How many times have you talked about generative AI lately? It seems to come up in every business meeting, regardless of the agenda or topic of conversation. Given this trend, it's no surprise that enterprise spending on generative AI technology is growing at its fastest rate in history. Large global enterprises spent $15 billion on generative AI solutions in 2023, roughly 2% of the global enterprise software market in the technology's first full year. While this percentage may seem small on the surface, consider the fact that it took SaaS four years to reach that level. And by 2027, spending on generative AI is expected to be even higher, reaching $250 billion.
What does this mean? Enterprises will be heavily (and in some cases exclusively) focused on powering the AI generation of their technology stack. Is this a good thing? Of course, the answer is complicated.
Indeed, experts such as McKinsey predict that AI's impact on overall productivity could add trillions of dollars to the global economy. Overinvestment Adopting next-generation AI at the expense of building the basic foundations for success could be counterproductive for companies that haven't yet built a solid foundation for their technology stack and business processes.
To some extent, this happened in the early days of cloud. When the cloud revolution really got going in the late 2000s, business and technology leaders were focused on transformation. Limited budgets led them to divert spending from day-to-day operations. As a result, companies rolled out new, innovative business models on top of underfunded technology tools and underdeveloped processes.
The same could happen with Gen AI. While the technology promises to help companies write code, create content, research technical solutions, sell more products, and train employees, investments in Gen AI need to pay attention to the underlying aspects of the business to get the most impact.
The overarching goal is that companies need to prioritize modernization and fix issues with existing technologies and processes to make room for new and exciting innovations like gen AI.
There are six stages that companies should undertake before and while entering the world of AI.
First, optimize what you haveYour cleanup efforts start here. Assess the strength of your technology stack, examine your organizational structure, and review your foundational policies. Identify red flags and apply industry best practices to fine-tune your current state. Pay close attention to your data stack, both structured and unstructured data, which is the foundation for AI, including gen AI.
Second, it speeds up optimization.Once a company has fixed the initial issues, it can identify opportunities for improvement. Instead of gutting the process, try to standardize and improve it. Even a high-level review can refine the process and provide a competitive advantage.
Third, modernize your resources, but make sure you always keep humans involved.This is perhaps the most important step. After all, human creativity is what drives your organization's success. So, consider ways to re-platform, improve workflow design, add automation, and keep humans at the center of your processes. Free your employees to focus on higher-level work while preserving the irreplaceable value of human intelligence in the end product.
Fourth, rethink where AI can support your business strategyIs there a new market to target? A new product to introduce? A better way to serve your customers? Leaders need to inspire employees at every level of the business – operations, finance, marketing, sales, software development – to think about how they can use AI to achieve more. By reducing technology debt and harnessing the power of AI, the possibilities are endless.
Fifth, consider how to continually innovateAny transformation must be continuous and robust. Establishing a baseline and foundation is important, but as AI becomes a bigger part of your everyday business toolset, predicting success in the future will be crucial.
Finally, emphasize skills developmentIncreasing reliance on next-generation AI will require organizations to rethink and enhance certain roles by investing in upskilling and reskilling programs to give individuals the opportunity to learn new skills and transition to new roles. This will have a compounding impact on entrepreneurship: AI will enable individuals to innovate, adopt new practices, and improve the status quo, but individuals themselves will need to take an active role in acquiring new skills and managing the technology themselves.
Building an AI-powered modernization approach is based on the belief that business innovation should be sustainable.
This is one example of how a large technology company prepared for its foray into Gen AI: it had cornered the market and was comfortable in its position, but was being challenged by agile, brave and adventurous startups that were ready to embrace Gen AI without the burden of legacy infrastructure.
We worked with the company to guide the business through six stages of AI-powered modernization. We showed employees how to use gen AI to decipher thousands of lines of code in legacy systems, overcoming the company's fears of new technologies like gen AI. With the code easier to read, business leaders could identify opportunities for each stage of modernization, re-envisioning, and innovation. Now the company is leaving behind the limitations of the past and embarking on its gen AI project.
Conclusion
Gen AI is here and is expected to revolutionize business strategies going forward. Enterprises should not only invest in it, but also learn from some mistakes they made in their past cloud strategies. Enterprises should start clean-up operations by following the AI-enabled modernization mindset, embed gen AI into the core of their enterprises, and lead sustainable growth into the future.
