Generative AI: The next digital revolution

In 1989, English computer scientist Sir Tim Berners-Lee began working on a project to facilitate the global exchange of information, creating what we now know as the World Wide Web. This invention has permanently altered the way people interact with technology, from revolutionizing how humans communicate, collaborate, and share ideas to transforming commerce, education, entertainment, and countless other aspects of our daily lives.

Fast forward to today, and we are witnessing another technological leap, perhaps as monumental as the invention of the internet. That technology is generative artificial intelligence (gen AI).

Generative AI, a subset of artificial intelligence, has already taken the world by storm. By relying on large language models (LLMs) and vast datasets, gen AI can produce content in seconds, including text, images, audio, video, and code.

With the advent of generative AI, applications such as OpenAI's ChatGPT, Google Bard, and Microsoft's Bing Chat have shown the potential for enhancing human creativity and productivity.

A recent study by McKinsey Digital estimates that generative AI could bring in an additional $4 trillion in economic value annually.¹ In addition, software development cycles could double,² and our own experience shows a 30%–40% improvement in collaboration and decision-making.

Across industries, generative AI promises to transform how we work, enhancing human abilities. Here are a few examples:

1. Automating repetitive and time-consuming tasks: Generative AI allows employees to free up time and focus on more challenging and creative activities. The technology can increase productivity and minimize errors by analyzing unstructured data, supporting decision-making, and automating workflows.
2. Accelerating time to market: Generative AI can support ideation, concept development, and prototyping through big data analysis, enabling the creation of products faster and more efficiently.
3. Personalizing customer experiences: Generative AI can improve how organizations interact with consumers through tailored interactions and highly customized content, thereby improving customer satisfaction and loyalty.
4. Advancing tech adoption: Generative AI simplifies digitization efforts by automating tasks, generating content, analyzing data, and personalizing training, making human-technology interaction easier.

Although the shift to becoming an AI-first enterprise isn't easy, enterprise leaders must do it quickly. In fact, 57% percent of Fortune 1000 companies report that their boards expect a double-digit increase in revenue from AI and machine learning investments in the coming fiscal year.³

One of the industries that can benefit the most from generative AI is insurance, where AI's predictive and statistical uses can be extremely beneficial for underwriters and actuaries.

Insurance is all about probability and statistics – a sweet spot for AI. Generative AI can analyze large amounts of data from customers' feedback, claims artifacts, climate change records, local weather patterns, economic conditions, and demographic trends. This gives underwriters and actuaries insights that support more accurate risk assessments and pricing to make the claims process effective and efficient. Here are a few examples:

1. Enhanced policies and claims management: AI can identify potential risks and provide information for faster and improved underwriting decisions by analyzing unstructured data, such as customer reviews, social media posts, and press coverage.
2. Improved communication and customer service: Generative AI can automatically generate easy-to-understand policy summaries and coverage explanations, leading to better communication and customer relationships.
3. Global agility: For many insurers, conducting business in one language significantly inhibits growth. Generative AI can provide multilingual customer service by translating customer queries and responding in the preferred language.

For instance, one of the largest global reinsurers significantly increased its underwriting response time using AI to prevent market share loss against competitors. This company redesigned its internal processes and digitally transformed its IT systems, laying the foundations for AI and machine learning technologies. The application of AI algorithms and data automation led to a sustainable acceleration of the company's underwriting process, increasing overall efficiency and improving risk analysis accuracy.

As the possibilities from gen AI sweep across industries, enterprises face a dilemma. On the one hand, leaders cannot spend too long crafting the perfect generative AI strategy and miss out on opportunities. On the other hand, they must not rush in without the right foundations in place.

We know that hands-on lessons from real-world scenarios are invaluable, especially as technology is changing so fast. Based on our experience helping enterprises scale AI, here are our recommendations:

1. Identify use case viability: While many use cases exist, generative AI is not a one-size-fits-all solution. The first step is to understand your business' critical challenges where it can deliver the greatest impact.
2. Develop talent and expertise: Once you've identified promising use cases, ask yourself – does your business have the resources to bring them to life? We suggest creating a generative AI center of excellence (CoE) to train employees for new roles like prompt engineers, prompt-compliance checkers, and customer-protection officers.
3. Build trust with governance: Generative AI, like all technologies, is not infallible. For enterprise leaders, demonstrating that AI practices prioritize transparency, fairness, and accountability is critical – especially as the technology becomes mainstream.
4. Set expectations: Once you've chosen a pilot project, have a team in place, and have incorporated responsible AI safety measures, you must actively educate stakeholders on what they should and shouldn't expect from generative AI.
5. Tap into your partner ecosystem: Technology partners can be especially valuable for developing generative AI programs. Whereas in-house talent may have only worked on a handful of AI projects, technology service providers can share their experiences from leading hundreds of projects across industries.

Put together, these building blocks lead to a major shift for enterprises. In the past, companies might have used AI to automate customer service chats, solely focusing on productivity or cost savings. Now, with a more comprehensive approach, organizations are eager to harness AI's full potential, unlocking insights that transform decision-making and business strategy across the enterprise.

Like the invention of the first web browser, generative AI stands at the cusp of a digital revolution, ready to reshape our world in profound ways. As we embrace this transformative technology, it's important to remember that the power of AI, like any tool, lies in its responsible and creative application.