With increasing regulatory requirements and evolving customer expectations, the MGA landscape has never been more competitive. Since 2023, when investments in generative AI were estimated to surge by over 300% across the insurance industry, MGA executives have been evaluating numerous AI solutions promising to revolutionize everything from underwriting speed to claims processing accuracy, yet many are still struggling to separate genuine innovation from marketing hype.
While AI technology holds tremendous potential for transforming MGA operations, the initial wave of implementations is revealing a gap between promises and practical results. Smart MGAs are now asking tougher questions about return on investment, implementation complexity, and measurable business impact. This critical evaluation phase represents an opportunity for the industry to move beyond experimental projects toward strategic AI adoption that delivers real value.
The looming AI reality check
Gartner released a report predicting that more than 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value, and inadequate risk controls. This high cancelation rate is not a condemnation of AI itself but a powerful indicator of the widespread challenges in its deployment. For MGAs, who operate in a highly regulated, risk-adverse environment, these factors are magnified. Many MGAs are learning (or will soon learn) that the key to AI success lies not in adopting every available solution but in carefully selecting technologies that align with specific organizational needs and deliver measurable outcomes. That same Gartner report included a survey that found only 19% of organizations have made substantial investments in agentic AI, with the majority either making cautions investments or taking a wait-and-see approach.
This caution is well-founded. A Deloitte survey of 200 US executives in 2024 provides a stark illustration of this disconnect, finding that while 76% of organizations had already implemented generative AI, less than half believed the benefits clearly outweighed the risks. This finding suggests that a rapid pace of adoption isn’t synonymous with strategic readiness. Insurers are learning that AI can’t simply be “plugged in” to a legacy system. For an AI to function effectively, it requires clean, accessible data and well-defined business processes. The rise of agentic AI (systems that can autonomously perform complex tasks) makes it essential for MGAs to go a step further. Instead of simply automating broken or inefficient processes, they must reevaluate and redefine them. This uneven perception underscores that adoption without a strategic foundation can lead to more problems than it solves.
The problem with hype-driven “agent washing”
Part of the problem, as highlighted by Gartner, is a phenomenon they call “agent washing.” This involves vendors rebranding existing technologies, like chatbots and robotic process automation as true agentic AI, even though these products lack the autonomy and complexity required of a genuine agent. Gartner estimates that of the thousands of vendors in this space, only 130 offer genuine agentic capabilities. This makes it difficult for MGAs to identify solutions that will deliver meaningful value, as many use cases promoted as agentic today don’t actually require agentic implementations. These projects often lack the maturity and agency to autonomously achieve complex business goals or follow nuanced instructions over time, leading to disappointing ROI.
PwC’s “Insurance Banana Skins” report reinforces the caution, identifying the misuse or poor governance of AI as the second-highest risk to the global insurance industry in 2025, just behind cyber-crime. Concerns center on the potential for AI-driven fraud and the risk of regulatory breaches due to inadequate internal controls. This heightened awareness of risk is a necessary counterweight to the initial excitement, encouraging MGAs to move forward with discipline rather than simply chasing the next new tool.
Beyond the hype and the strategic pivot for MGAs
This disciplined approach is what will separate the leaders from the laggards in the coming years. As the industry moves from experimental projects to strategic, value-driven deployments, the key will be to focus on a few select use cases that are both feasible and offer a clear, measurable return.
The next part of this series, we will explore which AI applications are most likely to thrive in the MGA market and which are most likely to fail, offering a roadmap for strategic adoption in a fast-changing landscape.
AI at Vertafore
Vertafore is leading at this intersection of innovation and trust, powering your possibilities in the AI era.
With Vertafore’s AI-powered platforms, you can scale your success with confidence. AI is transforming how insurance professionals work and provides tremendous potential for you and your business. Tangible AI value is coming from three main areas: generative convenience, document intelligence, and data enhancement
These foundations have been in use for years in our industry and will remain a significant percentage of AI use. AI is powering the future of the entire insurance distribution channel, and with Vertafore, you can work smarter and faster with AI solutions built at the intersection of innovation and trust.