2025 BPS Study - FINAL (11.6.25)

This step reduces risk and builds internal advocates who can help champion broader rollout efforts.

4) Prepare and release into production with training and change management

Even the best tools will fail if users aren’t trained, supported, and bought in. Organizations must be transparent about what’s changing and why. Transparency reduces resistance and proactive communication builds trust. Training should be role-specific, practical, and outcome-driven. Rather than offering general AI overviews, training should walk employees through exactly how the tool works within their specific workflow. Resources might include hands-on workshops, interactive onboarding guides, peer-led training sessions and support channels for troubleshooting. The goal is not just to teach functionality but to show how the AI tool helps each employee do their job more effectively.

5) Post-release monitoring and reinforcement

Launch is not the finish line—it’s just the start of value realization. Post-implementation, the organization should continue tracking KPIs and monitoring usage patterns to ensure adoption. Many tools fail because people simply don’t use them consistently. Technology leaders should collaborate with business unit heads to reinforce usage expectations, trouble shoot obstacles, and adjust based on real-world usage. Incentives and accountability matter. Adoption often requires both “carrots” (e.g., performance metrics, recognition) and “sticks” (e.g., performance expectations tied to usage).

6) Roll into phased implementation

Once the pilot proves successful and early lessons are integrated, the AI solution can be scaled across other departments or use cases. This phased approach minimizes disruption and allows each new phase to build on the momentum and insights of the previous one. A phased rollout not only expands AI usage strategically, it also avoids overwhelming employees and ensures that value is being captured as implementation scales. Conclusion AI is not just a new type of technology platform to be leveraged but a strategic capability within an organization. Agents and brokers can transform their business through generative AI and need to be prepared to build this new capability through organizational readiness, a clear rollout strategy, and a commitment to equip staff with the training and skills necessary to be successful. By starting with quick wins and embedding AI into real workflows, brokers can become more efficient, intelligent, and client-focused.

To learn more about Generative AI and its application for Independent Agents, visit the Big “I”’s technology resources page (https://www.independentagent.com/agency-management/technology/) . .

Generative AI: Transforming Insurance Practices

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