HumanXP advises executives on enterprise platforms, data foundations, and AI that reaches production and stays there. The counsel comes from an operator who has carried the budget, the audit, and the outage, not from the sidelines.
Most technology strategies fail in the same handful of places. I work on those, with the person who is accountable for the outcome, and leave behind an operating model your team runs without me.
Bringing acquired businesses onto shared platforms one wave at a time, selecting and governing integrators, and getting each cutover done without revenue disruption.
Decision rights, reference patterns, systems of record, and a governed data foundation with named owners, so teams move fast inside guardrails.
Use-case selection, business cases, pilot-to-production gates, and the change work that makes a deployment stick after launch.
Risk-tiered intake, acceptable use, human oversight, model evaluation, and production readiness, written with Legal, Security, and Risk and built to pass an audit.
Single intake and prioritization, lane-based capacity, vendor and MSP selection and performance, and the SOX, PCI, and SOC 2 discipline a public company needs.
Decision rights, service lanes, stakeholder alignment, and adoption measurement, so a new way of working survives the people who designed it.
Four engagements, each led directly. The figures are the ones I would put in front of a board.
One of the largest automotive services companies in the United States, NASDAQ-listed, with 12 consumer brands and more than 5,200 franchise and company-operated locations, built through acquisition. Lawrence joined as an advisor and converted to the vice president role that owned enterprise delivery, reporting to the CIO.
The inherited estate was a dozen acquisition-era systems, three business-unit CIOs, and a control environment still maturing after the IPO. I led the multi-year program to bring the acquired brands onto shared enterprise platforms, with a single cloud ERP across finance, supply chain, service contracts, warranty, entitlements, and billing as the anchor. Brands moved in waves, each going live at 99.9% uptime with no revenue disruption, with the remaining brands sequenced on the same roadmap at handoff.
I built the governed enterprise data platform with named data owners and one system of record per domain, and authored the responsible-AI framework with risk-tiered intake and production gates. Under it, computer vision assessing roughly 400 vehicles a day, an eleven-use-case voice AI program, and multi-agent workflows went from pilot to production with measured ROI. Generative AI embedded in the technology organization's own work took audit and compliance coverage up tenfold without added headcount.
Alongside, I redesigned the IT operating model into function-aligned service lanes, sourced and governed the delivery partners behind the platform estate, and carried SOX application controls, PCI DSS across all brands, SOC 2 Type II, and GDPR/CCPA through audit.
A top-5 global research university needed a generative AI platform its whole community could use, inside security, privacy, and acceptable-use standards an institution of that standing does not relax.
I led design, build, and university-wide rollout of a platform serving 12 large language models to 22,000 students and staff through a LangChain orchestration layer. The governance bar was defined first and the product was built to clear it, which is the pattern I now recommend to every enterprise AI program.
The result was broad adoption without a security or privacy exception, and a reusable model for how an institution adds new models and use cases as they appear.
One of the world's largest energy equipment manufacturers ran lead, quote, order, and sales processes differently across business units, with the CMO and two regional chief sales officers as the executive stakeholders.
I led the enterprise lead-to-order consolidation, deploying Dynamics 365 with CPQ as the corporate standard, and consolidated CRM, field service, PLM, and ERP processes and master data across business units, including systems inherited through acquisition. A global power and energy technology company followed with work of the same shape.
The lasting result was one commercial process and one set of customer and product data across units that had previously operated as separate companies.
A top-20 US private research university engaged HumanXP to lead web, emerging technology, and innovation, and the engagement converted into a senior director role.
I replaced the custom web application estate with Salesforce Service Cloud and turned the application development team into a Salesforce delivery organization. A Gartner-based IT cost benchmark and capability assessment set the operating model baseline and investment priorities. Predictive analytics on BigQuery supported executive decisions.
I also conceived and launched a regional applied-AI community as founding director, convening researchers, startups, and industry partners.
HumanXP is Lawrence Eribarne's practice, founded in 2019. There is no bench and no handoff; the person you talk to is the person who does the work.
Lawrence Eribarne has spent more than twenty years leading enterprise technology, most recently as Vice President, Solution Delivery at Driven Brands, a $2B NASDAQ-listed automotive services company with 12 consumer brands and more than 5,200 locations. There he led an 80-plus person organization of employees, managed service providers, and integrators, shaped a $30–50M annual portfolio, led the multi-year consolidation of acquired brands onto shared enterprise platforms, built the governed data platform, authored the responsible-AI framework, and carried SOX, PCI DSS, and SOC 2 through audit in the years after the company's IPO.
Before Driven he was a partner in Enaxis Consulting, a Fortune 500 CIO and CISO advisory practice that doubled and was acquired by Accenture, where he carried revenue and margin accountability, led cloud migration and sourcing programs including a ~$100M outsourcing selection for a global mining company, and advised energy and industrial clients on technology strategy and NIST-based security programs. Earlier he founded the Global IT PMO and chaired the Enterprise Architecture Review Board at Huntsman, a $12B chemical manufacturer, and ran global service delivery for 22,000 users in 110 countries at Intertek.
LinkedIn · lawrence@humanxp.com
Short pieces on the problems I see most often. Written for executives who have to decide, not for people who want to be impressed.
A risk-tiered framework that lets low-risk use cases move through pre-approved paths while higher-risk ones get real review, and why the evidence has to come out of the systems rather than a spreadsheet.
Systems of record, named owners, and one client identity across acquired businesses are the difference between integrations that hold and integrations that quietly fail three years later.
The hard part of enterprise AI is not building it. It is the intake, the gates, the roles, and the measurement that decide whether anything survives contact with operations.
Employee experience and customer experience are one system. Technology that makes the front line's day worse eventually shows up in the customer's.
What to assess about an organization before anyone draws a roadmap, and the handful of readiness signals that predict whether a transformation lands.
Executive advisory, interim leadership, speaking, and writing. One address, read by the person who will answer.
Based in Dallas, Texas. Working across the United States.
How engagements start. A conversation about the decision in front of you. From there, most work takes one of three shapes: an assessment with a decision ledger and a stop-list in the first weeks, an interim executive seat, or an advisory relationship alongside your leadership team.