Phil HowardEnterprise Sales
Bringing 15+ years of enterprise technology sales to AI adoption

Customers ask for what they know.
Progress starts with
what they haven't seen yet.

Every major technology shift raises the same business questions. AI is making them more urgent.

I'm Phil Howard. I spent 15+ years in B2B and enterprise sales at Verizon, then seven years running an organization from the other side of the table. I like learning a business well enough to connect problems, people, and possibilities that are often considered separately. Each engagement below began with a narrower request and expanded as better questions brought the larger business problem into view.

See what that looks like Email me
2003 to 2018 Verizon National Account Manager,
then Senior Client Partner Then Executive Director
O'Dwyer Retreat Center, 2018 to 2025
Phil Howard
$10M+ Annual enterprise portfolio
Senior Client Partner, Verizon
Selected work

Three engagements. The numbers came after the questions.

Customers often begin with the most apparent need. Each of these engagements grew because better questions revealed a broader business problem and a more valuable path forward.

THE ASK THE OPPORTUNITY
A global biopharmaceutical company

The ask was a discount. The opportunity was to make the refresh secure and connected.

They wanted volume pricing on a bulk mobile-hotspot order. Asking how they planned to use the devices surfaced a company-wide laptop refresh plan with Dell and no unified mobile-security approach. The Dell model they had specified did not include mobile broadband. A call to Dell confirmed the same model could be custom built with an embedded chip, an option they had not ordered. On my recommendation they changed the order and paid the difference. I brought Dell, IBM, Verizon engineering, finance, customer service, and a national implementation team together around a secure rollout. Two devices per user became one.

$1.6MEnterprise solution value
1,500+ mobile broadband-enabled devices
An enterprise software company that had grown by acquisition

The conversation kept returning to price. The larger problem was fragmentation.

Every conversation with the SVP of IT came back to cost. He could see 25 lines for his own team, but acquisitions had left roughly 2,000 lines spread across carriers, contracts, and policies. I worked with Verizon Finance and operations to build consolidated pricing and a cost-center model that preserved local accountability while creating enterprise visibility. The result was one exclusive agreement covering roughly 2,000 lines, grown from the 25 he could see when we started.

$2MEnterprise solution value
25 known lines grown to 2,000
A national news and publishing organization

The headquarters agreement was the foothold.
The affiliates were the growth.

The first national agreement covered headquarters. I used it to reach the organization's 130+ affiliates, each of which made its own buying decision. As adoption grew, we built successive agreements with stronger volume pricing, giving every new affiliate a clearer reason to join.

$4M+Enterprise solution value
Annual, 100 lines grown to 5,000+

Customers are described generically by design. I don't publish client names.

Both sides of the table

For seven years, I was the one being convinced.

I spent 15+ years making the case across financial, operational, and technical priorities. Then I spent seven years owning the consequences of all three.

15+ Years in B2B and enterprise sales

At Verizon, I served as a National Account Manager and then Senior Client Partner across Fortune 500, regulated, and nationally distributed accounts. The work included multi-year negotiations, competitive takeaways, and partner ecosystems assembled around complex customer problems.

7 Years owning the decisions

As Executive Director of a $1.5M organization, I owned the P&L, operations, vendor decisions, and every capital investment for an organization serving 6,000+ people annually. The number of people served grew 42% over five years, and revenue grew more than 20% in a single year.

The CFO

What has to be true for this investment to earn its place?

Cost, savings, revenue impact, risk, and return. A technically sound solution can still stall if the economic case is unclear or the downside has not been addressed.

What I ask themWhat return would make this investment worth the risk?
The COO

What happens when this meets the real world?

Capacity, speed, reliability, and what happens when something fails. The platform matters only if the work becomes faster, more dependable, and manageable for the people who have to use it.

What I ask themWhere is the current process costing you the most time?
The CIO

Who is still supporting this in three years?

Security, integration, governance, scale, and supportability. Technology leaders inherit the decision long after launch, so the solution has to fit the systems and team already in place.

What I ask themWhat would make this impossible for your team to support?

The solution has to fit the people as well as the problem.

