Canadian insurers confront legacy limits as AI redefines scale, speed, and strategy in a data-driven era.
André, as the CEO of GFT Canada, you’re steering the company through a rapidly evolving insurance tech landscape—what initially drew you to this mission, and how has your vision shaped GFT’s direction in Canada?
What drew me to this mission was the opportunity to drive meaningful transformation in an industry that impacts the lives of millions—often during their most difficult and stressful moments.
Historically, the insurance sector has been slow to adopt new technologies, but that trend has shifted significantly in recent years. This transformation makes the industry especially appealing to a former technologist like me. After 12 years with GFT, I saw a unique opportunity to amplify our impact when the chance to lead GFT Canada arose four years ago.
From the outset, my vision has been to position GFT Canada as a trusted innovation partner for insurers—one that blends deep industry knowledge with hands-on technology expertise. We’ve focused on building strong partnerships and expanding our capabilities in core system modernization, digital user experience, operational efficiency, and AI-powered insights.
I’m proud that our team is helping Canadian insurers accelerate their transformation journeys with solutions that are pragmatic, scalable, and designed to deliver value quickly. This mission feels more relevant than ever, as the industry faces mounting challenges from climate change, disruptive business models, and rising operational costs.
With so many insurers accelerating their digital transformation agendas, where do you see most Property & Casualty providers currently positioned in their AI adoption journey?
Property & Casualty insurers aren’t far yet in their AI journey, but they are beginning to deploy some key solutions in three main areas of focus.
The first is the software development lifecycle. Insurers are implementing AI into their development processes in order to improve internal IT team efficiencies, enhancing speed and productivity with an array of tools. Next, they are using AI to provide employees with greater access to organization wide information. They are doing this usually via an internal chatbot of embedded search tools. With access to information that was previously siloed and held by different gatekeepers, employees will now be able to enhance their work. Lastly in the same vein of chatbots, insurers are also beginning to roll out AI claim and underwriting assistants to help with everything from fraud detection to data ingestion.
Legacy infrastructure remains a critical barrier—what makes these outdated systems so incompatible with modern customer demands and AI-powered services?
AI has heaps of potential, but it is nothing without data. Think of AI as a new employee and data as their manager. Every new employee needs to be trained by a well-informed upper level executive who knows the ins and outs of the business as well as current happenings. If they are trained by an employee who only has a cursory knowledge of operations or is rooted in the way things used to be done the employee won’t be able to do their job properly.
In the same vein, AI needs access to a holistic picture of the entire company’s data – and that data needs to be up to date. Legacy infrastructures typically have company data siloed across multiple gatekeepers and channels, making it difficult to access. And because financial institutions have been around for so long, lots of the data is no longer relevant. AI can’t make informed decisions or recommendations if it only has bits and pieces of company data or is being trained on data sets that no longer apply to operations.
Additionally, integration mechanisms are very limited in legacy systems. It’s challenging to accomplish the full benefits that generative AI solutions promise without a full integration of the technology.
When it comes to driving real impact with AI, why is operational transformation inside the organization more crucial than just launching customer-facing tools?
Operational excellence is key for insurers to stay competitive in a crowded market. While customer-facing tools are a great way to improve relationships, to truly see gains that impact the bottom line such as in productivity, AI needs to be implemented in internal processes.
By starting with internal operations, insurers can increase efficiencies by streamlining manual , time-consuming daily tasks. Additionally, with this internal experience, the company and its employees can develop trust in their own AI before deploying it to their customers.
GFT has built strong partnerships to lead cloud migration for major insurers like Beneva—what does a typical engagement with GFT look like from strategy through execution?
A typical GFT engagement begins with a strategic assessment to align cloud goals with business priorities, followed by architecture design, roadmap development, and regulatory planning. Leveraging strong partnerships with AWS, Azure, and GCP, GFT delivers secure and scalable cloud infrastructure, application modernization, and data migration. Throughout the process, GFT embeds FinOps practices to ensure financial accountability and optimize cloud spend, while providing ongoing support for performance and compliance.
As insurers rethink their application stack, what are the biggest misconceptions they have about modernization, and how do you help them overcome those?
The biggest misconception is the idea that modernization is only about technology. Insurers need to also rethink architectures and modify their own internal business processes accordingly as part of this modernization. Change management is a critical component of migration, but most companies believe modernization simply means lifting and shifting to the cloud. GFT advises insurers about this adoption concept early on in the modernization process, combining business-led assessments with deep technical analysis, to show clear modernization pathways that prioritize value, mitigate risk, and align with long-term transformation goals.
How do partnerships with platforms like Guidewire enable GFT to accelerate change for insurers, especially in laying the groundwork for scalable AI integration?
GFT’s partnerships with leading providers allow us to link our clients with the best cloud platforms on the market. Guidewire for example is making major investments into AI so that insurers can implement multiple generative AI features. At GFT we make sure the insurer can take full advantage of the benefits generated from those features by helping them develop a strategic approach. With Guidewire we can help completely transform insurers’ legacy systems by migrating their data to Guidewire Cloud. Once all of the data has been brought together and siloes have been eliminated, the company will have the strong data foundation necessary to train AI accurately and efficiently.
Beyond technology, what organizational shifts—team structures, culture, or governance—are necessary to fully capitalize on AI-driven transformation?
Despite AI’s prevalence in the media and high level conversations, the employees who are on the ground working with it day to day still don’t completely understand it. There is a lot of miscommunication and discourse around the role of AI in the everyday workforce with many employees fearing that AI will result in the loss of their jobs. In order to successfully transform a business with AI the company first needs to invest in hands-on training to help employees understand how AI fits both into the company’s overall goals as well as how it will support them in their individual roles. Once their concerns are assuaged and they are educated on the tools, they will be able to automate mundane tasks to spend more time on strategic initiatives.
What distinguishes the Canadian insurance market in terms of innovation appetite and digital readiness compared to global trends?
While the Canadian insurance market is often characterized by a cautious approach to innovation and digital transformation, they have actually already done a large amount of work to replace core systems. They are now “smart followers”, gradually optimizing their new platforms with emerging technologies like generative AI, automation solutions and analytics in order to improve underwriting, claims processing, and customer engagement. The shift towards digital-first strategies indicates a commitment to modernization, albeit at a measured pace.
As AI continues to redefine financial services, what strategic priorities should insurers set today to ensure they’re not playing catch-up tomorrow?
Although it’s important to be ready for AI adoption, insurers should avoid waiting too long to deploy the first solution. Waiting for everything to be perfect before adoption will create a major lag, resulting in a large gap between them and their competition. Instead, insurers should start with a low risk application that will help develop trust in the technology as well as give the team hands on experience. Once this initial application is rolled out, bigger use cases can begin being developed and implemented.
