The rise of agentic AI in financial services promises significant efficiency gains and competitive advantages, but its success hinges on robust data infrastructure.
By Epoch AI Consulting · 14 May 2026
The rise of agentic AI in financial services promises significant efficiency gains and competitive advantages, but its success hinges on robust data infrastructure. Companies must prioritize building an authoritative, accessible, and governable data store to fully realize the potential of autonomous AI systems, or risk undermining trust and regulatory compliance.
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The financial services sector is on the cusp of a technological revolution, driven by agentic AI. These systems, capable of independently planning and executing tasks, hold the promise of streamlining complex workflows, enhancing customer experiences, and improving risk management. However, beneath the surface of sophisticated algorithms lies a critical dependency: data. According to a recent MIT Technology Review Insights report, in partnership with Elastic, the effectiveness of agentic AI is less about the algorithms themselves and more about the quality, security, and accessibility of the underlying data. Financial institutions must therefore approach AI implementation with a laser focus on data readiness, ensuring their systems are built on a solid foundation of reliable information.
The report highlights several key factors driving the need for data readiness in agentic AI within the financial services sector:
Agentic AI amplifies both the strengths and weaknesses of the data it uses. Therefore, organisations must build a trusted and centralized data store. This includes consolidating data across different locations to avoid inconsistent answers, and produce decisions that are harder to trace and explain.
Financial services operate under intense regulatory scrutiny, demanding a high degree of accountability for all data tools. It’s no longer sufficient to simply track data lineage. Organisations must be able to explain the logic behind AI-driven decisions, demonstrating why specific data points were deemed relevant and how they contributed to the final outcome. This requires an auditable and governable framework that provides transparency into the underlying processes.
While structured data in spreadsheets is relatively straightforward to analyse, the real value lies in unlocking insights from unstructured data sources like natural language in customer interactions, policy documents, and risk assessments. This requires advanced natural language processing (NLP) capabilities and robust data cleaning processes to ensure accuracy and consistency.
Many financial institutions struggle with fragmented data, locked in separate systems across the organisation. These data silos hinder the ability of AI agents to access and process information efficiently, leading to delays, inconsistencies, and ultimately, a lack of confidence in AI-driven decisions. As Steve Mayzak, global managing director of Search AI at Elastic, points out, "There are many different ways to describe how to execute a trade at a bank. In an agent-powered world, we need those descriptions to be deterministic—to give the same results every time. Yet we’re building on powerful but non-deterministic models. That’s incredibly tricky, but not impossible.”
An effective search platform is essential for navigating the complex landscape of fragmented and poorly indexed data. By enabling financial services companies to readily sift through both structured and unstructured data, maintain security, and apply it in the right context, they can unlock the true potential of AI.
The implications of data readiness for agentic AI are far-reaching for financial services companies. Those that prioritize data quality, accessibility, and governance will be better positioned to:
Conversely, organisations that neglect data readiness risk undermining trust in AI systems, facing regulatory scrutiny, and falling behind their competitors. The path towards AI transformation requires more than just implementing cutting-edge models; it demands a strategic investment in data infrastructure and governance.
At Epoch AI Consulting, we understand the critical role of data in unlocking the full potential of AI, especially in highly regulated industries like financial services. Our approach to AI implementation begins with a thorough assessment of your existing data landscape, identifying gaps and opportunities for improvement. We believe that a successful AI adoption strategy starts with a clear understanding of your data assets and how they can be leveraged to achieve your business goals.
Our AI strategy services focus on helping companies develop a comprehensive AI roadmap that addresses data readiness as a core component. This includes defining data governance policies, implementing data quality controls, and building scalable data infrastructure. We work with organisations to develop a clear vision for how AI can be used to solve costly problems or create revenue opportunities, ensuring that data is at the heart of the solution.
We recognise that many organisations lack the internal capabilities to fully leverage agentic AI, with a Forrester study finding that 57% of financial organisations are still developing the necessary internal capabilities. That’s why we also offer AI training and AI workshops to upskill your teams on the latest AI tools and practices. Our AI training for employees ensures your staff are equipped to work alongside AI systems, understand their outputs, and maintain data quality. We also provide corporate AI training, tailored to different roles and skill levels within your organisation.
Epoch AI Consulting also provides bespoke AI and data delivery services. We can design and build custom SaaS solutions that meet your specific needs, automate data processing pipelines, and embed AI talent within your organisation to drive innovation. Whether you need an AI consultancy for businesses UK to guide your AI strategy, or a skilled AI consultant UK to execute your vision, Epoch AI Consulting is here to help.
For SMEs looking to understand how to implement AI in business, our AI consulting for SMEs provides tailored advice and support. We help you navigate the complexities of AI adoption and identify the most impactful use cases for your organisation. If you're looking to hire an AI consultant or find the best AI consultancy UK, consider Epoch AI Consulting for our expertise and commitment to delivering tangible results.
The future of financial services is undoubtedly intertwined with agentic AI. However, the success of this technology hinges on a foundational element: data. Organisations that prioritize data readiness, invest in robust data infrastructure, and cultivate a data-driven culture will be best positioned to reap the rewards of autonomous AI systems. By addressing the challenges of data quality, accessibility, and governance head-on, financial institutions can unlock the true potential of agentic AI and pave the way for a more efficient, innovative, and customer-centric future. As AI continues to evolve, focusing on data will be the key differentiator between those who thrive and those who are left behind.