Generative AI represents unprecedented value generation and business leaders need to be aware of all the use cases where it can be applied.
Today, leaders are leveraging this technology to overcome common and time-consuming challenges in a variety of areas. According to McKinsey & Company, it is estimated that 75% of the value of generative AI will manifest itself in customer operations, marketing and sales, software engineering, and research and development (R&D).
In this blog, you will discover real use cases applied to each sector. For more information, feel free to download the report from our partner Google Cloud: The executive’s guide to generative AI.
When a new technology is advancing as fast as Gen AI is, it can be hard to keep up. The accelerating evolution of Gen AI is radically transforming the way organisations work and approach overcoming their challenges and meeting their goals.
This breakneck progress has not only altered expectations in terms of speed and efficiency, but has also opened up a range of previously unexplored possibilities. The speed with which generative AI has been integrated into various sectors, from retail to healthcare, demonstrates the urgency of adapting and adopting agile strategies to fully capitalise on its benefits. Those organisations that manage to keep up and proactively embrace this technological revolution are the ones that are positioned to lead in a technology world that is changing at a brutal speed.
In this dynamic context, it is essential to explore how generative AI is being applied to specific use cases, opening up new perspectives and challenging conventional boundaries in each sector. From retail to financial services, each area presents unique opportunities to leverage the capabilities of generative AI, enabling businesses to innovate, improve efficiency and redefine processes in this exciting new technological paradigm.
Organisations are already applying Large Scale Language Models (LLMs) in sector-specific use cases such as these:
1- Retail and CPG
- Creative assistance
- Conversational commerce
- Customer service automation
- New product development
2- Media and entertainment
- Multimedia content discovery
- Creative assistance
- Internal document and media search
- Branded consumer interactions
- Content overview and metadata
3- Financial services
- Priority use cases
- Enhanced virtual assistants
- Capital markets research
- Regulatory and compliance assistant
- Customised financial recommendations
4- Manufacturing
- Machine-generated events monitoring
- customer service automation
- Document search and synthesis
- Product/content catalog discovery
- Supply chain advisor
5- Healthcare and life sciences
- Digital patient concierge
- Public and private contextual search
- Expedite Prior Authorization (PA)
- Clinical trial report generation
6- Telecommunications service providers
- Customer or employee service automation
- Network planning and operations
- Advertising and creative content assistance
- Employee knowledge search
- Test or code script generation
- Contract analysis and negotiation
If you want to see more use cases and their descriptions, feel free to download the guide from our partner Google Cloud: The executive’s guide to generative AI.
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