The annual Accenture Tech Vision report has always been a beacon for the future of technology. Now in its 25th year, this year’s report AI: A Declaration of autonomy highlights four key trends that are set to reshape the tech landscape – 1) The Binary Big Bang, 2) Your Face in the Future 3) When LLMs get their Bodies and 4) The New Learning Loop. I am going to zone in on “The Binary Big Bang”, the generation-defining moment of AI transition, as a transformative force for the insurance industry. The trend name really reflects the next great evolution in AI, particularly generative AI. The Binary Big Bang tracks the emergence of agentic systems, and how they challenge conventions around software development and the cost of building digital ecosystems. It dives into a major change underway in how software is designed, what we need from it, and who uses it. And it sets the stage for always-there AI, which will be rich with autonomous agents defined by rapidly expanding digital ecosystems.
Cracking the natural language barrier
When foundation models cracked the natural language barrier, they started pushing the limits of software and programming, multiplying companies’ digital output and vastly accelerating innovation. As AI expands exponentially, this trend underscores how AI/generative AI (gen AI) is not just an add-on to existing processes but a fundamental shift in how technology is integrated into the core of insurance operations. AI models and agents are becoming integral parts of the insurance enterprise infrastructure, influencing everything from customer service and risk assessment to underwriting and claims processing. To fully harness the potential of these technologies, insurance companies need to rethink their approach to technology. Executives are in effect building AI ‘cognitive digital brains’ where the whole is greater than the sum of its parts. AI is not just about automating existing processes; it’s about creating new processes, workflows, and software that can drive innovation and efficiency.
How insurers can capitalize on agentic frameworks
So what exactly are AI agents? They are goal-oriented, autonomous systems that reason through problems, make decisions, leverage tools, and take actions on their own. AI agents are based on multimodal foundation models and can access external tools and data. With the evolution of GenAI towards agentic frameworks, insurers can go to market faster by breaking down the technology development lifecycle and delegating it towards agents:
The requirement managing agent : Bringing the industry knowledge along with best practices to effectively analyze the requirements and manage the progress, prioritization and completion.
The Code development agent : Breaking down the code creation into logical components to have a structured, function-oriented code that can be traced back towards requirements.
The testing agent : Agents programmed to perform various levels of testing mimicking the end user for accurate sampling and effective testing iterations.
Deployment and support agent : Agents that can help push the code to production and provide post-production fixes specific to environment.
Three key benefits of AI model and agent integration
Powered by intelligent data analytics, AI copilots, and sustainable AI, the integration of AI is causing three pillars of technology to emerge, each hugely beneficial to insurers: Abundance, Abstraction, and Autonomy.
Abundance: The rising costs of legacy technology mean that insurers can no longer afford to delay modernization efforts. AI and gen AI are accelerating code generation, enabling everything from legacy code reverse engineering to reducing tech debt and eliminating obsolete code. For instance, 78% of insurance executives agree that AI agents will reinvent how their organizations build digital systems. This modernization is crucial to remain competitive. The shift will enable insurers to launch new products and services more quickly, with 62% of executives ranking this as a top priority if they had unlimited software engineering resources. An equal percentage prioritize adding new features to existing products and services.
Abstraction: Gen AI is simplifying complex tasks and making them more manageable. This abstraction can lead to more efficient workflows and better user experiences for both insurance employees and customers. For example, generative AI and panoptic coaching can aid underwriting and claims decision-making, while agentic AI can drive personalization and enhance customer experiences. By creating simpler, more intuitive interfaces, AI can streamline processes and improve overall efficiency.
Autonomy: AI systems are becoming increasingly capable of making decisions and performing tasks with minimal human intervention. This leads to faster and more consistent service, reducing the potential for human error and freeing up staff to focus on more strategic tasks. Once data integration is advanced within what we are calling the ‘cognitive digital brain,’ insurers can hard-code workflows, institutional knowledge, value chains, and social interactions into a system that operates at a higher level.
AI makes the best use of data
In addition, AI is revolutionizing how insurers use data. It aids in decision-making, identifies trends, uncovers unknown facts, and provides the right data at the right time. This not only enhances efficiency but also reduces underwriting and claim costs with increased accuracy. AI and gen AI enable:
Generation of documentation, use cases, data dictionaries, and user stories
Automated configuration into new modern platforms
Rewriting for the new modern tech stack
Reimagining requirements earlier in the lifecycle
Presentation of test cases for the entire application to the business prior to new build
AI-powered underwriting pioneers
Exemplifying all of the above is QBE Insurance Group, a multinational insurance company headquartered in Sydney. To help make faster, more accurate decisions across multiple lines of business, QBE is scaling industry-leading, AI-powered underwriting solutions co-developed with Accenture. A series of learning sessions helped drive the design and build of the solutions that are now used to analyze new business submissions for completeness, appetite check and risk evaluation insights. As a result, for the product lines with solutions in production, QBE can now process 100% of the submissions they receive from brokers, greatly accelerating market response time. Through this collaboration, QBE will be able to identify and select risks more effectively, improve broker and customer experience and support growth.
Swiss Re is also working with Yukka lab to transform reinsurance underwriting by providing each of their underwriters with an AI assistant that aggregates and pre-assesses the world’s news in real time to facilitate better and faster decision-making. The goal is to reduce the underwriting cycle, improve the cost ratio and finally, reduce claims.
A paradigm shift in how insurance companies operate
The Binary Big Bang is more than just a technological shift; it’s a paradigm shift in how insurance companies operate. By integrating AI and gen AI into their core operations, insurers can achieve greater flexibility, faster development times, and enhanced innovation. The benefits of abundance, abstraction and autonomy are clear, and the industry is poised for an AI tipping point where these changes are embraced with enthusiasm. As AI continues to evolve, the insurance industry will become more efficient, more responsive, and more customer-centric, setting the stage for a new era of growth and innovation.
