Generative AI – Is it a hype bubble?

As we all know that in recent times Artificial Intelligence (AI) has grown rapidly, and one of the most thrilling areas of this development is Generative AI. It’s a term that has been making waves in tech circles. Major marketers have jumped on the generative AI train. But what is it about Generative AI that has sparked such interest. In this blog let’s try to take a deep dive to understand Generative AI – beyond the hype.

The initial enthusiasm has now reached a feverish pitch with venture capital investments increased by a massive 425% in generative AI startups, more than 100 million ChatGPT subscribers in 2 months and almost two billion site visits per month with an average time spent of around ten minutes – like Twitter and Facebook. One is almost immediately reminded of Bitcoin and Metaverse in recent years, which similarly burst on the scene, but have quietened down a lot. Will Generative AI go the same way? So far it does not look so, instead democratization of AI at such a rapid scale makes one believe that this technology is here to stay and will be immensely disruptive. 

Generative AI is a branch of artificial intelligence (deep learning in particular) that can create new content such as images, videos, text and music. Generative AI has two types of models (1) GAN (Generative adversarial networks) and (2) GPT (Generative pre-trained transformers). The GANs are primarily used for deep fakes, and GPT is powering ChatGPT and is used to create content. Generative AI is also used in fields like drug discovery, material science and robotics. It can generate art, solve complex problems, and transform industries. 

There are five reasons why I feel that Generative AI will stay beyond the hype and means all business. There are strong underlying signals that show Generative AI’s rise is backed by fundamentally sound drivers – such as rapidly accelerating innovation, plentiful funding even in a subdued macro environment, increasing demand for human capital, growing focus among company senior management and investors, and mostly viewing GenAI to disrupt their business in the next five years.

• A recent survey by one of the known consulting firm shows that 73% of respondents either partially or fully understand GenAI, with 29% already using GenAI tools in their business, but the key insight is that 52%+ expect GenAI to have a meaningful, tangible, disruptive impact on their businesses over the next five years.

• Patenting activity in GenAI innovations has shown a massive acceleration in the last four years, growing almost 5x, from around 1,450 patents to 6,000+, or 83% compounded annual growth over the last five years. This rapid acceleration shows the belief of researchers in the immense potential GenAI holds. And right on cue, their belief was born out in 2023 when the whole world is talking about it. More importantly, we think this will continue to show acceleration in the future, as more people realise the potential this technology holds. It is worth pointing out that patenting is a non-trivial pursuit, with significant resource requirements in terms of time, labour, and money. So, each patent represents a meaningful addition of knowledge to the field in expectation of monetary rewards in the future.  Below is the innovation S-curve (Source: GlobaData) for GenAI – which identifies the disruptive innovations within AI from millions of patent filings within artificial intelligence using proprietary AI algorithms. And as can be seen, most of the innovations were either ‘emerging’ or ‘accelerating’ stages.
  

Some of the major GenAI innovations are around GenAI for coding, Generative AI for images, GenAI for designing and AI-generated media, and clearly show how broadly applicable these innovations are and their potential to impact business across industries. More importantly, what the above chart also shows is that just focusing on broader AI will mask the disruptive pockets of innovation within AI, which are the real source of disruption. 

• Another way to understand a technology’s relevance is to understand how much mind space they dominate – particularly for investors and senior management of companies. In some of the recent surveys analytics data showed a massive surge in analysts asking GenAI-related questions to the top management of companies to assess their preparedness for this emerging threat/opportunity for their business. And some companies have been very vocal about GenAI in their filing documents. NVIDIA is one to highlight here as it’s been the most consistent and most outspoken about GenAI. IBM thinks GenAI will provide explosive growth over the next ten years, starting now. Snowflake foresees consumers to be able to write their own queries on Snowflake using ChatGPT.
  
  
• One other reason why GenAI is more substance than hype is that companies across sectors are contributing in developing their human capital in this niche area. This suggests a very broad applicability across industries, and I think, there will hardly be any business in the future which will not be transformed by it. Companies invest in human capital only when they think it has the potential to generate future revenue streams or augment the current revenue base, and hiring trends is another signal of GenAI being a powerful driver of businesses in the future.
  
  
• Funding start-ups is in my view, a key driver of technology innovation. And despite the start-up funding squeeze in general, start-ups with GenAI products/services are still attracting investor dollars in a tight funding environment. Seasoned investors clearly think GenAI holds massive future potential. GlobalData a leading data research & data management firm’s deal analytics reveals that overall start-up funding has collapsed 65% since the peak of 2021, from $684 Bn to $240 Bn in 2023 (annualizing first-half trends to full-year). In comparison, start-ups with a GenAI focus are going strong with a 160% rise in the same period (annualizing first-half trends to full-year).

In summary, no doubt there is some hype but also a lot of reality. GenAI is here to stay and will only get better with future versions. Unlike previous technologies, AI can make increasingly complex decisions enabling new business opportunities. Still, AI decision-making comes with AI responsibility. Making responsible AI part of a business’s operations requires adopting new practices and appropriate AI governance.

 

 

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