When AI Accuracy Becomes Non-Negotiable

In high-stakes industries, making informed, accurate decisions is essential to success. Health care clinicians look to medical evidence to shape lifesaving diagnostic decisions. Attorneys use legal precedents and precise citations to support their claims in court. And finance professionals rely on up-to-the-minute data to manage risk and lending with confidence.

For professionals in these and other demanding sectors — including tax and accounting firms, and corporate performance and ESG leaders — there is no room for error or uncertainty.

General-purpose artificial intelligence is increasingly being adapted for specialized professional use. But these AI tools face significant hurdles in establishing the trust and guardrails required for adoption.

Lisa Nelson is well-versed in the specific needs of these high-stakes professions, having served these industries her entire career. Nelson is the CEO of Financial & Corporate Compliance at Wolters Kluwer, a global leader in information solutions, software and services for professionals.

Nelson says the implementation of any new technology must be approached cautiously and with precision. 

“AI should not lower existing professional standards,” says Nelson. “It requires controls tailored to model risk. High-stakes professions need to ensure that their technology partners understand their industry and have the trusted content, domain expertise and safeguards these environments require.”

When AI gets it wrong, more than reputation is at risk

For high-stakes industries, even a single error can create not only reputational risk, but real human consequences. In finance, for instance, an April 2026 Wolters Kluwer survey of 230 risk, compliance and AI leaders in the banking sector found that more than 35% see the collections and debt recovery process as the function most vulnerable to AI risk.

“What if there was an issue of mistaken identity, or the technology flagged something inaccurate?” says Nelson. “This could trigger wrongful collection activity, inaccurate credit reporting or improper escalation toward repossession or foreclosure. These are major, life-altering events where, if AI isn’t thoughtfully introduced, then an organization is doing a disservice to its customers and stakeholders.”

Martin O’Malley, CEO of Wolters Kluwer Legal & Regulatory, says that legal professionals also cannot risk inaccuracies in their AI. Legal practice is governed by statutes, regulations and case law — which means that the accuracy of an AI system’s underlying data is crucial.

“Large language models [LLMs] that have been trained on broad internet content are guided towards legal accuracy via prompt engineering or additional fine-tuning, but there’s always the risk that information sourced from the web is outdated or inaccurate,” says O’Malley. 

AI models also create new risks around data privacy, security and governance.

Nelson says she has seen instances where employees using non-enterprise-grade AI tools entered sensitive client information, such as loan data or health records. Once shared, that information enters an unregulated environment, leaving companies with limited control over how their data is accessed or used.

“When that happens, that data can then even be used to train models. You cannot risk that type of reputational damage or even regulatory spotlight because of AI use,” says Nelson. 

AI needs to be built on trust and transparency from the start

The strict standards of these sectors demand a different approach to AI.

Nelson says AI can add value to these industries only when accuracy, explainability, trusted content and expert oversight are built into the solution from the outset. It’s essential that these systems meet the same standards that have long governed these industries, making certified solutions with contractual protections, business controls and clear data-use agreements a safer choice.

Organizations should ensure that their solution has been trained on the best possible data that would have been relied on prior to the advent of AI, Nelson says. Other necessary pillars include strong privacy and security protections, transparency into how AI systems operate and clear standards for governance, accountability and fairness.

Together, these principles help preserve human judgment, make AI outputs more understandable and establish the trust required for AI to support critical decisions.

“The true value of AI is ultimately measured by trust and accuracy,” says O’Malley.  

For legal professionals specifically, he says that they need tools that go beyond simple research to draft, review and analyze documents with speed and precision. 

“When grounded in authoritative content, AI becomes a powerful partner that helps legal professionals navigate that growing complexity with confidence,” says O’Malley.

Putting principles for trusted AI into practice

Wolters Kluwer’s Expert AI approach combines advanced AI with proprietary, expert-curated content, domain expertise and responsible governance for high-stakes professional workflows. For Wolters Kluwer, trust is not an afterthought. It is a design requirement, informed by its experts, technology partners and customers.

“Wolters Kluwer’s Expert AI is augmenting expert-curated information and domain workflows with generative and agentic capabilities built for professional use,” says Nelson.  “What is important is not so much the power of the underlying model, but how the whole system is grounded, managed and incorporated into the user’s job.” 

With a history dating back nearly two centuries, Wolters Kluwer has built deep domain expertise and specialized knowledge across the professions it serves. Today, this foundation of trusted content powers Wolters Kluwer’s Expert AI, combining trusted, expert-curated content with advanced AI technologies.

To ensure accurate outputs, Wolters Kluwer incorporates multiple safeguards into its Expert AI solutions. These technologies incorporate “model grounding,” which ensures that responses are based on trusted, verified sources rather than unsupported, model-generated content. This means users can see not only the answer to a query, but also the evidence, assumptions and reasoning behind it. This approach also helps prevent AI hallucinations.

Another key guardrail is the company’s expert-in-the-loop approach: Proprietary content is developed and curated by subject matter experts, while domain specialists continuously review and validate AI performance to help ensure accuracy, relevance and compliance.

For example, within the health care field, Wolters Kluwer’s UpToDate Expert AI platform is grounded in trusted clinical content authored and reviewed by more than 7,600 practicing clinicians and supported by an extensive editorial and medical review process.

“Our experts understand how factors such as source hierarchy and precedential value can impact the accuracy of an AI output,” says O’Malley. “They create intricate taxonomies, practice-area classifications and editorial enhancements to help AI systems understand relationships between authorities that aren’t apparent from text analysis alone.”

A trusted system directly embedded into professional workflows

AI grounded in authoritative information, supported by strong governance and built with rigorous safeguards, can be a reliable part of critical professional workflows.

Libra by Wolters Kluwer, a legal workspace platform, provides a secure environment where authoritative legal content is activated directly in the flow of work to create practical, action-oriented content such as briefs, templates, checklists, playbooks and guidance without having to switch between applications. In the financial and corporate compliance sector, the newly launched NILS™ AI Assist expedites insurance professionals’ research needs. And UpToDate delivers evidence-based recommendations to health care clinicians at the point of care, helping them better assess complex cases.

By combining trusted content, domain expertise and responsible AI within professional workflows, Wolters Kluwer is working to make AI useful in the moments where accuracy, transparency and judgment matter most.

“AI will be a powerful ally in helping professionals navigate stakeholder expectations and competitive pressures. Our mission is to help our clients make this transition with confidence,” says O’Malley.