Impacts of generative AI on businesses

2022 was a landmark year for artificial intelligence (AI), mainly due to the launch of several consumer AI apps, such as ChatGPT, DALL. E and Lensa. The common theme was the use of generative AI, which brought about a paradigm shift in the world of artificial intelligence. While the current generation of AI uses pattern recognition or rule-following methods to analyze data and make predictions, the advent of transformational architectures has opened up a new area: Generative AI. 

Generative AI can mimic the human creative process by creating new data similar to the information it was trained on, turning it from an intermediary into a (potential) participant. 

Gartner estimates that as early as 2025, more than 10% of all data will be generated by artificial intelligence, heralding a new age of human-machine collaboration. Age of WithTM.

The generative AI market is likely to double every two years over the next decade.

While generative AI is primarily gaining ground in its early days for consumer uses that could be defining the era, it also has the potential to enrich business workflows with contextual awareness and human-like decision-making, and could radically change the way we do business.

We may be just beginning to realize the impact of solutions like Google's Contact Center AI (CCAI) to enable natural language communication with customers, or industry-specific solutions like NVIDIA's BioNeMo that can accelerate drug discovery or AWS

HealthScribe genAI for automatically generated clinical records.

Generative AI is therefore attracting the interest of both traditional (e.g., venture capital, mergers and acquisitions (M&A)) and emerging resources (e.g., ecosystem partnerships). In 2022 alone, venture capitalists have invested more than $2 billion, and technology leaders have also made significant investments, such as Microsoft's $10 billion stake in OpenAI and Google's $300 million stake in Anthropic.

The far-reaching implications and potential value of generative AI deployments are accelerating the realization of experimental, consumer, and soon enterprise AI use cases. And while most media reports focus mainly on consumer use cases, the opportunities are vast and some are already materialising. However, questions remain about how individuals and businesses could use generative AI to increase efficiency, improve products, gain new experiences, or make operational changes. Likewise, we're just beginning to explore how generative AI could be commercialized and how to create sustainable business models.

However, it is important to realize that despite its meteoric growth, generative AI is still in its infancy, which carries certain risks. Some of the most important ones to be addressed relate to privacy and security, bias management, transparency and auditability of results, intellectual property rights and equal access, especially for people at higher risk of losing their jobs. So we need to balance commercialization, regulation, ethics, co-creation, and even philosophy, as well as expand the group of stakeholders who are driving generative AI beyond technologists and enthusiasts. 

Although the media focus is mainly on consumer use cases, the opportunities are vast and some of them are already being realized.

Generative AI could eventually redefine the relationship between people and technology, much like the cloud, smartphones, and the internet before it. Some analysts estimate that the generative AI market will reach $20 billion in 2032. This represents almost 20% of total AI spending, up from around 5% currently. In other words, for the next decade, the market will double every two years. 

Regardless of the numbers, we believe that the economic impact could be much greater. The aim of this report is to help understand the potential of generative AI mentioned above, while also better navigating the situation of a rapidly changing market. 

We'll start with a brief explanation of the fundamentals, discuss business and consumer use cases, focus on how market players can create sustainable business models, and conclude with some reflections and bold predictions about the future of generative AI.

This report covers the following topics:

• How generative AI works
• Generative AI use cases for consumers and businesses
• Business relationships and competition in generative AI
• Adoption and commercialization of generative AI