AI for Executives: How to Reduce Noise and Get Results

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AI has dominated discussions, not only on the global tech scene, but also in the business world in general. The impact of applications such as ChatGPT and DALL·E has been such that consumers are now fully aware of the wealth of possibilities offered by large language models (LLM) and generative AI. Indeed, according to research from AppRadar, new AI apps have been downloaded 23.6 million times by Android users since November. Over 700 AI startups have received a combined $7.1 billion in funding in the past three months alone. Very few technological innovations have succeeded in simultaneously capturing the imagination of the worlds of technology, investors, businesses and consumers.

Given this varied interest and appetite, companies have unprecedented opportunities to experiment with and adopt new AI-based solutions. However, the breadth of potential applications available – from customer service to supply chain finance – is such that policymakers and investors face the challenge of deciding which horses to support and when. After all, those who may have recently committed resources to metaverse-adjacent technology or blockchain only to discover that real business value is still a long way off may be reluctant to follow the latest hype.

Of course, the reality is that while ChatGPT may have made AI mainstream, generative AI is actually just the latest advancement in a plethora of data science-based applications. The insurtech industry, for example, has been transformed over the past decade by data solutions that have automated processes, helped digitally address risk, increased volumes, and ultimately improved the customer experience.

I imagine that for many people, insurance companies would not be the first vertical you would associate with the adoption of advanced technologies. However, the key for these institutions is that they can immediately see the logic and business value of AI solutions. For relatively little outlay and minimal risk, they can quickly and meaningfully transform large aspects of their business. And that's the fundamental rule when we consider the best opportunities for LLMs to have a serious business impact: what can they use to give them a good return on investment with minimal risk?

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For decision-makers at large enterprises, LLMs (and AI in general) present an overwhelming number of options. Every business function can benefit from AI processing. The first thing to consider is the different maturity and level of development...