Cushman & Wakefield's AI Foundation

Most large enterprises grapple with AI transformation through fragmented efforts, siloed data, and elusive outcomes. Cushman & Wakefield, the global commercial real estate firm, took a different route, spending four years constructing a trustworthy, scalable enterprise AI core. This involved embedding technologists directly into business units under a product operating model, prioritizing human behavior and trust over the fleeting trend of AI pilots.

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Companies working on this

Profiles of the companies named in this story, with founding year, headquarters, and a short description from our database.

Databricks

A unified data analytics and AI platform built on the lakehouse architecture.

Founded

2013

Location

San Francisco, United States

Valuation

$190.0B

Sal Companieh, Cushman & Wakefield's Chief Digital and Information Officer, told CIO.com that this approach, dubbed the "Cushman Way," focused on building a robust data foundation that would make any AI pilot meaningful. This top-down strategy, coupled with augmenting data, helped build trust and strengthened their data infrastructure.

Building Trust and Alignment

The firm's biggest challenge was managing varying levels of maturity across the organization. While others chased technology, Cushman & Wakefield anchored on human behavior and trust generation. This focus ensured that when AI adoption surged, their top-down strategy was already in place, targeting significant go-to-market or employee experience transformations.

A key shift occurred three and a half years ago: outside of cybersecurity and infrastructure, all technology investment required co-creation and co-presentation with a business leader. This ensured technology initiatives directly aligned with firmwide priorities, with every technologist able to connect their work to the company's earnings calls.

A Unified Platform, Flexible Execution

Cushman & Wakefield's strategy hinges on three pillars: an operating model preventing duplication, a financial investment model aligning capital to firmwide capabilities, and enterprise standards for uniform technology approaches with business-unit-level flexibility. The company has matured its operating model three times in four years, continuously building flexibility as a core skill.

The firm partnered with Databricks, viewing the relationship as a co-creation partnership with shared leadership and culture. They sought a product roadmap that aligned with their future capabilities, not just current needs.

Databricks' platform enables Cushman & Wakefield to build modular capabilities that can be assembled for specific business units. They are leveraging Databricks' Genie for natural-language data governance, allowing employees to check data quality and governance policies without deep technical expertise.

Measurable Outcomes and Future Vision

This strategic approach has dramatically reduced the time from idea to outcome, shrinking it from months to days. This speed has materially reduced the time needed to onboard clients and acquisitions.

The most significant outcome, however, is the shift in human behavior, reducing resistance to change. Complex questions that once required extensive communication are now instantly accessible.

Companieh advises IT leaders to not underestimate the human element in AI transformation, emphasizing the need for genuine education on both opportunities and foundational requirements. Balancing an outside-in perspective with internal needs is critical for shaping the future of work and industries.