By Marc Staut.
Data is at the core of incorporating AI and automation into your firm’s workflows. Without a deliberate data strategy, these initiatives can fall short.
What is a data strategy? It’s a blueprint for how your firm manages, leverages and harnesses data assets. Any firm considering an AI-driven technology or planning to leverage automation needs to collect data, store it securely and make it readily available for analysis and decision making.
Every firm should view data strategy as a core business initiative, not just an IT responsibility.
Data ownership is a firm-wide responsibility
A common misconception among firm leaders is that data strategy falls solely under IT because IT manages databases. However, data strategy extends beyond the technical management of databases—it covers the entire lifecycle and usage of data within the firm.
From partners to support staff, every team member touches or relies on data to perform their role effectively. When leaders assign data responsibility solely to IT, they limit the firm’s ability to leverage data to its full potential.
For example, AI and automation can redefine tasks and client interactions, but both need reliable, structured data to deliver meaningful outcomes. AI models must train on firm-specific data, while automation relies on data integration across systems. If data isn’t accessible, accurate or well-managed, these tools won’t yield the return on investment the firm hopes to achieve.
Treat data as an asset
The first step in your data strategy should be treating data like any valuable asset—cash, brand equity, or talent. When you treat data as an asset, it becomes part of the strategic conversation. It influences decision-making, client relationships and service delivery. Just as you wouldn’t allow cash to be unaccounted for or talent to be mismanaged, you have to care for and maintain data.
Taking a strategic approach to data means ensuring it’s clean, accurate, traceable and explainable. These principles form the basis of what’s often referred to as Explainable AI (XAI). XAI ensures stakeholders can trust and understand AI-driven insights.
If you want to use data for advanced analytics and insights, consider whether your data strategy incorporates these four data characteristics, as they directly impact the reliability of data-driven decisions.
Build trust through data quality
Another foundational aspect of your data strategy is committing to quality data. Without this, any insights you derive from the data can be questioned and even dismissed.
We see this often in firms that haven’t committed to data quality, so data quality is inconsistent and people aren’t confident in the underlying data’s accuracy. Someone presents a data-driven report and makes a recommendation, but stakeholders challenge its validity due to a lack of data trust.
For a data strategy to be effective, firm leadership must establish clear standards and practices to ensure data accuracy, consistency and transparency. When everyone in the firm agrees on data quality standards, the firm can confidently base decisions on data, knowing the information is reliable.
Support AI and automation with data
The promise of AI and automation inspires many firms to consider their potential. But without accessible, structured data, these technologies can’t function effectively. Moving between systems, integrating workflows, and automating processes all depend on consistent and readily available data.
Every department in your firm generates and uses data, and each has unique needs and responsibilities. AI models and automation tools require data from all areas, including marketing, HR, admin, and client service departments. Making data accessible firm-wide ensures these technologies can operate seamlessly to improve productivity and client service.
The role of firm leadership in data strategy
Data strategy requires more than just IT’s input—it needs firm leadership’s active involvement. A commitment to a data strategy from the top makes it essential to the entire firm and sets a tone reinforcing data’s value and role in the firm’s success. Encourage every team member to contribute to data quality and ensure everyone understands and adheres to established data governance practices.
A comprehensive data strategy positions your firm to leverage emerging technologies confidently. As we look to the future, treating data as a shared responsibility and a mission-critical asset will help your firm meet the needs of a data-driven marketplace.
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Marc Staut is a shareholder and chief innovation and technology officer at Boomer Consulting, Inc.
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Tags: Firm Management, Technology
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