Earlier this week, we shared some insights on the overall competitive AI landscape and its more specific contributions. Today, we will unpack what these strides in AI competition and innovation mean for consumers and businesses alike.

What do all these startups and innovations mean for businesses and consumers?

At a very practical level, businesses and consumers will have a cornucopia of AI tools at their disposal to address their needs. Already, AI products are enhancing the success and competitiveness of small businesses:

— Constant Contact’s Small Business Now report showed that 91% of small businesses who use AI indicated that it contributed to their business’s success. “Our findings show that AI and marketing automation can help solve some of the biggest challenges small businesses face—attracting new customers, marketing to them and delivering a memorable experience. Small businesses recognize this opportunity, and many have already begun leveraging them to tell better stories, sell smarter and work more efficiently. Best of all, they are spending less time marketing and more time doing what they do best… running their business.”

As competition and innovation continue, AI will become more cost-efficient, and barriers to entry will keep falling—good news for both businesses and consumers.  Already, the costs of training AI models, running AI models (i.e., AI inferences), and powering AI computation with hardware are all rapidly declining. As the technology improves, AI is also becoming more efficient to use.

— Nvidia founder Jensen Huang said last month that “the cost of compute has decreased by a factor of 1 million over the past decade.”

— AI training cost has declined at an annual rate of 70% since 2020. A model that cost $4.6 million to train in 2020 cost only $450,000 in 2022—and that price tag is expected to drop even more, to just $30 by 2030.  

— AI inference cost continues to fall as well. The cost per one billion inferences is expected to drop from $10 million in 2022 to $650 in 2030.

— AI hardware costs are expected to continue falling at a 57% annual rate.  

— In 2020, the amount of compute needed to train a similarly performing neural network was 44 times less than in 2012.  

Looking ahead, the AI boom will add trillions to the economy and transform all sorts of industries for the better. According to an analysis by PwC, AI-related products and improvements will contribute $15.7 trillion to the global economy by 2030, including $3.7 trillion to the U.S. economy (14.5% of total estimated GDP). Notably: 

— 45% of the gains will come from products (as opposed to productivity improvements), which means that consumers will benefit from many new products.

— AI will increase the GDP of local economies by as much as 26% by 2030. 

— Through productivity improvements alone (marketing, R&D, software improvements, etc.), AI will add billions in revenue to not just high tech but also the banking (up to $340 billion), entertainment ($130 billion), pharmaceutical ($110 billion), and telecommunications ($100 billion) industries, according to a McKinsey analysis.

There is no doubt the generative AI revolution will provide enormous benefits to consumers, small businesses, and the U.S. economy overall. As policymakers assess the space, they should look at the facts: competition up and down the stack is strong and only getting fiercer.