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In-house legal teams have pioneered generative artificial intelligence (AI) adoption.

Our report, Lawyers cross into the new era of generative AI, demonstrates in-house teams are often time-poor, deal with low-value but high-volume tasks, and typically work in organisations with a greater appetite for risk. Simply, in-house teams are better prepared for AI adoption. 

But, despite this, in-house teams face several risks and challenges around generative AI which has translated into caution, particularly around the external use of generative AI. We've also seen challenges around billing, with in-house teams and firms at odds with pricing expectations.

This article will explore the core risks associated with free-to-use generative AI platforms, discuss how teams can overcome such risks, and look at how to approach pricing challenges.

In-house teams and the associated risks of AI

In our July 2023 survey, 70% of in-house teams expected external counsel to use generative AI. That number sharply declined to just 57% in January 2024. Mark Smith, Director of Strategic Markets at UUÂãÁÄÖ±²¥, says risks around accuracy, quality, and security justify declining expectations: "I suspect the number one reason is accuracy and fear of having the wrong advice, particularly heightened by issues with free-to-use generative AI."

Respondents cited the following as the most pressing risks of adopting generative AI: hallucinations (57%), security issues (55%), and the tech not being trustworthy enough (55%). Only 10% cited no concerns about generative AI. Free-to-use generative AI platforms create accuracy risk. Accuracy issues occur due to platforms trained on poor data sets, which create incorrect or misleading information to fill in knowledge gaps or reveal false information based on false inputs.

Accuracy is a huge area of concern and one where in-house teams can't afford to get wrong. In-house lawyers are hired for their specialist knowledge and legal expertise. That knowledge informs legal issues but increasingly defines strategic objectives, influences commercial outcomes, and even delves into ethical decisions. If in-house leaders rely on misleading or incorrect information, the outcomes could prove disastrous for their organisations.

Security is another core concern. Free-to-use generative AI tools make in-house teams vulnerable to potential data breaches. Bunmi Tandoh, In-house Solicitor for the London Borough of Enfield, describes data breaches as a 'major risk'. The risk stems from poorly managed data sets, trained on sensitive or personal information, producing outputs that contain or imply private data.

Confidentiality is important for in-house lawyers, too. Again, the main risk stems from free-to-use models. May Winfield from succinctly summarises the issue: "Inputting confidential data onto a free-to-use generative AI platform is like throwing it into a public forum; you can't delete it or remove it and someone asking the right question could, potentially, extract that data." 

In-house lawyers, as we've argued elsewhere, should avoid free-to-use generative AI models. Such platforms are often opaque, trained on insufficient or problematic inputs, and lack human oversight, leading to accuracy, security, and confidentiality issues. 

AI-powered tools grounded on legal research and guidance content, such as Lexis+ AI, allow in-house lawyers to avoid risks. Respondents to the UUÂãÁÄÖ±²¥ survey echoed support for more trusted models, with almost two-thirds suggesting confidence in using more trusted models.

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The impact of AI on pricing models

As shown above, in-house teams are increasingly aware of the risks and benefits of generative AI. But one administrative challenge looms on the horizon: pricing. There exists a conflict in-house teams and external law firms, as questions remain over the beneficiaries of AI's time- and cost-saving.

Our report found that more than half (52%) of in-house teams expect bills to reduce as a result of generative AI. But only two-fifths of lawyers said bills should be reduced. In addition, 62% of in-house teams said they expect firms to change billing practices as a result of generative AI, but only 18% of law firms believe they'll make any substantial changes to billing practices.

There are contrasting opinions over the impact of AI on pricing. In-house teams imagine wholesale change, but law firms see business as usual. According to John Quinn, Founder and Chairman of , AI will change the economic underpinnings of law firms. "There will be less need for associates at firms," Quinn says. "What we're going to need is lawyers who are more capable with generative AI and better at engineering and designing prompts for AI programmes."

Chris Tart-Roberts, Head of Lawtech at , echoes Quinn's analysis: "AI is certainly not about replacing lawyers, but we're going to see it turbo-charging their expertise." The inescapable fact, according to many contributors from the report, is that generative AI will change the nature of legal work and pricing will have to pass at least some time- and cost-savings to in-house teams. 

Generative AI is irrevocably changing the legal sector. Many are unsure how it will impact their firms, their teams, or their roles. Pricing and billing will change, but questions remain on the precise nature of that change. The next few months will prove crucial. At present, pricing is largely ignored in the conversation, at least in material terms. But changes will arrive and in-house teams will need to be alert, making the most of the tech and forging new economic relationships and based on the tech.

Download our report, Lawyers cross into the new era of generative AI, and explore our insights today!