomes an AI company. The bet is that Unum becomes a more technology-enabled benefits platform while preserving the predictable outcomes that made the business valuable in the first place. Insurance remains the economic core. Digital experience becomes the operating wrapper. AI becomes the acceleration layer. Trust preserves the predictability that has defined the business for generations.
If that is the future, what has to become true?
If Unum is preserving predictable results while changing how work gets done, the foundation underneath that future has to do more than support applications. It has to preserve trust across every interaction: customer to application, employee to workflow, employer to platform, broker to service team, AI to data, vendor to system, and application to API.
Digital should remove friction so human interactions become more meaningful. Technology should automate the work surrounding relationships, not the relationships themselves. The best use of AI is not to make Unum feel less human. It is to give employees more time, more context, and more confidence when human judgment matters most.
That makes security, reliability, performance, governance, and observability part of the customer experience. They are no longer invisible infrastructure concerns. They are part of whether customers experience Unum as dependable, responsive, and trustworthy when the moment matters.
“You have to get a vision of where you are today and where you're going. You have to get that foundationally right.”
Digital convenience should not make the business feel less human.
Unum increasingly competes on more than the insurance product itself. The surrounding experience matters: claims, leave management, employer administration, broker support, customer service, and employee self-service. Those interactions shape how people remember the company.
Customers want speed, clarity, and convenience. They also want confidence that someone capable is available when the situation is sensitive, confusing, or emotionally charged. The future customer experience is not purely digital. It is digital where digital helps, and human where human judgment creates trust.
That means the goal is not to replace people with software. The goal is to remove the administrative burden that prevents people from doing the work customers actually value. Digital should make the routine parts easier so the human moments become better.
AI should strengthen people, not replace them.
AI is changing how work gets done across insurance, benefits, leave, claims, service, and internal operations. That does not make AI the story. The story is whether AI helps preserve the qualities customers already value: fairness, empathy, clarity, and confidence.
In Unum’s business, judgment matters. Disability, leave, illness, and financial uncertainty are not ordinary service moments. They are moments where customers often need reassurance as much as speed. AI can help surface information, simplify steps, summarize context, and reduce manual work. It should not remove appropriate human intervention from the moments that define trust.
This is where AI governance becomes a business requirement rather than a technical nice-to-have. If AI supports claims, service, leave, or customer interactions, the system has to be transparent enough, controlled enough, and observable enough to preserve confidence in the decision-making process.
“The organizations creating the best outcomes aren't choosing between AI and people. They're leveraging AI to remove friction...”
Modernization has to protect the business model, not just modernize the tools.
Every company has an economic engine. Unum’s engine depends on disciplined execution, trusted customer relationships, benefits experience, capital discipline, and predictable outcomes. The company is not behaving like an organization trying to burn down the old model and start over. It is modernizing from a position of strength while trying to keep the business dependable.
That is a harder problem than transformation theater. It means improving digital experiences, introducing AI, reducing operational friction, and addressing legacy risk without creating new complexity that undermines the results investors expect. The pace of change matters, but so does the stability of what is changing.
The strongest interpretation is that Unum is not trying to reinvent the business. It is trying to preserve predictable results while changing how the business delivers them. That requires technology that improves speed without increasing fragility, expands digital access without weakening trust, and supports AI without making outcomes less explainable.
“We have to find balance between the legacy technology that we have... and the new emerging technology and disruption that's coming.”
They’re deciding what architecture will carry every future interaction between customers, employees, brokers, partners, applications, APIs, and AI.
Protecting predictability.
The business case is not a spreadsheet pretending to quantify empathy. Mercifully. The business case is predictability. Customers expect predictable support. Employers expect predictable administration. Regulators expect predictable governance. Investors expect predictable execution.
As more of the business is delivered through applications, APIs, AI, partners, vendors, and digital workflows, predictability becomes harder to preserve. The risk is not simply that one system fails. The greater risk is that thousands of small digital interactions slowly erode the trust that has taken generations to build.
Trust is not only a brand asset. It is an operating asset. If trust weakens, the effects can show up in customer satisfaction, employer confidence, broker relationships, regulatory attention, operating cost, and investor confidence. That is why the architecture underneath the future matters.
Unum has already chosen to modernize.
It has already chosen to expand digital experiences.
It has already chosen to make AI part of how work gets done.
It has already chosen to preserve the trust and humanity the business is built on.
The remaining decision is whether the foundation underneath those initiatives preserves the predictable outcomes the business has spent more than 175 years delivering.
Cloudflare is asking Unum to evaluate that foundation before today’s architecture becomes tomorrow’s constraint.
Why architecture becomes part of the trust model.
Most security companies built tools that sit on top of infrastructure. Cloudflare built the infrastructure itself. That difference matters when the business problem is no longer a single application, a single user group, or a single security control.
As AI changes how work gets done, the interactions that matter multiply: people to applications, employees to AI tools, AI to APIs, vendors to systems, brokers to platforms, and customers to digital services. The control problem becomes less about adding another product and more about governing interactions consistently in the path of traffic.
Cloudflare’s architectural argument is that security, performance, networking, application delivery, and developer services should operate from one global platform. Requests can be evaluated consistently before they reach the systems they are trying to access. Policies can be defined once and enforced closer to the interaction itself. The goal is not more technology for its own sake. The goal is less operational complexity and more consistent control over the interactions that now carry the business.
The Cloudflare story starts in 2004 with a question: where does email spam actually come from? To answer it, the founders built Project Honey Pot, a distributed system that let any website owner plant tracking traps for spammers and malicious bots, mapping their behavior across the internet in real time. Over five years, thousands of websites in 185 countries joined.
The dataset grew rapidly. And users kept pushing for more capability — “don’t just track the bad guys. Stop them.”
Lee Holloway didn’t build another web proxy. He built a globally distributed reverse proxy layer that ran the same software stack on every machine, everywhere, simultaneously.
The physical infrastructure was unremarkable: commodity x86 servers in colocation facilities around the world, nothing exotic.
The radical part was the software architecture and what it was designed to do.
Rather than sending traffic to a specialized system for caching, then another for security, then another for routing, Lee built a unified packet-to-application processing pipeline where a request arrives, gets parsed, hits security logic, gets routed, and gets served, all inside the same system.
Combined with anycast routing (where every Cloudflare location shares the same IP address and the internet automatically routes users to the nearest one), this meant that any Cloudflare server anywhere in the world could handle any request for any customer.
Cloudflare didn’t build services on top of a proxy, it built a network. That difference is now visible in every enterprise conversation about what infrastructure can actually support the next ten years.
By 2025, Cloudflare was processing traffic for roughly 20% of all websites on the internet. But revenue and growth are not the real story. The real story is architectural timing.
AI agents are not like traditional software. Traditional software runs in predictable locations, on predictable schedules, talking to known endpoints. AI agents are autonomous. They make decisions, call APIs, spin up processes, and talk to other agents. Constantly, globally, simultaneously, and at a scale that was unthinkable five years ago.
They need infrastructure that is globally distributed, low-latency, secure by default, and instantly available, with no servers to provision and no regions to choose.
Cloudflare has been building exactly that infrastructure for fifteen years, without knowing AI agents would need it.
That foundation was not built for AI. But it turns out, building for the hardest problems on the internet (global scale, millisecond latency, consistent security everywhere, no boxes) is exactly what AI needs. Cloudflare did not predict AI. They just built the right thing, and AI arrived.
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2026-06-09 1:00 PM ET
The New York Stock Exchange
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