Services-led Growth
for the AI Era

Context

As CEO of Able, I led the expansion from a prototyping studio into a full-scale product strategy and engineering firm. While this drove initial growth, by early 2024, I identified a critical shift: traditional software development practices were being disrupted by AI.

To avoid obsolescence, we had to pivot from being a firm that simply built software to one that led the industry on how to build software better and faster.

Strategic Pivot

We launched a systematic initiative to experiment with and operationalize AI across the entire software development life cycle. This was not just about using new tools; it was about redesigning our service delivery model to close the capability overhang for our customers.

We organized our efforts into four technical domains: off-the-shelf integration, RAG architectures, autonomous agents, and custom model development. By testing these against every stage of delivery—from infrastructure setup, to coding and deployment, to maintenance—we developed a proprietary, AI-powered SDLC.

This transformed our "custom builds" into a productized service offering that optimized for speed, quality, and technical durability.

Results

This transformation fundamentally changed our market position, shifting us from a vendor to a strategic implementation partner.

We successfully secured and delivered: a market-entry partnership for a leading AI model company to operationalize their solutions for enterprise clients; a distributed patient data platform for a global biopharmaceutical company, integrating complex data silos into a unified AI-ready architecture; and a portfolio-wide implementation strategy for a private equity firm, modernizing the product and engineering teams across their holdings.

Context

By early 2025, AI adoption across a 15-company private equity portfolio was almost nonexistent despite significant pressure from stakeholders. The primary barriers were classic symptoms of the capability overhang: teams were over-committed to legacy roadmaps, leadership felt threatened by organizational shifts, teams were insecure about adoption, and a fundamental lack of practical imagination regarding AI's actual application.

Strategic Approach

We designed and executed a three phase Implementation Framework to move the portfolio from inertia to integrated innovation, to create measurable value and introduce new capacity that would continue to self-improve.

Phase I: The Art of the Possible — We gathered representatives from all 15 portfolio companies for an immersive bootcamp and hackathon. The goal was to bridge the imagination gap by combining technical education with immediate, practical application. This phase was designed to demystify the technology and provide teams with the confidence to move AI solutions into production within weeks.

Phase II: Co-Innovation & Capacity Building — Moving beyond broad education, we selected high-priority companies for deep-dive engagements. Rather than building solutions for these teams, we built with them. This co-innovation model ensured that we weren't just accelerating product roadmaps, but building the internal technical capacity necessary for these organizations to own their AI future long after our engagement ended.

Phase III: Cross-Functional Scaling — As engineering throughput increased by up to 30%, we identified that Product and Design teams were becoming the new bottleneck. We expanded the framework to include these functions, ensuring the entire delivery chain was synchronized. This prevented the common trap of localized efficiency and ensured that increased velocity in engineering actually resulted in faster market impact.

Results

Our diagnostic metrics confirmed velocity and quality improvements of up to 30% across the portfolio. Beyond the quantitative gains, the most significant outcome was a cultural evolution. We replaced organizational resistance with a sustainable capacity to experiment and learn, ensuring these companies moved from being observers of the AI era to active participants in it.

Context

Before I arrived, Edelman had been selling Meta on Trust — research, reputation management, and the infrastructure to help one of the world's most scrutinized companies play defense.

Meta didn't want to play defense. They wanted to play offense.

Ninety days into the role, I had met with stakeholders across Meta's global marketing organization and read the same signal everywhere. Every conversation came back to growth. The incentives, the energy, the ambition all pointed the same direction. I repositioned the engagement entirely — away from reputation defense and toward commercial offense: performance marketing tied to acquisition metrics, brand campaigns supporting product launches, and go-to-market advisory for new market expansion.

Unifying a Fragmented Global Organization

Meta's regional teams across North America, EMEA, LATAM, and APAC operated with significant autonomy — producing politics and strategic disjointedness that made cohesive global campaigns difficult to execute.

Edelman's global network was the answer. I built a unified account model spanning all five geographies, establishing shared planning frameworks, joint campaign sequencing, and aligned messaging architecture across regions. Meta's marketing leadership gained a single strategic partner capable of operating at global scale while remaining locally effective — and Meta's regional teams, previously pulling in different directions, began operating with greater alignment.

Results

Over 18 months the account grew from $4M to $12M — a 3X expansion — driven by new service lines across growth marketing and product go-to-market. When Meta's procurement organization pushed back on our rates as the account scaled, the marketing leaders whose teams depended on our work engaged on our behalf. The value we had delivered made that advocacy possible.

Context

In 2016, I was named VP Global Account Lead for Google at R/GA — inheriting a relationship with significant potential but no established commercial foundation. The mandate was straightforward in theory and complex in practice: build a global, multi-disciplinary embedded services operation inside one of the world's most sophisticated technology organizations, and grow it into a strategic, high-margin partnership.

The challenge wasn't technical. It was human and commercial. Google's internal teams were capable and opinionated. To become a genuine strategic partner rather than a vendor, we had to earn trust at every level — from individual product teams to executive stakeholders — while simultaneously building the operational infrastructure to deliver consistently across geographies and service lines.

Account Strategy

Growth came in three interdependent phases, each unlocking the next.

Phase I: Trust before expansion. The first priority was depth, not breadth. Rather than pursuing rapid scope expansion, I focused on making our embedded teams indispensable to the Google product teams they worked alongside. This meant hiring specialists who could operate credibly inside Google's culture, establishing clear accountability structures, and delivering at a standard that created internal advocates — people inside Google who would champion our expansion rather than resist it.

Phase II: Service line expansion. With trust established, we systematically identified adjacent capability gaps within Google's organization and built service offerings to fill them. Each new service line was introduced through existing relationships, de-risking commercial conversations by anchoring them in proven delivery rather than speculative proposals.

Phase III: Global scaling. Proven service lines and strong internal relationships created the conditions for geographic expansion into EMEA, LATAM, and APAC. Critically, this wasn't just replication — each regional expansion required adapting the partnerships model to local team structures and stakeholder dynamics, while maintaining the commercial and delivery standards that had made the partnership valuable in the first place.

Results

Over four years, our Google customer portfolio grew from zero to $25M in annual revenue — with 110%+ NRR every year of the engagement — while expanding margin as the model matured and delivery became more efficient.

The most significant outcome wasn't the revenue figure. It was the nature of the relationship itself. By the end of the engagement, R/GA wasn't a vendor to Google — we were embedded in their organization across geographies, with internal stakeholders who actively protected and advocated for the partnership.