AI in law firms: the paradox

Summary

TLDR
  • According to LexisNexis, out of over 400 lawyers, 56% foresee more AI, but only 17% judge the implementation of new technologies in their firm to be sufficiently fast.
  • Many firms invest in sophisticated AI but neglect laptops, peripherals, and networks, accumulating technical debt, slowdowns, errors, and underutilized expensive tools.
  • Devices that are out of support do not receive security patches and encourage risky behaviors, such as disabling antivirus software, exposing confidential and privileged client data.
  • According to GDPR and ENISA frameworks, protection measures must be proportionate to the risk, and outdated infrastructure makes it more difficult to comply with them.
  • Solutions start with infrastructure audits, endpoint renewal, balanced budgets, integrated governance, training, and KPIs such as hours lost due to technical issues.
Index

The problem of misalignment between AI in law firms and hardware

The technological mismatch becomes apparent when the adoption of AI in law firms proceeds at a rapid pace, but operating conditions remain inadequate to fully exploit its infinite potential.

According to research by LexisNexis Conducted on more than 400 lawyers in private practice, 56% of respondents expect the use of artificial intelligence to increase, but only 17% believe their firm is implementing new technologies quickly enough. This gap results in a real “digital gap,” where technical innovation races ahead, but everyday reality fails to keep up.

The first node concerns the setting of priorities. Indeed, many law firms focus their investments on sophisticated AI tools (predictive analytics, Document automation , intelligent search systems) while neglecting the stability and performance of individual work platforms. It so happens that an associate has an AI-based contract review engine but is forced to use it on a laptop with slow hard drives, insufficient memory and faulty peripherals.

A second critical element concerns the governance of endpoint devices. Adoption of AI in law firms cannot go without an updated hardware ecosystem that is consistent with security, performance and technical support standards. Otherwise, the promise of automation remains unfulfilled and the perceived value of innovation diminishes.

The result of all this is a continuous accumulation of “technological debt.” expensive and underused tools, wasted time, errors, slowdowns, and widespread dissatisfaction among professionals. If every day a lawyer is forced to contend with a mouse that crashes or software that takes minutes to open, even the most advanced artificial intelligence software loses much of its impact.

The operational and strategic implications for law firms

When AI in law firms is formally adopted but lacks an adequate technological base, the consequences are immediately and tangibly apparent.
Some associates of large U.S. firms interviewed by ALM (a U.S. publishing company specializing in legal and professional information) have described their devices as “borderline unusable” ( Cahill Gordon & Reindel LLP ) or even “barely functioning” ( Desher & Partners ). These accounts, though anecdotal, are not exceptions, but signs of a broader and more worrisome trend: respondents' frustration does not in fact stem from a lack of advanced software, but rather from the inability to take full advantage of it due to outdated and unstable devices.

At the operational level, the result is increased work time, avoidable errors, and interruptions that add up to undermine the firm's overall productivity . At the strategic level, the impact is even more profound: A firm that invests in AI but neglects the soundness of its infrastructure runs the risk of not achieving measurable returns, undermining internal trust, and compromising reputation with clients. In an increasingly competitive legal market, where technology is also a branding lever and credibility , this imbalance represents a real risk that can no longer be ignored.

Security and cybersecurity risks generated by misalignment

The gap between advanced AI platforms and outdated endpoint devices is not only about productivity, but also exposes law firms of any size to serious computer vulnerabilities .

Laptops out of support and out-of-date software don't receive security patches , thus opening windows of exposure that cybercriminals can exploit as vectors of access. In parallel, the instability of devices often leads to risky behavior on the part of the employees themselves, as the temporary deactivation of antivirus to “speed up” operations, use of accounts with excessive privileges, or saving sensitive files to unprotected drives.

According to reports from Verizon and NIST ,exploits of known vulnerabilities and the use of compromised credentials remain among the leading causes of cyber incidents. For law firms, the impact of these attacks is even greater: attackers Indeed, they target confidential data, trial strategies, and insider information. A single violation in this regard can result in economic, legal and reputational damage from which it may be difficult to recover.

