Final preparations are being made for A-Team Group’s 16th annual Data Management Summit NYC, which will bring leaders and experts from around the world to take a deep dive into the drivers, themes and trends that are shaping the data industry for financial institutions.
Over a full day of keynote addresses and expert panel discussions, delegates will be treated to a deep dive into all aspects of the current situation in data management, with a particular focus this year on artificial intelligence and agentic processing.Speakers have been hand-picked for their expertise, experience and seniority within institutions and vendors drawn from across the ecosystem.
The event comes at a salient time for institutions’ data chiefs. AI and agents dominate the technology scene, offering huge rewards in terms of cost-saving operational automation, as well as deep research and insights that are providing organisations with the intellectual capital to boost revenue. They are also providing compliance capabilities at a time when regulators are, themselves, harnessing similar technologies to place firms under greater scrutiny.
These transformative innovations are requiring organisations to rethink their data strategies, with renewed focuses on aspects such as data quality and trust.
Governance Elevated
One key factor that has taken on additional importance as agents remove humans from data processes is governance. Always important for ensuring the safest use and distribution of data, governance policies are now the gatekeepers of data trust, ensuring not only that the information that feeds AI models and agents is of the highest quality but that the data they produce is trustworthy too.
For instance, the meaning of critical data elements – a longstanding fundament of data management – has been radically altered in the modern landscape, argues Brian Greenberg, Senior Director – Data Operating Model Lead & Data Management Practice Product Manager at BNY.
This poses new complex challenges for organisations, Greenberg told Data Management Insight.
“The concept of a ‘critical data element’ has historically served as a coping mechanism – a way for data producers to prioritise governance on the fields that were most often used in regulatory reports, management dashboards and the like,” said Greenberg, one of the speakers at the summit.
“While the concept of critical data elements remains, the ubiquity of AI tools has expanded the focus to AI-ready datasets. When an agent is given access to a dataset, it can utilise any or all of its data elements to respond to a query – often without warning.
“As a result, the approach of governing only the critical data elements has become a riskier proposition. If a dataset is made available to an AI-enabled workflow, each data element in it needs to be governed to a standard that can withstand scrutiny when it surfaces in a result,” he said.
The Summit will kick off with an Opening Keynote Fireside Chat with Samit Korgaonkar, Enterprise Data Platform & Governance at Google, who will be interviewed by Peggy Tsai, a Data Management and AI Leader who won A-Team Group’s Editor’s Recognition Award for USA Data Management Industry Professional of the Year in 2025.
The discussion, entitled Scaling AI-ready data foundations: Lessons from big tech for capital markets execution, will set the scene for the day’s sessions, all of which will cover topics that range from knowledge graphs and data products to modern data operating models and semantic layers.
New Pressure
The scaling of AI has become an important topic for data managers as the prevalence of agents has spread. The autonomous enablers need data on a huge scale and their use has, like the adoption of AI, has put new operational pressures on organisations as they seek to benefit from the streamlining capabilities that agents offer.
For instance, Tyler Frieling, Director of Applied Technology at Blackrock, argues that implementation of agents needs to be carefully considered from an enterprise point of view.
“As agents become co-workers, it’s important to think through their apprenticeship cycle; which is really the root cause of future problems,” Frieling told Data Management Insight. “Were experts brought in and made accountable for the actions of the agents being deployed or were the agents produced by the workforce that had the most passion and time?
“Traditional organisational behaviour and engineering can help us think about how agents are trained and deployed as well as the ramifications, so the other critical aspect is to not see agents as new technology but as new types of employees.”
This isn’t something that can be achieved successfully and – from a data standpoint, safely – without careful planning.
“Scale with AI is tremendously difficult for humans,” he added. “We need frameworks and rubrics in place to help us assess the situational awareness of agent teams but we also need to be sure skills and/or knowledge are known to humans so they can act appropriately.”
Market Participants
The A-Team Group Data Management Summit NYC 2026 will also hear from leading vendors and data consumers, who will deliver keynote addresses that provide industry context to the innovations that offer.
Participants will comprise Rocket Software, Element 22, Sphinx, IBM and BNY. Each will send a senior leader to detail their products and the objectives they seek to achieve.
- Data Management Summit New York City will be held on September 17 at @Ease, 7th Floor, 605 Third Avenue, New York. Attendance can be reserved by clicking here.
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