What do developers really think about artificial intelligence (AI)? To many, AI is synonymous with innovation. While some noisy naysayers on the sidelines may cry the promise of generative AI (GenAI) is overhyped, the reality experienced by actual developers and leaders in the digital trenches working with GenAI and large language models (LLMs) tells a clear story: AI is a top priority in the enterprise today because it has already delivered real, tangible business benefits.

In Kong's [2024 API Impact Report](https://konghq.com/resources/reports/ai-and-api-adoption-challenges)2024 API Impact Report survey of developers and business leaders, we found that **83% say AI investments have created the opportunity for new products or services in the last year**. It's probably not surprising to hear then that **92% report that AI is a priority** in the year ahead.

Clearly, the GenAI age is not only here but well underway. 

Organizations are scrambling to adopt and integrate GenAI and LLMs into their products and services. But the rush to adopt AI paired with a disconnect between how employees work and employers' policies has led this moment in AI history to feel a bit like the Wild West — with policies, rules, and best practices disregarded or worked around. 

Our research finds that most organizations have AI guidelines or regulations in place, but **60% of people say they ignore or find ways to work around their organization's AI-usage rules**.

The task at hand has moved beyond figuring out if AI can deliver business value to determining how to quickly adopt AI without compromising on security and compliance.

What does all this mean for businesses? First, it shows that enterprises are adapting faster to better respond to new trends and technologies — but they still need to move even faster. Second, it spotlights the need for new solutions to ensure the security and compliance businesses demand around data. Finally, it shows that one of the biggest enablers of future opportunities can also become a vulnerability if mishandled.

In this blog post, we'll look at these three points as we explore how developers and businesses are faring in the early days of GenAI. We'll explore what the people working with GenAI and LLMs are seeing today — and what they foresee in the future.

## Businesses are more agile than ever — but there's work to be done yet

Big businesses and enterprises aren't historically renowned for their agility. But the promise of new opportunities seems to be leading many organizations to quickly respond to the rise of GenAI and LLMs. And this response shows an agility that was lacking in enterprises during previous watershed moments in tech — like cloud or mobile.

It takes time for policies to be put in place around new and disruptive technologies. When users are more eager and willing to adopt new tools than their organizations, organizations are often left playing catch-up. Think back to companies in the 1990s that banned internet browsers and e-mail — or, more recently, banned mobile devices for work purposes. Even more recently still, think back to Fortune 500 companies that wouldn't allow developers to use AWS.

But, thanks to the accessibility and unparalleled allure of GenAI and LLMs, the speed at which individuals are adopting these technologies outpaces previous technological breakthroughs. Fortunately, most organizations are at least trying to keep up. 

**80% of organizations have guidelines or restrictions on AI use**, according to our survey. Great news, right? The problem is that most workers are ignoring those. And the tools organizations are using to enforce the rules are either not cutting it or nonexistent.

## Solutions are needed to secure and govern AI usage

Though the majority of people surveyed report their organizations have AI restrictions, 60% of people say they find ways around their employer's AI-usage rules.

Employees will use GenAI — they already are. To make the most of the opportunities these technologies present, organizations must figure out how to address the challenges that come with it, like what it means for data governance or regulations.

Solutions like the [AI gateway](https://konghq.com/blog/enterprise/what-is-an-ai-gateway)AI gateway exist to put guardrails in place and ensure security and compliance around GenAI usage without limiting developer productivity. With an AI gateway, organizations can move swiftly into the uncharted waters of the AI age without throwing caution to the wind.

*A well-defined, robust governance playbook for responsible AI adoption is key. To learn more about how to securely implement AI in your organization, check out our eBook on developing your organization’s AI governance playbook, *[*Navigating AI Innovation: A Playbook for Secure and Governable LLM Integration*](https://konghq.com/resources/e-book/ai-governance-playbook-innovation-meets-security)*Navigating AI Innovation: A Playbook for Secure and Governable LLM Integration**.*

## AI and APIs are big business (and a potential vulnerability)

APIs are a core part of the organization for at least 85% of Fortune 100 companies. APIs enable seamless and superior customer experiences, speed up time to market, and lead to the creation of innovative new business opportunities. And **nearly half say their organization needs to be more aware of the business value of APIs**. 

In addition, our survey finds that t**he most critical aspect of API management in the next 1 to 2 years will be the integration with AI** — followed closely by API security, compliance, and governance.

Moving into 2025, the focus for many organizations will remain on AI and APIs. AI and APIs are inextricably linked, with APIs essentially serving as the eyes, ears, and hands for AI. And while AI enables our platforms to become intelligent, APIs are what build the platforms. This is why a strong API strategy is the foundation for AI innovation: starting with observability, security, and governance as a base allows organizations to adopt AI quickly, without opening them up to vulnerabilities.  

But what do all those API and AI innovations and efficiencies add up to in the big picture?

According to our research, **the global economic impact of APIs is currently around $11.7 trillion** — and it's expected to reach $17.3 trillion by 2030. Likewise, the value of APIs to enable AI is forecasted to have a cumulative economic impact of $43 trillion by the end of this decade. 

Of course, all that tremendous upside comes with some challenges. Our research predicts a **548% growth in the forecasted annual number of API attacks by 2030**, further driving home why [API infrastructure is mission critical](https://konghq.com/blog/enterprise/apis-are-mission-critical)API infrastructure is mission critical.

## Get the 2024 API Impact Report

Want a deeper dive into the challenges and opportunities around AI and API adoption and innovation? Check out the [2024 API Impact Report](https://konghq.com/resources/reports/ai-and-api-adoption-challenges)2024 API Impact Report. 

In it, we look into the global state of AI and APis in the enterprise as told by the developers and leaders who know it best. We dig into why there's no AI without APIs — and how organizations can benefit from the symbiotic nature of the two. We explore the massive economic impact of APIs. And report how leaders and developers say AI adoption and API innovation are progressing in their organizations, including the challenges faced, benefits seen, and an honest outlook about what's next.