Added to this is the issue of compliance. The European and international regulations - since GDPR at framework ENISA - require that technical measures to protect data and IT infrastructure be proportionate to the risk. An outdated infrastructure makes it more difficult to meet these requirements, increasing the cost of operational and insurance risk.
Integrating patch management, device inventory, and endpoint security into the roadmap of AI adoption in law firms are not just best practices, but real governance necessities.

Possible solutions: realigning hardware with the future of AI

To truly enhance the potential of AI in law firms, the “invisible” technology-that is, the hardware and day-to-day infrastructure-must be robust, up-to-date and consistent . The following are some concrete actions that can help bridge the gap that exists to date both in the SME Than in large multinational corporations:

  • Infrastructure audit: analyze the device fleet, measure response time, failure rate, and compatibility with AI tools.
  • Investment in endpoint devices: Ensure laptops and workstations with adequate performance, regular updates, and efficient peripherals.
  • Budget balance: allocate part of the resources dedicated to AI also to hardware renewal and systemic maintenance.
  • Integrated governance: create a committee to coordinate innovation and operations, preventing AI from proceeding independently of the infrastructure.
  • continuing education :Promote a culture of good device use, constant updates, and proactive IT support.
  • Monitoring and KPIs: measure indicators such as average time to failure, percentage of obsolete devices, and hours lost due to technical problems.
  • Security and resilience: ensure that hardware is compatible with the security standards required by AI platforms, including strong authentication, regular patching, and automated backups .

Only through these measures can investment in AI in law firms translate into concrete efficiency, value for clients, and long-term sustainability.

Beyond the hype: building a solid foundation for AI in law firms

AI in law firms represents one of the profession's greatest transformations, but it risks remaining a cosmetic innovation if it does not rest on a solid foundation. Ignoring the hardware, laptops, peripherals and network infrastructure is tantamount to building a skyscraper on an unstable foundation.

Firms that want to maintain their leadership and their clients must evaluate with equal care both the power of their AI solutions and the quality of the operating environment that supports them.

In this scenario, Lanpartners can act as a strategic partner to assess, update, and manage the digital ecosystem of law firms in an integrated way, ensuring that AI does not remain just a label to be boastfully displayed, but becomes an operational reality that is useful for daily work.

Going beyond hype means combining vision and concreteness, innovation and technological stability. Only then will law firms be able to grasp the full potential of AI without stumbling over their own foundations.

Frequently asked questions

Why is artificial intelligence not performing as expected in many law firms?

AI performs less than expected when running on inadequate hardware. Many firms invest in advanced tools like contract review and intelligent research, but leave associates with slow laptops, low memory, and faulty peripherals. The result is technical debt: expensive and underutilized software, wasted time, errors, and dissatisfaction among professionals.

What does LexisNexis research say about AI adoption in law firms?

The LexisNexis research, conducted on over 400 lawyers in private practice, shows that 56% expect an increase in the use of AI, but only 17% believe their firm adopts new technologies quickly enough. This gap creates a digital divide between available innovation and daily operational reality.

What cybersecurity risks do obsolete laptops pose in a law firm?

Unsupported laptops and outdated software do not receive security patches and become gateways for cybercriminals. Instability also encourages disabling antivirus, using accounts with excessive privileges, or saving files on unprotected drives. For a law firm, the damage can be economic, legal, and reputational, because confidential data and litigation strategies are exposed.

Can outdated IT infrastructure create GDPR compliance issues?

Yes, outdated infrastructure makes it more difficult to comply with GDPR and the ENISA framework, which require technical data protection measures proportionate to the risk. It also increases the cost of operational and insurance risk. For this reason, patch management, device inventory, and endpoint security must be included in the AI adoption roadmap.

What concrete actions can a law firm take to realign hardware and artificial intelligence?

The study should begin with an audit of the device fleet, measuring response times, failure rates, and compatibility with AI tools. Then, it is necessary to renew laptops and workstations, allocate part of the AI budget to hardware, create integrated governance, train staff, and use KPIs such as mean time between failures and hours lost.

What indicators should be used to measure if a law firm's IT infrastructure is adequate for AI?

Useful indicators are the mean time between failures, the percentage of obsolete devices, and hours lost due to technical issues. These should be complemented by device response times and compatibility with AI tools, detected through an infrastructure audit. These data show whether the investment in AI produces a measurable return.