Organizations that plan to adopt Generative AI must first build a strong foundation of cloud computing and data analytics and nurture a culture of innovation. Putting these three building blocks in place ensures better cost management, faster adoption, and a more comprehensive transformation of an organization.
Generative AI (GenAI) has become one of the hottest topics of discussion for senior insurance leaders. There is a growing body of evidence that GenAI is capable of increasing efficiency, reducing manual tasks and creating better customer experiences across the industry.
In order to reap those benefits, an organization must start by building a robust foundation with three key components; cloud computing, data analytics, and an innovative culture that promotes upskilling. Building such a foundation takes time, investment, and endorsement from top leaders.
A foundation in the cloud
All AI applications require significant computing power and data, which only the cloud can provide on demand and at scale. Technology is developing faster than ever, and the cloud allows organizations to plug and play with different technologies, testing what works best without requiring a large investment for each trial.
We undertook an extensive three-year mission to rebuild our technology, data, and analytics platforms that put us in a prime position to deploy GenAI. This included a dramatic shift to on-demand cloud technology and software as a service (SaaS) solution while retiring our legacy systems.
Today more than 90 percent of our systems are on cloud infrastructure, 2x the global insurance benchmark- making us the insurance industry’s cloud leader. Cloud led to improvements in system stability, availability, security, and agility. While overall processing capacity has more than doubled, our information technology infrastructure costs have remained stable.
Since our migration, we have focused on ensuring that our cloud infrastructure is as cost-efficient as possible. This means mapping size to usage by evaluating the accessibility needs of various data sets and using different cloud solutions accordingly.
The cloud has raised our operational and compliance standards in emerging markets through the standardization of solutions in the business units. This helps address the challenges of adopting new technologies across markets that may differ in their stage of development.
Cloud computing lowers the costs of entry for individual data projects, increases data accessibility and quality, and allows for faster, more affordable experimentation. With the cloud we can now deploy technology infrastructure 90 per cent faster than was possible before.
Our migration to the cloud-enabled the application of AI across 25 percent of our processes, and it also created valuable opportunities to accelerate the next stage of our journey, GenAI adoption.
Demand for data
It’s widely accepted that good data is the fuel that drives AI and analytics, but obtaining, managing, and governing that data in an affordable and secure way presents a formidable challenge.
Ensuring data quality is the second cornerstone of the technology foundation required before an organization embarks on its GenAI journey.
We leveraged the cloud to simplify our data discovery and greatly lower our data costs.
First, we brought our data from closed-source systems to the cloud where it can be easily accessed. Secondly, we implemented strict data governance to ensure we have high-quality data that can be validated. We mandated regular monitoring through data governance forums, resolving over 400 data quality issues as we rebuilt our technology infrastructure systems.
Thirdly, we created a comprehensive and detailed catalog of our data to help users find what they need. Today, we have a curated database on the cloud and easy-to-use tools that enable teams from across the company to access and use that data. The cloud enabled us to become a data-driven organization.
Accelerating Innovation
Lastly, GenAI adoption becomes more effective when it is an organization-wide effort, with ideas and testing across departments. We cast a wide net for ideas and applications, and then test and learn from each case before we scale up the most successful ideas across our markets. We want GenAI to be a part of our thought processes and workflows, whether they work in finance, risk management, or human resources. This requires upskilling and nurturing of innovation.
Cloud computing allows us to train a wider, more diverse group of employees to be data-smart and to hone their innovation skills. Our AI Center of Excellence provided the tools and training to create a robust approach towards scaling our capabilities with access to the best talent, collaboration opportunities, assets, solutions, preferred partners, and expertise.
We have created a Cloud Academy to teach core technological capabilities that graduates can then adapt to their projects and initiatives, creating an engaged, inspired, and motivated talent base.
We are also embracing low-code or no-code data analytics tools that reduce the need for deep technology expertise in order to access and use data on the cloud. These tools allow more people to build, experiment, and innovate.
One example of the benefits of this execution comes from our audit department, which has implemented an interactive GenAI-powered system that leverages advanced language models from Azure OpenAI to automate aspects of the internal audit process.
Endorsement at the top
Another key component of successful GenAI adoption is senior endorsement of the organisation’s strategy to drive transformation across the organisation. We hold each of our markets’ senior leaders responsible for their progress in building the technology foundation needed for GenAI adoption.
GenAI promises to bring significant savings through greater efficiency, but saving money through efficiency only to spend more on technology and a difficult adoption process is counterproductive. Cloud computing, strong data analytics and access to innovation tools across the organisation are the three keys to reducing costs and time to market for future GenAI applications.
We have just begun our GenAI journey, but we have built a strong foundation to support our company to deliver our Purpose of helping millions of people live Healthier, Longer, Better Lives.
Ashish Jain is a senior visionary digital and technology change leader renowned for successfully initiating, leading, and implementing transformative initiatives. Ashish has a proven ability to build effective digital services, establish innovation partnerships, and lead effective change.
At AIA Group, Ashish heads the Corporate Function technology team. In the role, he delivered IFRS17 – AIA’s most extensive big data implementation while pioneering the integration of public cloud; drove business digitization and automation at scale across 18 markets; led buildout of Risk, Treasury, Investment, Finance Data platforms driving governance efficiency and data-driven management decision making. He is championing AI strategy and implementation for the Corporate office.
Outside work, Ashish can be found sweating in a hot yoga studio or running by the Hong Kong Harbourfront.
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