By Robert Q. Klamser, Chief Innovation Officer at Stretto. Stretto were Finalists in the ‘Best SaaS Product for Law and Legal Services‘  awards at the 2025 SaaS Awards.

Picture this: A senior partner at a corporate law firm spends three hours manually reviewing 200 contracts to identify indemnification clauses for a routine due diligence project. Meanwhile, across town, a solo legal practitioner dedicates an entire afternoon to researching venue requirements across five jurisdictions for a straightforward motion. Both scenarios represent precisely the type of repetitive, time-consuming work that artificial intelligence (AI) can streamline. Yet many legal professionals remain hesitant to explore these possibilities.

Their hesitation is not unreasonable. According to American Bar Association 2024 Artificial Intelligence Tech Report, the legal industry has seen relatively low AI adoption rates with just over 30 percent of attorneys reporting to use AI-enabled technology tools. The concerns driving this type of cautious approach are legitimate: client confidentiality, ethical obligations, accuracy questions, and the fundamental responsibility to maintain competent representation. However, these valid concerns have created  a common misperception that AI adoption and utilization must be an “all-or-nothing” proposition, only capable of yielding efficiencies when deployed across all functions and department.

The reality is far different. For most legal professionals and law firms, meaningful change occurs incrementally, and AI does not represent a panacea to address every aspect of legal practices and procedures. While this may seem contrary to the hype surrounding the potential impact that AI can have, it actually creates space for legal professionals to take smaller, strategic steps towards effective AI adoption, while maintaining the careful risk management that defines competent legal practice.

Key Steps to Starting or Continuing a Successful AI Journey

Legal professionals can embark on or continue their AI journey by following a structured, risk-conscious approach that builds expertise gradually while maintaining professional and ethical obligations:

Step 1: Identify Low-Risk, High-Volume Tasks. Begin with repetitive, administrative work that doesn’t involve confidential client information or require nuanced legal judgment. These tasks often consume significant time while offering limited intellectual satisfaction, making them ideal candidates for AI assistance.

Step 2: Pilot with Non-Confidential Work. Start your AI pilot projects with publicly available information, hypothetical scenarios, or anonymized examples. This approach allows you to understand AI capabilities and limitations without risking client confidentiality or creating ethical dilemmas.

Step 3: Measure and Evaluate Results. Establish clear metrics for success—time savings, accuracy improvements or cost reductions. Document what works and what doesn’t, creating an evidence base for future decisions about expanding AI use.

Step 4: Scale Gradually with Proper Safeguards. As comfort and competence grow, gradually expand AI use to more complex tasks while implementing appropriate verification workflows, client disclosures, and oversight mechanisms.

Embracing AI While Addressing Professional Concerns

Before delving deeper into practical applications, it’s essential to acknowledge and address the professional and competitive concerns that make many lawyers appropriately cautious about AI adoption.

• Privacy and Confidentiality Considerations. The duty to protect client information doesn’t disappear with new technology, it evolves. Legal professionals can maintain this obligation by starting with AI applications that don’t involve confidential information. Use AI for legal research on published cases, drafting template language for common situations, or analyzing publicly available regulatory guidance. When ready to progress to confidential work, consider local AI deployments or platforms specifically designed for legal use with appropriate data-handling protections.

• Accuracy and Reliability Standards. AI should never replace professional judgment, it should enhance it. Think of AI as generating sophisticated first drafts that require the same careful review you’d apply to work from a junior associate. Establish verification workflows where AI output undergoes human review, fact-checking, and professional evaluation. This approach maintains accuracy standards while capturing efficiency benefits.

• Ethical Obligations and Professional Responsibility. Lawyers are required to provide competent representation, which increasingly includes understanding relevant technology. Several state bars have issued guidance emphasizing that lawyers must understand the tools they use, maintain confidentiality, and disclose AI use when material to the representation. Rather than avoiding these obligations, embrace them as part of professional development in a changing landscape.

• Competitive Dynamics at Play. While incremental adoption emphasizes caution and careful implementation, it’s important to recognize the competitive dynamics at play. Clients increasingly expect their legal counsel to leverage technology for efficiency and cost-effectiveness. Law firms that thoughtfully integrate AI capabilities will be better positioned to meet client expectations while maintaining profitability. Early adopters who implement AI thoughtfully, with appropriate safeguards and quality controls, will develop competitive advantages in efficiency, cost management, and service delivery. The key is starting the learning process now, even with small steps, rather than waiting for perfect solutions or complete certainty.

How to Start Small and Build From There

Lawyers should start with small, practical applications of AI and build up in complexity while building confidence. One area to start is enhancement of legal research where the  research process can be transformed without compromising quality. Use AI to generate initial case law searches, create jurisdiction comparison charts, or summarize regulatory developments. For example, when researching employment law issues across multiple states, AI can quickly identify relevant statutes and key cases, providing a research foundation that you then verify and expand through traditional methods. This approach cuts research time while maintaining the thoroughness clients expect.

Another option is document review for patterns and compliance in due diligence projects. AI excels at pattern recognition across large document sets. You can prompt AI to identify specific contract clauses, flag regulatory compliance issues, or spot inconsistencies in corporate documentation.

AI can also be used for administrative task optimization to transform routine work that consumes valuable time. AI can draft initial time entry descriptions, suggest calendar scheduling based on email content, or create first drafts of routine correspondence. These applications don’t involve complex legal analysis but can reclaim hours weekly for substantive legal work.

Template and form generation are also ideal functions that can be optimized with AI efficiency. More advanced users can develop AI-assisted workflows for creating common legal documents. Start with straightforward templates like engagement letters, basic contracts, or routine pleadings, where AI can generate initial drafts based on your specifications. This approach maintains your professional judgment in customizing documents while eliminating repetitive drafting work.

AI in the Bankruptcy Law Sector

The bankruptcy law sector provides an excellent example of targeted AI implementation. In large-scale Chapter 11 bankruptcies, legal teams must communicate with thousands of creditors regarding key case developments and milestones. A significant portion of this effort involves fielding endless creditor inquiries through call centers and other communication channels.

Recently launched AI chatbot technology enables attorneys and stakeholders to navigate corporate bankruptcy proceedings more efficiently. These platforms process thousands of concurrent inquiries in real-time, delivering unprecedented efficiency in creditor communications while dramatically reducing operational costs.

The goal isn’t to replace all human communication with AI, but rather to improve the user experience by allowing AI to handle routine inquiries at scale while preserving human expertise for complex matters. This solution alleviates legal professionals from administrative burdens, enabling focus on substantive case proceedings. Creditors maintain communication options—phone, email, text, or chat—but receive faster, more consistent responses to standard questions while retaining access to human expertise when needed.

The path to effective AI adoption in legal practice doesn’t require revolutionary change or comprehensive transformation. Instead, it demands the same careful, methodical approach that characterizes good legal practice: identifying specific problems, implementing targeted solutions, measuring results, and building upon successes.

By starting with low-risk applications, maintaining rigorous quality controls, and expanding gradually based on demonstrated results, legal professionals can capture AI’s efficiency benefits while upholding their professional obligations. The goal isn’t to replace legal expertise with artificial intelligence, it’s to free legal professionals from routine tasks so they can focus on the complex analysis, strategic thinking, and client counseling that truly require human judgment.

The question isn’t whether AI will transform legal practice, it’s whether you’ll be prepared to participate in that transformation thoughtfully and competently. Starting small isn’t just safer; it’s smarter. Take the first step, measure the results, and build from there. Your clients, your colleagues, and your competitive position will benefit from your willingness to begin this journey, one careful increment at a time.