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The widespread adoption of AI is an inflection point for CIOs. We are charged with creating an “Intelligent Enterprise”, where business operations are reimagined, optimized, and redefined by AI at scale. How can the CIO support this shift? What are the emerging best practices?
At its core, intelligence (artificial or otherwise) is the ability to acquire and apply knowledge and skills to achieve specific outcomes. True intelligence lies in the ability to gather data, analyze it effectively, and then apply that analysis to drive actions that produce results. This is a difficult task in itself. Now, imagine trying to accomplish that at scale across an entire enterprise:
That’s the challenge of creating an Intelligent Enterprise.
The emergence of the Intelligent Enterprise took the convergence of several key market trends that have taken years to develop and mature to a point where enterprise-class standards could be met. The macro-level market trends are not new or mysteries, they include digital transformation, cloud computing, and AI. No single one of those trends alone allows for an Intelligent Enterprise. All are required to operate AI at enterprise scale. Achieving this level of operational maturity requires careful planning and execution, and it’s here where the CIO comes into play. As the leader already responsible for ensuring that enterprise systems are resilient, scalable, secure, and performant, the CIO is uniquely positioned to oversee the integration of AI into business operations.
At FICO, we have decades of experience in operationalizing AI at scale and with low latency. We have seen firsthand the challenges — and rewards — of embedding AI into mission-critical systems. My 15 years of experience operating AI systems at FICO for our own internal use as well as for consumption by our customers gives me, as the CIO, a solid foundation for discussing what every CIO needs to know about supporting an Intelligent Enterprise.
Today, we find ourselves in the midst of an “intelligence revolution” driven by data, AI, and the expectation of hyper personalization. In fact, the growth of data is a core enabler of the current wave of transformation. By 2025, it is estimated that the world will generate a staggering 181 zettabytes of data—nearly three times the amount created in 2020. To put that into perspective, 181 zettabytes is 181 followed by 27 zeros of new data. Managing this volume of data is a challenge in itself, but deriving value from it is where the real potential of the Intelligence Revolution lies.
Scaling to handle this volume of data and spanning the entire enterprise from operations to customer engagement presents a challenge unlike the ones CIOs have encountered with disparate SaaS and legacy monolithic applications of the past. The breakthrough here isn’t in AI itself, but rather in the technology that allows us to operationalize AI on an enterprise scale. Many companies are still in the pilot phase, exploring AI through small-scale proof-of-concept projects. However, when you look at how many organizations have successfully operationalized AI to deliver tangible value, the numbers are much smaller. According to Boston Consulting Group, in 2024, only 22% of companies have progressed beyond the proof-of-concept stage, and only 4% are creating substantial value from AI. The main barrier to realizing the full potential of AI is the challenge of operating it, and that’s where CIOs have a crucial role to play.
To successfully run AI at scale, CIOs must focus on integrating the right technologies, processes, and tools across the enterprise. For an Intelligent Enterprise, it means implementing AI in a way that is responsible, scalable, and can deliver real-time results with ultra-low latency. This is no small feat, and it involves overcoming four core challenges:
One solution to overcome these challenges is to leverage AI platforms that accelerate and streamline the process. These platforms integrate the necessary technologies—cloud infrastructure, responsible AI capabilities, proven models, and low-code/no-code interfaces—into one cohesive system. At FICO, we’ve developed our platform to simplify the operationalization of AI. We have developed capabilities that ensure AI decisions are transparent, accountable, and auditable. We leverage cloud infrastructure for the scale required by enterprise applications.
Our low-code/no-code options allow business users to compose solutions without needing to write code. Our cloud-based platforms are designed with built-in cybersecurity controls and regulatory compliance certifications to meet business requirements. The net result is that AI platforms like the FICO Platform accelerate the integration of AI across business functions, improve agility, and ensure that AI can scale and deliver value efficiently.
As businesses continue to evolve into Intelligent Enterprises, the CIO’s role is more important than ever. CIOs must help their organizations operationalize AI to unlock the full potential of the Intelligent Enterprise. By leveraging AI platforms and focusing on responsible AI, scalability, and ease of use, CIOs can ensure that AI delivers measurable value to the business. AI platforms offer a crucial tool for CIOs, providing the infrastructure and resources necessary to support enterprise-wide AI adoption. As we move forward, CIOs will need to embrace AI as a key part of their digital transformation strategy, ensuring that AI is operationalized and integrated across the entire business for optimal performance and success.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
Serhii Bondarenko Artificial Intelegence at Tickeron
30 July
Prashant Bansal Sr. Principal Consultant at Oracle
28 July
Carlo R.W. De Meijer Owner and Economist at MIFSA
Steve Morgan Banking Industry Market Lead at Pegasystems
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