As we discussed in the first article in this blog series, digital agility—our ability to pivot based on changes in the market—must be approached the same way as building a house. It must be built from the ground up.
In our second piece, Cloud Infrastructure: The Foundation for Digital Agility, we discussed why cloud infrastructure is the foundation of that “house” that makes our businesses more agile. The cloud lets us scale up or down as we need.
Today, we examine the next level of the “house”—data and AI governance and how it can be a business accelerator when done well.
Value Driven Outcomes and Business Goals as a Guiding Strategy
Before an organization embarks upon their data and AI journey (or continues it), its business goals must be their north star. The technology a business adopts succeeds only as far as it supports those goals.
All too often organizations invest in technology only to find they don’t get the ROI they had hoped for. That tech investment has to be intentional. Whether value is driven by creating scale, reducing cost and risks, increasing productivity, or a combination of all three, these core business values should be the measuring stick at every step of the journey. You can ask yourself, for example: does the information on this dashboard really help me optimize workforce efficiency, or is it just a lot of numbers in a chart nobody can interpret?
Data and AI concepts are moving into our ecosystem at a speed that is revolutionizing many aspects of life. Organizational change management and human adoption, which have since been important factors in successfully driving digitalization, are now even more important in this new era. When setting up a solid AI governance system, user adoption programs become a key element for success. Neglecting the human factor leads to situations where people stick to old habits of doing things manually. Low leadership commitment, meanwhile, creates challenges in the implementation process, causing projects to slow or stop altogether.
Building a Strong Data Foundation
A solid data foundation is the next step for organizations seeking digital agility. It requires not only the right structures and governance to ensure data is accurate, contextual, and secure, but also the leadership needed to cultivate a data culture.
Without this foundation, organizations risk undermining trust in their data, misaligning analytics with business needs, and ultimately falling short of their goals.
Building the foundation starts with an assessment of the organization’s data maturity. This means evaluating data governance alignment with business goals, data integration and accessibility across platforms, data quality, and security. It also involves understanding the organization’s human context—skill levels, leadership commitment, and clearly defined roles—vital factors that either enable or hinder success.
Gaining this understanding of both technical and human data maturity is the only way to establish trust from the start of any digital initiative. Only then can organizations move from storing information to actively using it in real time as an asset rather than a byproduct of operations.
Transforming Data into Tangible Business Value with AI
Unifying disparate data into a modern, scalable architecture creates one reliable source of truth. Trust in your data empowers people to extract the greatest value from it. Yet the sheer volume of data combined with the ongoing skills shortage requires more automation and intelligence to keep up.
Real-time, AI-powered integration and orchestration ensure insights are delivered when and where they are needed. Automation plays a critical role by healing broken data flows and maintaining lineage tracking.
Applying advanced tools such as self-healing pipelines and orchestration helps streamline and govern data operations at scale. These practices reduce technical debt and create the agility needed to pivot quickly.
It is critical to approach AI not as a bolt-on tool but as a catalyst for results across the entire data lifecycle. Without this approach, chasing the promise of AI can erode digital agility. Organizations get the most value from AI when it’s planned within the context of strong data management, governance, and specific business needs.
At CTG, we ensure that every AI investment is tightly coupled to the data foundation and broader business strategy, so that agility is realized in practice rather than just promised in principle. This alignment has allowed our clients to achieve key business outcomes including:
- Accelerated decision making. Modern BI and natural language interfaces empower non-technical business users to derive insights instantly by asking complex questions in plain English and receiving curated, actionable answers.
- Continuous process improvement. AI-driven operations, such as fraud detection or predictive analytics, are embedded directly into workflows, allowing organizations to adapt at speed while reducing manual effort and error.
- Increased trust and compliance. Data governance frameworks and secure, enterprise-specific AI solutions protect sensitive information and ensure integrity, even as collaboration and automation increase.
Examples of Data and AI in Action
Our clients have found that investing in integrated data and AI strategy allows for far faster pivots in their markets or when responding to challenges.
For example, we worked with a regional utility provider to unify its customer and operational data. They were notifying more than 12000 customers by mail about imminent updates to their water infrastructure. Without an effective way to scale their customer support, they risked losing trust with people who relied on them for running water. Through immediate access to their maintenance and customer data, they could solve each customer’s issue on the phone in less than five minutes on average.
Similarly, we set up a global manufacturer with data infrastructure that optimized its supply chain. Their data was mostly concentrated in their headquarters region, which didn’t give employees in other regions access to the data they needed. While their data was already in the cloud—a good start as we know—they relied on legacy tools that limited their scalability. Now, they’re able to immediately access data that is relevant for its many business units across the globe.
Put succinctly: how data is organized and accessed (especially with the help of AI), can mean the difference between pivoting smoothly in a critical moment, or falling behind to competition.
If you don’t feel your organization is getting the value out of its data like it should, I invite you to reach out to make data access and organization a reality. We’re here to help.
In the meantime, stay tuned for our next blog on the digital workplace’s role in digital agility.
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