The rapid development of GenAI and its evolution into agentic AI are creating unprecedented opportunities for enterprises, unlocking new value and strategic imperatives across industries. Yet, as data becomes an increasingly critical asset, organizations face mounting pressure – and need – to harness the power of internal and external data sources effectively.

While CDAOs and technology leaders may see a clear-cut case for adopting a transformative data strategy, full C-suite buy-in is not always straightforward. Today’s CDAO should be a master communicator, capable of breaking down silos, demystifying the complex data landscape, and articulating a vision for new technologies that resonates with non-technical executives.

Working effectively with the C-suite in the current technology environment involves CDAOs demonstrating what each leader or function can gain from data strategy – from cost savings for CFOs to process optimization for COOs and a more effective talent strategy for CHROs.

Here are three strategies to engage the C-suite, drive alignment, and build a truly data-led enterprise.

1. Bring data to life – make a clear case for its value

Many C-suite leaders proclaim themselves champions of technology and innovation. Yet as they juggle competing priorities and focus on their own agendas, they may not always recognize that having a transformative data strategy is an urgent business need – and important to the success of any technology initiative. In practice, that involves CDAOs making two arguments:

First, highlight the current data gaps. CDAOs cannot assume that leaders understand the state of their current data footprint or its limitations. Concrete examples should be used to demonstrate where inefficiencies exist and how data investments can drive measurable value.

One inefficiency that many C-suite leaders understand is the need to break down silos to ensure full visibility into an organization’s data ecosystem. A large multinational organization may have many teams operating largely in a vacuum across geographies or functions; that means they may have redundant contracts with data vendors, each contracting separately to acquire the same data, but with limitations on comingling and vectorizing it.

Those duplicate contracts significantly limit ROI and increase costs; that company could see significant cost savings and efficiency gains by consolidating them into one – if they take the time to truly understand their data gaps and data footprint as an entire organization, not just siloed parts.

Second, sell the vision, not just the technology. Effective data leaders don’t just advocate for infrastructure upgrades – they paint a picture of what’s possible. To paraphrase an old advertising adage, you aren’t selling the car, but the person the car allows the buyer to be – the same applies to data.

Leaders should believe in and be able to envision the organization they can become through smart data investments.

2. Speak the language of the business

To gain traction, data strategy discussions should align data investments with business priorities. Rather than focusing on technical capabilities, CDAOs should frame data investments in straightforward terms that can resonate – like revenue growth, operational efficiency, or risk mitigation – not industry jargon.

That also means that it is imperative to truly listen to business leaders’ concerns and questions, as well as address them in the shared language of your organization’s goals and priorities. Where possible, directly address the impact of data investments on a C-suite leader’s business or function to illustrate why data investments can help them meet their goals along with those of the organization:

• For CFOs – Emphasize cost savings and ROI of data investments
• For COOs – Highlight efficiencies and process optimization
• For CHROs – Showcase how workforce analytics can inform talent strategy

By developing a working understanding of the challenges and opportunities each C-suite leader faces, CDAOs can spot relevant use cases and drive cross-functional alignment – and create more value.

3. Measure, analyze, and celebrate progress

A transformative data strategy is not a one-and-done process: It’s a constant and iterative roadmap for your business that should respond to the market, the business’ priorities, and new, increasingly capable technologies. Shaping business strategy and reimagining your organization’s approach to data requires long-term vision – and long-term action.

Measurement and analytics should be the eyes and ears of your data strategy, allowing you to chart your progress and course-correct as needed. Ask yourself the following questions – because your colleagues in the C-suite are likely to ask them, too:

• Are we quantifying the value of our data investment?
• Is our strategy aligned with business objectives?
• The market is changing rapidly. How are we evolving our data footprint?
• What pilot projects have shown the most ROI so far?

Remember, though, measurement alone isn’t enough. A successful CDAO should also proactively showcase progress to ensure that executives not only see but champion the value of their data investments. Don’t assume they understand the value of their investments – show them.

By taking a proactive approach to measurement, storytelling, and alignment, the modern CDAO can position data as a strategic driver of business success. 

Against a backdrop of surging AI investment, the ability to effectively harness data is an important differentiator. CDAOs should seize this moment – engage the C-suite, drive cross-functional collaboration, and chart a path for your organization and the future of data-driven decision-making.

The message is clear: A transformative data strategy isn’t just a technology investment – it’s a business imperative.

*Note: This publication contains general information only, and Deloitte is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor.

Deloitte shall not be responsible for any loss sustained by any person who relies on this publication.

About the Author:

As Deloitte’s U.S. Chief Data and Analytics Officer, Ashish Verma enables the firm’s executive committee as well as our clients to plan and execute new business strategies with technology innovation while driving AI into day-to-day operations, evolving key data and analytics capabilities to meet changing market dynamics, and delivering IT-enabled business transformations.

With 25 years of consulting expertise, Verma has significant experience as a leading AI and data technology strategy professional. He has partnered with Telecommunications, Media, Technology, Financial Services, Consumer and Industrial Product, Automotive, Transportation, Hospitality, Energy, Health Care and Life Services clients in the areas of domain-specific vertical solutions, M&A, customer experience, business and finance transformation solutions.