The greatest AI opportunity is in trusted information
Generative AI has transformed documents, emails, chats, reports and knowledge assets into a new class of enterprise capital. Organizations that can identify and govern trusted information will generate better insights, more effective AI agents, faster decisions, and greater returns from AI investments.
Key takeaways
- Generative AI is transforming documents, emails, chats, and other unstructured content into strategic business context that requires an authoritative source of truth.
- The next AI race is about access to trusted information that multiplies AI value.
- Deloitte helps organizations establish trusted information foundations that support regulatory compliance, GenAI insights, and enterprise-scale AI solutions.
Unstructured information is becoming the fuel that powers AI reasoning.
Documents, emails, chats, reports, and other content are no longer passive records. They have become active inputs into AI-generated insights, recommendations, and decisions. But as organizations race to scale AI, many are discovering a new challenge: AI is only as trustworthy as the information it relies on.
Organizations need a defensible foundation of trust to scale AI performance.
Why AI struggles with unstructured information
Today, 70 to 90% of all enterprise information exists in unstructured formats such as documents, chats, emails, and PDFs.1 Much of that information sits unused, poorly governed, duplicated, or stored without the context needed to determine whether it is current, accurate, authoritative, or appropriate for AI to use.
As the volume grows, so do the costs. More unstructured data can mean more cloud storage, legacy technical debt, duplicated repositories, and higher token costs when GenAI tools process more information than they need.
Most importantly, AI systems must be using information that can be trusted. “The AI got it wrong” is unlikely to satisfy regulators, boards, customers, or employees.
In short: the greatest AI opportunity is in trusted information.
A foundation of truth for what comes next
An unstructured data strategy is about creating a reliable foundation of truth that can be governed, validated, and used with confidence. That foundation helps organizations reduce cost and risk today while preparing for more reliable AI tomorrow.
This work typically requires two stages: building trust, which involves cleanup and validation, followed by scaling with AI.
1. Build trust
The winners of the AI era will have the best information foundations—organizations must prove the trustworthiness of the information behind AI decisions. Organizations that establish clear ownership, authoritative sources, and information classification enable AI systems to retrieve better information, provide more consistent answers, and deliver more reliable business outcomes.
Classification is also critical. Applying metadata and auto-classification can make information easier to search, understand, and reuse by both people and AI solutions. It can also help determine whether information is authoritative, current, sensitive, duplicated, or eligible for disposal.
When content is cleaned up, validated, and governed, organizations can reduce unnecessary tokenization, lower storage needs, improve findability, and create a stronger foundation for future AI use.
2. Scale with AI
With a trusted foundation, AI can help extend and sustain the work. AI-ready data foundations reduce hallucination risk, strengthen governance, and improve confidence in reporting and decision-making.
To scale with AI, organizations must:
- Strengthen protection by aligning practices with regulations, policies, and access controls, ensuring only those that should have access can find it, even with Generative and Agentic AI solutions.
- Establish information governance, decommission legacy technology, and establish clear accountability to enable a single source of truth for AI usage and insights.
AI changes the burden of proof
Information trust is becoming a new source of competitive advantage. Organizations have access to the same frontier models but not to the quality, trustworthiness, and accessibility of the information underpinning those models.
Historically, organizations needed to defend the final regulatory filing and the controls surrounding its preparation. With GenAI and agentic AI, regulators are increasingly focused on something different:
Can you prove that the information used to generate the answer was trustworthy?
As AI becomes embedded in regulatory reporting, compliance monitoring, risk management, and decision-making processes, organizations will be expected to demonstrate where AI-generated outputs came from, what information sources were used, and whether those sources were authoritative, accurate, and appropriate for their intended purpose.
AI can now:
- Draft portions of regulatory submissions
- Summarize obligations, risks, and control environments
- Consolidate information from thousands of documents and records
- Generate analysis that becomes part of a regulatory artifact
Questions regulators will ask
Leaders should be prepared to answer a new set of questions about the foundations of their AI-driven decisions.
How Deloitte can help
In the AI era, competitive advantage will not come from access to better models. It will come from access to better information.
Deloitte helps organizations transform fragmented information into trusted information foundations that power AI reasoning, improve explainability, and accelerate enterprise AI outcomes.
The result:
- Better answers
- Faster decisions
- More effective AI agents
- Lower operating costs
- Greater regulatory confidence
The organizations achieving the greatest AI returns aren't feeding AI more information—they're feeding AI better information.
