Mastering Strategic AI: 12 Recommendations to Transform Your Organization

Did you know that private investment in AI reached a record $252.3 billion in 2024? This week, we dive into the report's 12 key recommendations "Artificial Intelligence Index Report 2025" to help you transform your organization with AI. These are actionable strategies to deepen thinking about automating processes, personalizing services, and managing change effectively.

The 12 recommendations of the report

1. AI Performance

AI performance continues to improve. In 2023, new benchmarks—MMMU, GPQA, and SWE-bench—were introduced to test the limits of advanced AI systems. In just one year, performance increased significantly: scores increased by 18.8, 48.9, and 67.3 percentage points on MMMU, GPQA, and SWE-bench, respectively. Beyond benchmarks, AI systems have made major strides in generating high-quality video, and in some contexts, language model agents have even outperformed humans in programming tasks with limited time budgets.

Consequences: It is high time for companies to adopt these advanced AI systems to improve their operational capabilities and remain competitive. Improving AI performance can lead to increased automation and operational efficiency, which can reduce costs and improve productivity.

2. Integrating AI into everyday life

AI is increasingly being integrated into everyday life, moving from the lab to practical applications. In 2023, the FDA approved 223 AI-based medical devices, up from just six in 2015. On the roads, self-driving cars are no longer experimental: Waymo, one of the largest operators in the U.S., provides more than 150,000 autonomous rides per week, while Baidu's fleet of Apollo Go robotaxis now serves many cities in China.

Implications: Businesses need to explore applications of AI in various industries to improve services and products. Integrating AI into companies' business processes can lead to major innovations and improved customer satisfaction.

3. Investing and Using AI in Business

Companies are fully committed to AI, driving record investments and increased usage, while research continues to show positive impacts on productivity. In 2024, private investment in AI in the United States reached $109.1 billion, nearly 12 times more than China's $9.3 billion and 24 times more than the United Kingdom's $4.5 billion. Generative AI has seen particularly strong momentum, attracting $33.9 billion in private investment globally, an increase of 18.7% compared to 2023. The use of AI in businesses is also accelerating: 78% of organizations reported using AI in 2024, up from 55% the year before. At the same time, a growing body of research confirms that AI boosts productivity and, in most cases, helps close skills gaps in the workforce.

Implications: Companies need to invest in AI to improve productivity and close skills gaps. The adoption of AI can lead to significant productivity gains and better operational performance.

4. U.S. leadership in AI model production

The U.S. continues to dominate the production of cutting-edge AI models, but China is closing the performance gap. In 2024, U.S.-based institutions produced 40 notable AI models, compared to 15 for China and three for Europe. Although the U.S. maintains its lead in quantity, Chinese models have quickly closed the quality gap: performance differences on major benchmarks such as MMLU and HumanEval have risen from double digits in 2023 to near parity in 2024. China continues to dominate in terms of AI publications and patents. Model development is becoming increasingly global, with notable launches in the Middle East, Latin America and Southeast Asia.

Consequences: Companies must remain competitive by investing in the development or improvement of AI models. Global competition in AI development means that companies must constantly innovate to stay ahead.

5. Responsible AI ecosystem

The responsible AI ecosystem is evolving unevenly. AI-related incidents are rising sharply, but standardized assessments of responsible AI remain rare among leading developers of industrial models. However, new benchmarks such as HELM Safety, AIR-Bench and FACTS offer promising tools for assessing factuality and safety. Among companies, there is still a gap between recognizing the risks of responsible AI and taking meaningful action. In contrast, governments are showing increased urgency: in 2024, global cooperation on AI governance has intensified, with organizations such as the OECD, EU, UN, and African Union publishing frameworks focused on transparency, trustworthiness, and other core principles of responsible AI.

Consequences: Businesses must adopt responsible AI practices to minimize risk and maximize user trust. Adopting responsible practices can help avoid costly incidents and maintain a good reputation.

6. Global Optimism Towards AI

Global optimism about AI is growing, but deep regional divisions remain. In countries such as China (83%), Indonesia (80%) and Thailand (77%), strong majorities see AI products and services as more beneficial than harmful. In contrast, optimism remains much lower in countries such as Canada (40%), the United States (39%) and the Netherlands (36%). However, sentiments are changing: since 2022, optimism has increased significantly in several previously skeptical countries, including Germany (+10%), France (+10%), Canada (+8%), Great Britain (+8%) and the United States (+4%).

Consequences: Global companies need to be aware of regional variations in optimism towards AI and adapt their communication strategies accordingly. Understanding regional sentiment can help better target AI initiatives and improve stakeholder acceptance.

