💰2024 AI Index Report: Key Findings, Tech Companies. Next Up Is Finance!

The AI Index Report published by Stanford University's HAI has been released. With the enormous cost of creating AI models, OpenAI's GPT-4 training cost about $78 million and Google's Gemini Ultra training cost about $191 million, the economic impact they can deliver for businesses and organizations is becoming more and more important. It turns out that the industries that can realize the highest increase in productivity with generative AI are the high-tech followed closely by the financial sector. We have summarized the economic chapter of the 502-page report.

Let's take a look at the "AI Index Report 2024" published by Stanford University's Human-Centered AI Institute (HAI) on April 15.

Chapter 4 of the 502-page report, focuses on the economic impact of AI and cites examples of maximizing work efficiency in the real world, predicting the economic impact of AI.

1. McKinsey Surveys Reduce AI Costs by 42%, Increase Revenue by 59%

With the generative AI craze of 2023, companies have gone through a lot of trials, testing out the technology in their operations. In 2024, we are already seeing more and more users across industries using it in a variety of ways. A major concern for many leaders is the possibility of large-scale labor substitution by AI.

The AI Index Report uses data from LinkedIn, McKinsey, Stack Overflow, and others to show AI-related economic trends - from hiring trends and demand for AI jobs, to corporate investment trends, to the level of AI adoption and economic impact forecasts by companies.

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10 highlights of the Economy Chapter are:

1. Generative AI investment surges to $25.2 billion - 10x increase in investment in 2023 compared to 2022.
2. AI investment is led by the U.S., $67.2 billion in ‘23 (8.7 times that of second-place China). 
3. Slight decline in AI-related jobs. AI postings decline as percentage of all job openings, influenced by a decline in demand from Big Tech. 
4. According to McKinsey, 42% of companies are using AI to reduce costs and 59% are increasing profits. AI drives work efficiency. 
5. Private AI investment declined for the second year in a row, while the number of funded AI companies increased by 41% compared to 2022.
   
6. 55% of McKinsey surveyed companies are using AI (50% in 22).
   
7. China dominated the industrial robot market with a 52.4% of installations in 2022.
   
8. In addition to industrial robots, service robots are increasing, expanding into various fields. 
9. AI increases work productivity. Research shows AI contributes to faster completion of tasks and improvement of output quality, bridging the skills gap between low- and high-skilled workers. 
10. 80% of Fortune 500 companies mention AI in their earnings reports, and 20% mention generative AI.

Since I work for Allganize, which provides work productivity AI solutions to address needs across the enterprise workforce, I found the graph above the most interesting.

There is general agreement that AI can reduce costs, but it is important to examine the evidence pointing to its impact on increasing profits for corporate adopters. The reports quantifies the benefits and cites increased revenue especially in manufacturing, services, marketing and sales, and risk management. It's a bit disappointing that there are no concrete examples of how these organizations achieved the increase in profits.

2. GPT-4, reducing task processing time by 40% and improving task quality by 40%.

In the report, HAI summarized examples of how generative AI has been used to improve work productivity. Most of them use GPT-4, and only the AT&T case has its own AI model.

• Amazon (GPT-4): Automates customer inquiry responses, reduces agent handling inquiries by more than 50%, personalizes your shopping experience.
   
• Accenture (GPT-4): Improved consultant efficiency, 25% faster and 40% better work quality, 12.2% increase in overall productivity.
   
• AT&T (own model): Streamlined call center customer service, increased calls per hour by 14.2%.
   
• Large U.S. Law Firm (GPT-4): Established a system for extracting and analyzing key information on litigation documents, reducing case processing time by 40%.
   
• CNN, BBC (GPT-4): Complex news articles, report summaries, and summaries for reports.
   
• MIT (GPT-4): Assist with administrative tasks and provide personalized instruction to students. Incorporating GPT-4 into your education system.

As you can see from the graph above, McKinsey research shows that the areas of work where companies are most likely to apply generative AI are document drafting (ad copy, technical content, etc.), personalized marketing, document summaries, image/video generation, and understanding customer needs and preferences. Certainly, there seem to be many application cases in the field of marketing and sales.

3. Predicting the Future Economic Impact of AI: High-Tech Edging Out Finance!

The AI Index Report 2024 shows the impact of generative AI on sales by industry in the graph below. For example, the high-tech industry is expected to generate $240 billion to $460 billion in revenue, with the introduction of generative AI expected to increase revenue by 4.8~9.3%.

After the high-tech industry, the most affected industry is banking. The introduction of generative AI is expected to increase sales by 2.8-4.7% and generate $200B-$340B in sales.

According to a Goldman Sachs investment report released in 2023, the adoption of AI is expected to increase annual productivity by 1.0%-1.5% over the next 10 years. AI is expected to play a big role in Japan's productivity growth.

If 2023 was the year of testing generative AI, this year is the stage where generative AI becomes a reality. B2B AI solutions are evolving to combine LLMs in the workplace to solve problems and produce sophisticated and accurate results.

Allganize is a B2B AI company providing industry-specific AI to help companies take advantage of generative AI with a speedy, low risk, and high ROI deployment. Allganize’s technology excels at processing large and complex industry documents. For example, finding answers in complex tables of corporate documents is an area where Allganize is consistently outperforming OpenAI.

Allganize’s Alli LLM app market is evolving towards full-stack AI and allows you to select and use various LLMs to suit your company's work and to use more than 100 work automation tools across all corporate functions.

If you are curious about AI-native workflow tools, contact Allganize!

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