By Jonathan Ntege Lubwama
- More than 70% of companies experiment with generative AI today, but less than 20% are willing to spend more money than they currently are on it
- AI is set to grow from a $40B market in 2022 to $1.3T in 2032
In 2023, artificial intelligence (AI) leapt from the realms of hype into the hands of real-world users, marking a new chapter in its evolution. This shift was catalyzed by advancements in generative AI, capturing the attention and capital of investors who envisioned a seismic change in our digital ecosystem.Bloomberg Intelligence projected an AI market boom from $40 billion in 2022 to $1.3 trillion by 2032, with the technology becoming the backbone of various sectors, from coding enhancements to infrastructure development.
Why This Matters: As we transition into 2024, AI has transformed from a novel concept to a pragmatic tool revolutionizing industries. Goldman Sachs Asset Management predicts that key sectors, including semiconductor production, cybersecurity, enterprise digitization, and healthcare, will uniquely harness AI, driving productivity and addressing demographic shifts worldwide.
However, the Wall Street firm did find that the mention of AI during third-quarter earnings calls showed only 29% of companies discussed artificial intelligence, down from the peak of 35% in the second quarter of 2023. The success of AI hinges on its implementation even though this is still a pipe dream. More than 70% of companies experiment with generative AI today, but less than 20% are willing to spend more money than they currently are on it.
For investors, AI’s rapid data processing capabilities are revolutionizing decision-making. This evolution represents a new paradigm where AI-augmented analytics provide a competitive edge, enabling trend identification and pattern recognition to inform investment strategies.
What’s Next: The progression of AI from a buzzword to a strategic implementer is still something companies are trying to incorporate. It’s not just about the technology itself but how businesses can seamlessly incorporate it. Pinpointing specific generative AI use cases, establishing solid processes, and crafting frameworks for optimal use are the cornerstones of successful AI integration.
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