As enterprises expand their ambitions for data, analytics, and AI, the Business Intelligence Competency Center (BICC) is undergoing a quiet but profound transformation. What began as a function focused on reporting and dashboards is now becoming a strategic hub essential to modern data governance, data integration, and even emerging AI and data science capabilities. Today’s BICC is no longer just a support center for BI — it is a foundational enabler of a broader, enterprise-wide data and analytics strategy.
From BI Support to Strategic Data Enablement
Historically, BICCs largely sat inside IT, finance, or another line-of-business function. Their mission was largely tactical: ensure BI platforms worked, reports ran on time, and the business was trained to use its dashboards. This legacy approach still lingers. According to the Dresner Advisory Services’ latest research, 26% of BICCs still report to IT and 20% to finance — together representing the most common organizational homes today.
But the landscape is shifting. There is a clear rise in BICCs reporting into data leadership roles — especially the chief data officer — signaling the beginning of a strategic reorientation. In 2025, 14% of BICCs report directly to the CDO, making it the third-most-prevalent reporting structure. The growth trend is unmistakable. As data leaders take accountability for enterprise data and analytics strategy, they increasingly draw the BICC into their orbit. This shift reflects a broader organizational reality: BI can no longer be isolated from data governance, data engineering, or AI. Modern data strategies demand a unified approach, and the BICC is becoming the connective tissue that holds these disciplines together.
Broader Mandates Require Broader Skills
As data leadership expands its influence, the expected skills within the BICC are evolving. Traditional business analyst roles and statistical resources remain important — and have held steady even amid the rise of generative and agentic AI. But other competencies are surging in importance.
The most notable increases include:
- Data integration and engineering
- Data preparation and pipeline development
- Data governance and stewardship
- Data science and machine learning expertise
Today, data integration and engineering skills are not optional — they are critical. In fact, 53% of BICCs in the research include data integration engineers, and the same percentage include data scientists. Nearly half (47%) include data stewards as part of their core team. And organizations with future-facing data leadership plans go even further: 70% plan to include data integration engineers, and 60% plan to include data scientists in their BICCs. This skill expansion reflects a reality many enterprises now face: success in BI, AI, and advanced analytics is built on strong data foundations. Without engineering, governance, and science disciplines integrated into the BI ecosystem, organizations struggle to scale their analytics investments.
The DSML and AI Imperative
The rise of data science, machine learning (DSML), and AI is accelerating the pressure on BICCs to evolve. DSML and AI strategies cannot succeed without:
- Clean, trusted, well-governed data
- Repeatable data integration and engineering practices
- Cross-functional collaboration between analytics, governance, and technology teams
BICCs are uniquely positioned to orchestrate these capabilities. Their mandate — to align business needs with analytics tools, processes, and data— naturally extends into supporting AI experimentation, model operationalization, and generative and agentic AI adoption. Simply put: The more organizations invest in AI, the more essential the BICC becomes.
Why BICCs Matter More Than Ever
Data leaders today aim to drive strategies that extend far beyond BI and reporting. They must unify governance, engineering, analytics, and AI into a cohesive, enterprise-wide strategy. A modern BICC provides exactly this:
- A dedicated team that translates business priorities into analytics capabilities
- A cross-functional structure that aligns data governance with BI and AI initiatives
- A scalable way to develop the critical skills — engineering, DSML, stewardship — needed for enterprise analytics success.
In short, adding or maturing a BICC is one of the most effective ways organizations can increase their odds of BI and AI success.
The Bottom Line
BICCs are no longer simply BI support teams. According to Howard Dresner, chief research officer at Dresner Advisory Services, “BICCs are evolving into essential engines for data governance, data integration, and the successful adoption of modern analytics and AI.” Without question, as more BICCs shift under data leadership — especially the CDO — they are playing a pivotal strategic role in shaping the enterprise data landscape. Given this, Dresner says, “Organizations that invest in expanding their BICC’s skills and positioning will be far better equipped to deliver trusted data, scale AI initiatives, and realize the full promise of data-driven transformation.”