7. Efficiency, accessibility and affordability of AI

AI is becoming more efficient, affordable, and accessible. Thanks to increasingly capable models, the inference cost for a system that performs at the level of GPT-3.5 has been reduced by more than 280 times between November 2022 and October 2024. At the hardware level, costs have decreased by 30% per year, while energy efficiency has improved by 40% each year. Open-weight models close the gap with closed-back models, reducing the performance difference from 8% to just 1.7% on some benchmarks in a single year. Together, these trends are rapidly lowering the barriers to advanced AI.

Consequences: Businesses must take advantage of reduced costs and improved efficiency to adopt AI. The increased accessibility of AI can lead to wider adoption and innovations in various industries.

8. Government Regulation and Investment in AI

Governments are stepping up their commitment to AI with regulations and investments. In 2024, U.S. federal agencies introduced 59 AI-related regulations, more than double the number in 2023, and issued by twice as many agencies. Globally, legislative mentions of AI have increased by 21.3% in 75 countries since 2023, marking a nine-fold increase since 2016. Alongside this growing attention, governments are investing at scale: Canada has pledged $2.4 billion, China has launched a $47.5 billion semiconductor fund, France has pledged €109 billion, India has pledged $1.25 billion, and Saudi Arabia's Transcendence project represents a $100 billion initiative.

Consequences: Companies must follow regulatory trends and participate in government initiatives to benefit from public investment. Working with governments can open up new opportunities for financing and growth.

9. Expanding AI and Computer Science Education

AI and computer science education is expanding, but gaps remain in access and readiness. Two-thirds of countries offer or plan to offer K-12 computer science education, twice as many as in 2019, with Africa and Latin America making the most progress. In the United States, the number of computer science graduates has increased by 22% over the past 10 years. However, access remains limited in many African countries due to gaps in basic infrastructure like electricity. In the U.S., 81% of K-12 computer science teachers believe that AI should be part of foundational computer science education, but less than half feel equipped to teach it.

Consequences: Companies must invest in the continuous training of their employees so that they can master AI skills. A well-trained workforce can lead to wider adoption of AI and innovations in various industries.

10. AI race in industry

The industry is leading the AI race, but the line is narrowing. Nearly 90% of notable AI models in 2024 came from industry, up from 60% in 2023, while the academy remains the leading source of highly cited research. The scale of the models continues to grow rapidly: training computation doubles every five months, datasets every eight months, and energy use every year. However, the performance gaps are narrowing: the difference in Elo score between the top-ranked models and the 10th place has fallen from 11.9% to 5.4% in one year, and the first two are now separated by only 0.7%. The border is becoming more and more competitive and more congested.

Consequences: Companies must remain at the forefront of AI innovation to remain competitive. Adopting advanced AI models can lead to significant productivity gains and better operational performance.

11. Impact of AI on Science

AI has received the highest accolades for its impact on science. The growing importance of AI is reflected in major science awards: two Nobel Prizes have recognized work that has led to deep learning (physics) and its application to protein folding (chemistry), while the Turing Award has honored groundbreaking contributions to reinforcement learning.

Consequences: The adoption of AI in scientific research can lead to major discoveries and technological advances.

12. Challenges of Complex Reasoning

Complex reasoning remains a challenge. AI models excel at tasks such as the International Mathematical Olympiad problems, but they still struggle with complex reasoning benchmarks like PlanBench. They often fail to reliably solve logical tasks even when correct solutions exist, limiting their effectiveness in high-stakes settings where accuracy is crucial.

Consequences: It is crucial to remain aware of the limitations of AI in complex reasoning and complement AI systems with human experts for tasks requiring complex reasoning. Adopting AI in the right contexts can lead to better efficiency and accuracy.

These recommendations clearly show that AI is transforming organizations in a profound and rapid way. By using AI in a systemic and reasoned way, companies can not only improve their efficiency and competitiveness, but also meet the growing expectations of stakeholders for responsibility and sustainability.

To apply these recommendations in your organization, start by assessing your specific AI needs and identifying areas where automation and personalization can have the greatest impact. Then, partner with industry leaders and academic institutions to develop tailored AI solutions. Finally, incorporate responsible AI practices to ensure the security and reliability of your systems.

Contact us to find out how Globe4Tech can help you integrate AI into your processes and increase your productivity, efficiency, customer satisfaction and bottom line.

Thank you for following my newsletter this week! We hope these recommendations inspire you to transform your organization with AI. Looking to take your AI strategy to the next level? Subscribe to stay up to date on the latest trends and actionable tips that will transform your organization. Do not hesitate to relay this newsletter and contact us to find out more.

Disclosure: This newsletter was designed by a human (me, Marc!) with the help of Le Chat par Mistral.ai for design and inspiration. The basic ideas, composition, and storytelling are the product of my three decades of leadership experience. I believe in putting into practice what I preach: using AI as a collaborator, not as a substitute for human creativity and insight.