The integration of AI into legal practice has reached a critical inflection point, and the risks of choosing the wrong solution extend far beyond simple inefficiency.

For legal professionals, the stakes are uniquely high: accuracy concerns, ethical implications, and professional standards hang in the balance with every AI-assisted task.

At the heart of these challenges lies a critical distinction many firms are only beginning to understand: the fundamental difference between consumer-grade AI and professional-grade AI.

As the gap between “using AI” and “using AI effectively” continues to widen, legal professionals who recognize and act on these differences will be positioned to deliver better outcomes, maintain competitive advantage, and uphold the professional standards their clients depend on.

Here, we’re sharing some key distinctions, based on a recent webinar sponsored by our friends at Thomson Reuters. (View the full recording here. Registration is required, and CLE credit is available.)

Trust Starts at the Source

There are many practical use cases for consumer-grade generative AI, from streamlining daily communication tasks to enabling creative experimentation, and these tools have brought AI capabilities to millions of users.

“Consumer AI does produce confident sounding results,” says Thomson Reuters’ Maddie Pipitone. “And that can be great for creative purposes, but not for professional purposes.”

For professionals who need to make confident, defensible decisions, the source of AI-generated information becomes critical.

Drawing from the general internet, consumer AI tools introduce uncertainty and may hallucinate data or fabricate cases, requiring extensive validation. ChatGPT, for example, has often cited community-edited publications like Reddit and Wikipedia as information sources, Pipitone notes, referring to recent studies.

Certain legal-specific tools, by contrast, will draw on their own curated body of information, she says, increasing the reliability of their large language models.

“When you have a tool like CoCounsel Legal from Thomson Reuters, it’s grounded in Westlaw and Practical Law, which ensures that additional level of accuracy and recency,” she says. “The data is up to date and not a blog post.”

CoCounsel will cite to every source, allowing you to validate all of its statements instantaneously.

AI is Here to Stay

In Thomson Reuters’ 2025 Generative AI for Professional Services Report, 42% of legal professionals anticipate that GenAI will be central to their workflow in the next year, and 95% say within the next five years.

On if AI will make an impact on workflows, Pipitone says: “It’s not really a question of if, at this point, it’s of how we do that responsibly and how we incorporate the right workflows into our practice to make sure we’re still fulfilling those ethical obligations and doing right by our clients.”

Doing so can be done by examining the capabilities of a Large Language Model. The timeline skill in CoCounsel, for example, allows you to create a chronology of events described in documents. What would usually take a substantial amount of time to complete manually can now be done in minutes, adding value to you and your clients’ time and making processes more efficient.

Privacy and Privileges

Using AI also creates complexities around data privacy and attorney-client privilege, and key differences emerge between consumer and professional products in this space.

Some consumer tools can store your data and use it for model training, Pipitone notes, and you have to affirmatively opt out to avoid this.

Uploading confidential client info into this type of system could violate confidentiality obligations, and even waive attorney-client privilege.

Legal-specific tools, by contrast, “are specifically built for that confidentiality and security purpose.”

These concerns about data privacy and privilege are essential considerations for any legal professional evaluating AI tools.

When firms select AI solutions designed specifically for legal practice with robust security measures, zero-retention policies, and built-in privilege protections, the path forward becomes clearer. The key is approaching adoption thoughtfully rather than avoiding it entirely.

“Building that trust both with yourself and with others in your firm is key to adoption,” Pipitone urges, “So starting small, verifying that output and then building from there to see where the AI fits naturally into your workday.”

View the Webinar

For more on practical ways to implement AI and communicating AI use to clients, see the full conversation here. (Registration is required, and CLE credit is available.)

The post 3 Ways Professional-Grade AI Differs From Consumer Solutions appeared first on Above the Law.