Financial, operational, and technical stakeholders can support the same decision for different reasons. Outcome Orchestration means understanding what matters to each person and shaping a solution that works across those priorities.

SOLUTION CIO COO CFO USERS DIFFERENT PEOPLE. DIFFERENT OUTCOMES. ONE SOLUTION.
Two rooms

Two perspectives.
I have worked from both.

I spent 15+ years selling enterprise technology and seven years owning the kinds of decisions enterprise sellers ask customers to make. Choose the perspective most useful to you.

How it comes together

A single request can touch finance, operations, technology, users, and implementation. See the method I use to bring those outcomes together.

The seller's chair
What seven years on the other side taught me

Owning the budget, the tradeoffs, and the consequences changed how I evaluate every sale.

The buyer's chair
AI adoption

AI is new. The questions are not.

For seven years, I ran a retreat center with five full-time employees, fifteen part-time staff, and thousands of people moving through the property each year. The constraint was rarely ambition. It was capacity. Every hour spent standing up a new system was an hour not spent on the mission.

Many companies face the same tension with AI. Interest is high. Expectations are rising. The harder questions are operational.

How does a pilot become part of everyday work?

Who owns it after launch, using the team already in place?

What rules govern its use, and who is accountable for them?

I spent 15+ years helping enterprises work through earlier versions of those questions when wireless was the emerging technology.

On adoption, a global biopharmaceutical company asked for volume pricing on mobile hotspots. Discovery uncovered a company-wide laptop refresh and a missing mobile-security approach. We replaced a laptop-plus-hotspot setup with one connected device and created a national implementation process for fully staged delivery.

On ownership, I built the national implementation team because the operational work of a rollout does not disappear. Either the partner plans for it or the customer's team absorbs it on top of everything else.

On governance, the refresh had no unified mobile-security policy behind it. We created a workable security and device-management approach around the customer's existing team and processes.

AI is new. The questions are not.

How this was built

I built this site with AI, and I governed it like a deployment.

Every model I used was fluent, confident, and occasionally wrong in ways that would have cost me credibility, not the model. So one master document became the source of truth. Facts were corrected there before they moved anywhere else. Customer identities stayed separate from public stories. Paraphrases could not become quotations. Potential outcomes could never be presented as booked results. I also prohibited the site from framing value as fewer people doing the same work.

ClaudeDesign direction, site code, and substantial drafting. Strongest fit for the iterative build. I made the final factual and editorial decisions.
ChatGPTStory development, interview preparation, fact discipline, copy refinement, and graphic creation.
GeminiIndependent second opinions on technology choices, wording, and diagrams.
NapkinEarly visual exploration. Useful for testing ideas even though none of the final assets survived.
CloudflareHosted on Cloudflare Pages.
What I chose not to ship

Building with AI also meant deciding what did not belong in the final product.

Interview agentI built a public interview agent around my career story bank. One adversarial prompt produced an answer I would never have given, so I took it down. Fixing that answer would not have fixed the underlying risk.
Backend workerWhen the agent came down, I audited the backend behind it and realized a protection I had relied on was not providing the control I thought it was. I decommissioned the Worker rather than leave an unnecessary service running.
Executive pressure testI built a tool that reframed the same customer opportunity through CFO, COO, and CIO lenses and generated the questions each might ask. It worked, but it was more useful as a private preparation tool than as a public website feature, so I kept it out of the final experience.

Built with AI. I set the direction, challenged the output, checked the facts, and owned what shipped. Now I want to bring 15+ years of enterprise selling to the companies shaping AI adoption.

Open to senior enterprise sales roles

If this is the kind of enterprise selling you value,I'd like to talk.

I'm focused on senior enterprise sales roles in AI and enterprise technology where the product is worth believing in, the customer problem is complex, and judgment matters as much as activity. If that describes what you are building, a direct note is the fastest way to reach me.

What I'm looking for

A product that creates meaningful new capacity or capability for customers.

A sales organization where experienced sellers are expected to make the whole team better.

A company that listens to the people closest to the customer.

[email protected] LinkedIn

A direct note gets a direct answer.