At Gallagher, the push toward digital transformation has moved beyond isolated tools into a broader ecosystem strategy. That shift, led by global chief digital officer Steve Rhee (pictured), reflects a view that client complexity now demands integrated access to data, analytics, and AI. The approach is designed not only to improve efficiency, but to redefine how brokers and clients interact with risk information in real time.
Rather than layering new capabilities onto fragmented systems, the firm built a centralized platform - Gallagher Go - as a single entry-point for clients. “There are too many point solutions that serve one particular part of the business well,” Rhee said. “Our clients’ complexity is growing and we’re broadening as an organization.” The platform consolidates functions across property and casualty, benefits, and claims, allowing clients to access documents, analytics, and advisory tools in one place.
The design reflects a deliberate shift toward an ecosystem model. “Clients have one destination, a clear understanding of where all their information lives,” Rhee said. He compared the approach to a scaled digital marketplace, where services expand around a unified experience rather than being delivered separately. That model also creates the foundation for embedding AI directly into workflows, including tools that will allow clients to query policy documents and extract coverage insights.
The platform strategy is underpinned by long-term investment in data centralization. According to Rhee, decisions made more than a decade ago to unify data across the organization are now enabling more advanced AI deployment. “Ten to 15 years ago, the company made a concerted effort to centralize data, and that decision has paid off significantly,” he said.
That data becomes more valuable when combined with industry specialization. Gallagher’s domain expertise across sectors such as construction, manufacturing, and marine allows it to contextualize data in ways that competitors relying on narrower tools may struggle to replicate. “All of that data becomes genuinely proprietary when paired with our industry expertise,” Rhee said.
The ecosystem model reinforces this advantage by creating a feedback loop between platform usage and data enrichment. As clients interact with tools, review analytics, and engage with advisory services, the system captures behavioral signals that inform future insights. “We collect data within the platform in ways that point solutions simply can’t replicate,” Rhee said. “Our data feeds the ecosystem, and the ecosystem feeds the data right back.”
This continuous cycle also extends to external data sources, including insurer pricing, limits, and capacity. AI is used to extract and structure that information, enabling clients to evaluate risk scenarios at different stages from pre-submission to renewal or acquisition. “We have data that can answer those questions based on what kind of business they’re in,” Rhee said, pointing to use cases such as assessing geographic exposure or benchmarking acquisition targets.
The shift toward an integrated platform is producing measurable outcomes, particularly in client retention and engagement. According to Rhee, digital adoption has translated into incremental gains that scale across the business. “We’re driving approximately one additional point of retention,” he said, noting that even marginal improvements carry significant impact at enterprise scale.
Client engagement metrics reinforce that trend. The platform is onboarding thousands of clients each month with regular repeat usage. “Engagement levels are strong, with clients logging in multiple times a month,” Rhee said. That activity reflects both the utility of self-service tools and the broader shift toward digital interaction.
The operational implications are twofold. First, clients gain efficiency by handling routine tasks such as certificate requests or policy changes independently. “They have self-service access to cert requests, auto ID cards, and policy changes,” Rhee said. Second, brokers are able to reallocate time toward higher-value advisory work, supported by shared access to analytics within the same environment.
The result is a more balanced interaction model. “It creates higher-quality interactions with their account team,” Rhee said. Rather than replacing human engagement, the platform reframes it, allowing brokers to focus on strategic guidance while clients manage transactional needs through digital channels.
A key element of the strategy is the distinction between internal AI deployment and client-facing applications. Internally, the focus is on improving service delivery, enhancing response times, accuracy, and insight generation. “We’re focused on embedding AI at the service level,” Rhee said.
Externally, the emphasis shifts toward enabling clients to interact directly with their data. “From a client-facing standpoint, AI serves two purposes,” Rhee said. “It surfaces strong analytics and insights that clients can directly act on, and it supports the personalized, self-service experience clients are asking for.” This includes capabilities such as benchmarking performance, querying policy details, and evaluating coverage options.
That separation is intentional, reflecting a broader industry challenge where operational AI and risk advisory are often conflated. By maintaining distinct tracks, the firm aims to strengthen both service delivery and client empowerment without blurring responsibilities.
