Market Data Matters is our industry newsletter with musings, observations and ideas regarding the challenges and opportunities facing market data management leaders.
Last year, Market Data Matters looked at the growing influence of the Chief Data Officer (CDO) in market data management.
What interested us then was the increasing focus on value. The conversation was moving beyond understanding market data spend towards what firms get from the data they consume, and whether they could be getting more from it.
A year on, AI has added another dimension.
A recent A-Team Insight article highlights a challenge many organizations are now grappling with: AI has generated a proliferation of pilots, tools and experiments, without necessarily delivering a proportionate level of results. At the same time, CDOs are taking on greater responsibility for the data quality, governance and accountability underpinning those initiatives.
It raises a further question for the CDO. If the market data conversation has moved from cost towards value, and AI is now creating the same demand to demonstrate value, how much of that responsibility should ultimately sit with the CDO?
We caught up with Amjad Zoghbi, CTO at TRG Screen, to get his perspective.
There is an obvious reason why AI is landing in the CDO's world: AI depends on data.
For Amjad, that doesn't change the fundamentals. Data still needs to be accessible, reliable and properly governed. Firms still need visibility and cost control. And they need to understand what their data can and cannot be used for.
We've explored the importance of getting the underlying data foundations right before, and Amjad's view remains simple: “AI needs data. So good data means better AI.”
What AI does change is the scale, speed and complexity of the challenge.
Market data provides a good example. As firms use market data within AI applications, existing questions around governance and licensing take on new dimensions. Can vendor data be used within an AI model? Does training a model constitute a different form of usage? What happens if data remains embedded after a license has ended?
These aren't new questions around data rights and governance. But AI is forcing firms to answer them in new contexts, and quickly.
The question of value isn't new. But determining value from AI is different to determining the value of market data.
“The usage is easy. We have visibility from the get-go,” he says. “The value calculation is much more complex because AI is everywhere.”
An organization can know how much it is spending on AI and where that consumption is taking place. But AI can touch everything from development and operations to sales, HR and marketing. Knowing what was consumed doesn't necessarily tell you what it achieved.
Activity isn't the same as value.
Using AI to perform an existing task faster or more efficiently may deliver clear benefits. But the bigger opportunity lies in enabling something different; new capabilities, better outcomes or a genuine point of differentiation.
AI brings the role closer than ever to conversations about business value. At the same time, it creates a growing list of governance responsibilities around data quality, usage, licensing, security, cost and accountability.
As the CDO becomes more central to the value conversation, AI also risks pulling the role back towards that of gatekeeper.
Does that make the CDO a kind of Chief Value Officer?
Amjad is cautious about going that far. “I think it would be difficult for one person, or even one function, to own the value of it,” he says.
Instead, he sees the CDO providing the visibility, framework and guardrails needed to understand value. The CDO can show a business unit’s input and outputs, what it costs and how it can be used. But judging whether that investment has delivered value ultimately sits with the business using it.
Governance doesn't have to be the opposite of value creation. Done well, it enables it.
So, is the CDO becoming a CVO? Not quite. But the direction of travel is clear.
Market data has already brought the CDO closer to the value conversation. AI raises the stakes: increasing the need for governance and control while putting even greater emphasis on what those investments actually deliver.
The opportunity is to make sure one doesn't come at the expense of the other. The CDO may not own the business outcome, but they increasingly provide the foundations, visibility and guardrails that allow value to be realized and demonstrated.
That, ultimately, is the shift: from governing data to helping the business get more from it.