AI strategies often impact multiple layers of the business, including workforce, operations and the technology stack.
When commercial real estate firm Cushman & Wakefield laid out its AI+ initiative in November, the goal was clear: embed AI across the transaction lifecycle in order to boost productivity and assist employees in daily tasks.
Since then, the company has deepened partnerships with tech vendors, rolled out generative AI-powered assistants and started to build out tools with a proprietary dataset, according to chief digital and information officer Sal Companieh.
“All of this works when multiple pieces of the puzzle come together,” Companieh said. “A technology that’s used effectively is far more impactful and generates more ROI than a technology that’s sound and engineered beautifully if there’s no training, education and actual immersion into the business.”
Successful generative AI plans aren’t easy. Technology leaders at the helm have to bring business leaders together to build up capabilities in a way that mitigates risk and supports organizational goals.
Maintaining proximity to the business and diversifying the voices at the table at all times is key, Companieh told CIO Dive.
“The person whose job it is to drive learning and development will come to the table thinking differently than the person that is there to optimize the data model, and differently than the person who is there to make sure that this can stay at scale without a cyber event,” Companieh said.
New tools, skills and positions
From a workforce perspective, Cushman & Wakefield had already started hiring complementary roles such as prompt engineers, data scientists and data architects when the AI+ initiative was announced. In other areas, the company has turned to training workers to bolster skills.
The company spent "hours upon hours" working with Microsoft to better understand how to leverage Copilot, according to Companieh. Around 50 employees gained access to the tool in a technical phase around a month ago with the next phase expected to go live in the coming weeks, Companieh said.
Cushman & Wakefield also rolled out AI writing assistant Jasper to marketing and research teams.
“We’re already live in a number of markets and it’s allowed us, in a highly complex commercial real estate environment that we’re in right now, to produce a higher volume of thought leadership and get the data and information in front of our clients at a faster pace,” Companieh said.
Cushman & Wakefield aims to use AI as a way to provide more data visibility for workers and, in turn, clients, enhancing the intersection between employee experience and client consumption.
“I would say our concentration on doing this with the talent lens in mind is not unique to us, but I’m proud that we’ve done it from the onset and not as an afterthought,” Companieh said.
Across industries, businesses are considering how best to prepare their workforce for generative AI adoption. Nearly all IT professionals and executives believe AI initiatives will fall flat without skilled teams that effectively use and work with these tools, according to a Pluralsight survey.
In the commercial real estate space, other major players like JLL and CBRE have also built training into their AI strategies.
JLL provided employees with instructions and demos to spur and explain use cases when it rolled out a conversational generative AI tool. CBRE also educated employees on responsible use when it built a self-service platform for workers to leverage generative AI tools.
Setting the business up for success
U.S. commercial real estate firms have struggled in the past few years amid major shifts in work preferences. Despite the hurdles, Cushman & Wakefield partly credits its agility to the firm’s technology foundation.
The company established a cloud-first, mobile-first mentality where deployed technology was primarily SaaS and cloud-based.
“In doing so, we afforded ourselves the privilege of [focusing] on data and automation, which makes AI a natural next step,” Companieh said.
Data-related dilemmas are a common roadblock for companies wanting to implement AI. Most chief data officers say their companies have not made changes to their data infrastructure to support generative AI plans, according to an October AWS study.
Side-stepping initial data troubles meant the company was nimble enough from a technology perspective to shift priorities in 2023, and begin thinking through how generative AI could benefit operations.
The company put together a multifaceted team, made up of learning and development, cyber, DEI, communications, customer experience, data science and AI professionals, to ensure generative AI was intertwined with product roadmaps when applicable.
At the same time, Cushman & Wakefield deployed a new operating model within the technology organization that underlined the importance of user experience.
“We had people in technology whose job it was to wake up every day and think about the experience of technology through delivery of each of our services to our clients,” Companieh said. “Now, we have a highly SaaS, cloud environment, we have proximity to the business and we have a focus on data; we have the three quadrants to be able to capitalize on the usage of AI.”
