In recent years, we have seen a significant increase in the use of generative artificial intelligence (generative AI) by companies to accelerate projects and solutions. This trend was evidenced by the MIT Sloan Master of Business Analytics' 2024 Capstone Project program, which connected students with organizations seeking to solve business challenges through data analysis.
An interesting finding is that generative AI, when combined with data analytics, enables companies to execute faster. While traditional machine learning approaches—now referred to as “legacy machine learning”—focus on precision and individual personalization, generative AI unlocks speed in processes and decision-making.
Accelerating Time to Market
Life sciences companies like Pfizer and Takeda are using generative AI to reduce time to market for new drugs. Pfizer has automated the knowledge transfer process, allowing thousands of scientific documents to be quickly classified and retrieved, accelerating both the discovery and production of therapies. Takeda, for its part, has analyzed data from over 500.000 clinical trials to streamline the design of new studies, accelerating the development of essential medicines.
Faster Responses to Customers
In the insurance industry, CogniSure implemented generative AI to extract critical information from thousands of PDFs and emails submitted by customers. This enabled the company to quickly process various file types, accelerating the delivery of insurance quotes. Comcast, a telecommunications company, improved its customer service by using generative AI to analyze call data and predict customer churn, enabling faster, more personalized responses during interactions.
Global shipping company CMA CGM adopted a generative AI system to provide immediate forecasts and dynamic pricing guidance. With access to fast and accurate insights, agents can efficiently provide up-to-date information to customers.
More Agile Internal and External Communication
Dick's Sporting Goods is using generative AI to create personalized email campaigns faster. By combining demographic data, purchase history, and previous interactions, the company has improved click-through rates and reduced marketing campaign preparation time. Consulting firm McKinsey & Co. has automated the labeling and classification of internal documents, ensuring that knowledge is shared efficiently among employees.
Beyond Speed: Accuracy and Workforce Impact
While speed is a significant benefit, accuracy remains crucial. Companies are implementing methods to ensure that generative AI solutions maintain high levels of accuracy. Furthermore, it's important to consider the impact of this technology on the workforce. Accenture is helping clients understand how generative AI will affect their teams, offering tools to predict these effects and plan reskilling initiatives.
Conclusion
The adoption of generative AI is redefining how businesses operate, offering unprecedented agility and efficiency. As more organizations explore this technology, we expect to see continued transformation in business processes and the way value is delivered to customers. To remain competitive, companies must balance the speed afforded by generative AI with the need for precision and effective team management.
