The corporate world is witnessing an AI revolution. Over the past five years, AI's growth and adoption have been significant, breaking the plateau of organizations using AI between 50 and 60 percent.

Companies reaping the highest financial returns from AI are leaving competitors in their digital dust. They're scaling up their AI investments, adopting advanced practices to expedite AI development, and leveraging AI to drive revenues.

AI high performers tend to follow certain practices to unlock value and engage in frontier practices enabling AI development and deployment at scale.

High performers use modular data architectures and automated data-related processes. They engage non-technical employees in creating AI applications, illustrating how AI technology does not discriminate between coders and non-coders. It's for everyone.

End-to-end platforms for AI-related data science and application development, standardized toolsets for data pipelines, and effective risk management against potential AI-related risks (hello, privacy concerns!) are the weapons of choice for the AI victors.

Though diversity in AI teams correlates with outstanding performance, gender and ethnic diversity gaps persist. High-performing companies are actively working to bridge these gaps, providing a lesson for others to follow.

AI adoption is not always about business. Many organizations are integrating AI capabilities into their sustainability efforts and working to reduce the environmental impact of their AI use.

High performers are outspending other organizations in AI investments. A larger proportion of their digital-technology budgets are dedicated to AI, delineating the true pioneers in the field.

High performers also have an advantage in attracting AI talent, reporting less difficulty hiring for roles such as AI data scientists and data engineers. They are more likely to recruit AI talent from a range of sources, including top-tier technical universities, tech companies, and diversity-focused programs.

Hiring for AI roles can be challenging, making reskilling and upskilling existing employees a common alternative. High performers are taking more steps to build employees' AI-related skills, again underscoring their vanguard status in the AI domain.

Generative AI, with its potential to generate significant value across various industries, is a watchword for future growth. Able to increase productivity and generate billions in revenues, generative AI has the potential to revolutionize industries, automate tasks, and create tailored content at scale.

But it's not all smooth sailing — generative AI presents challenges in integrating into business operations, including intellectual property rights, biased training data, human oversight, and security and privacy concerns.

As global economic growth and productivity growth have slowed in recent years, generative AI could be a shot in the arm for productivity, helping to compensate for declining employment growth.

Companies stand to capture the potential value of generative AI while managing the risks. Policymakers, meanwhile, should plan for the future of work, support workers in transitions, and develop policies to prevent negative uses of generative AI.

Generative AI technology can reshape the nature of work. It can also offer benefits such as enhanced customer experiences, improved productivity, and innovation. Companies can develop custom generative AI model applications and realize competitive advantages.

Ultimately, the rise of intelligent businesses depends on how well they can decode and implement AI. The blueprint for success is there — now it's up to businesses to follow it.