The odds are high that your business is one of the 95% whose efforts of moving from generative AI pilots to implementation are losing steam. If we’re right, then let us read your mind even more. The root of the matter could have less to do with tech stack sophistication and more to do with what powers your AI platform. The key? It’s data: how it’s structured, accessed, stored, and maintained. This is what truly determines the success of your data driven AI system.
Data Is a Critical Piece of the AI Puzzle
Two words: data readiness. In our experience with guiding enterprises through intelligent transformation, we can confidently say that this is what makes the difference between mere experimentation and true AI operationalization. It’s easy to talk about the glittery aspects of AI: the powerful, business-transforming capabilities of automation, personalization, and large language models (LLMs). But it’s just as important to talk about wading through a messy, fragmented data environment in order to meet those goals.
Evolving from siloed systems to a profitable enterprise with agentic AI means that businesses must learn what it takes to make it happen.
Think AI is still considered a fringe experimental tool? 40% of employees are already using it a few times a year or more. But there’s a risk. Most of those employees are using it outside of their corporate firewalls, and organizations are slow to address spotty data governance, siloed infrastructure, and migrating from complex legacy systems.
These factors can make it especially difficult to operationalize AI, leading to businesses missing out on powerful results like higher operational efficiency and ultimately revenue growth. Without robust data systems to support the logic, context, and continuous learning AI requires, even the best tools can fall flat and can potentially produce subpar outputs.
The quality of your data infrastructure can also affect the customer experience. After all, your customers are trusting your business with their data, and they expect you to use your data to make their lives easier. Knowing their needs and personalizing their experiences is possible with AI implementation, but these efforts must be underpinned by effective data management.
What Is Data Driven AI?
Data driven AI is a type of AI system powered by clean, structured, and accessible data. It’s capable of learning, predicting, and acting based on real-time insights pulled from across the enterprise.
Today’s Best Talent Are Prepared and AI-Savvy
AI is changing the talent landscape. To turn a business into an intelligent enterprise, leaders must create an intelligent workforce by preparing existing and future employees for the impact that AI will make on daily and unexpected tasks. Take note of talent who prioritize creativity, problem-solving, and data literacy. Most importantly, look for workers who take on a human-centered approach by using real-world context to critically evaluate AI-generated outputs.
When you empower your workforce with data driven AI and agentic solutions, you give them the power to transform your entire business operations.
Data Driven AI: The Key to an Intelligent Enterprise
Establishing a workforce that can collaborate with AI is critical. But to really take your business to the next level, you’ll need to ensure that your data is structured, properly governed, and readily accessible. This is how you achieve intelligent transformation. When human power and data combine, something magical happens. You’ll see results like faster decision-making, an upgraded CX, and sharper strategies that drive major growth—far beyond what traditional automation capabilities can achieve.
This isn’t just a theory. Here’s how we transformed operations for our company and our clients:
A Strategized AI Roadmap
We helped a leading streaming platform create a strategic AI roadmap that harnesses intelligent platforms to elevate viewer experiences. Our team’s efforts led to six ready-to-implement agentic AI use cases, complete with well-thought-out technical designs and a clear roadmap for implementation—all aimed at speeding up its journey to value.
RFP Process Automation
In our sales organization, we built AI assistants to auto-generate RFP responses using live repositories of brand, compliance, and legal documentation. The result was an end-to-end transformation of the RFP lifecycle and faster turnaround times, with more consistency and fewer manual inputs.
Enhancing Customer Interactions
With tools like iX Hero and iX Hello, we’re helping brands deliver real-time, multilingual support, complete with contextual memory. Customers can start a query in one language, switch devices, and pick up where they left off—because the AI is connected to the right data sources to make that continuity feel natural.
Potential Revenue Growth
We helped a transportation industry client to fundamentally shift its enterprise-wide strategy with agentic AI in a way that would center its technology strategy around its customers. By harnessing the power of AI-enabled automation, it saw $150 million in potential revenue growth.
Data as the Engine of Intelligent Enterprise
It might seem like magic, but at the end of the day, AI is powered by the right kind of data. With clean, integrated, and correct data, you can make sure that the transition from pilots to implementation will be a seamless process. It’s the businesses who do the hard work of building strong data foundations that keep their AI platforms running smoothly.
At Concentrix, we don’t believe in using agentic AI services as a short-term fix for broken systems. We use it to help businesses like yours reimagine the entire architecture from workflows to infrastructure. This way, data moves freely, intelligence scales up, and transformation blossoms.
Are you looking to turn your business into an intelligent enterprise? Find out how you can create future-proof data strategies and enter the implementation phase with data driven AI.
