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In-house legal teams are constantly striving to adapt and innovate in order to meet the evolving needs of their organizations. And while AI offers the potential to revolutionize legal operations by automating routine tasks, many legal professionals are often skeptical about embracing it, and for good reason! 


According to the ABA’s 2020 Legal Technology Survey Report, a substantial 51% of lawyers identify accuracy as the main roadblock hindering the adoption of AI in their firms. 

“I find cases that I regard as dispositive, authoritative, key cases on a particular topic often won’t come up with AI and instead the algorithm will find you some absolutely random nonsense.”

~ Alexander Paykin, Legal Technology Resource Center board member

Law firms are slow to adopt AI-based technology tools, ABA survey finds

However, if the technology is used correctly, generative AI could automate work activities that absorb 60 to 70 percent of employees’ time today. So, let’s identify and overcome the roadblocks that hinder AI’s seamless integration into legal workflows.

Top roadblocks to AI adoption for in-house legal teams

Top roadblocks to AI adoption for in-house legal teams

Roadblock #1: Lack of awareness and understanding

“While tools such as ChatGPT have shot to prominence in the past year, the use of it and other generative AI tools in the world of business to-date has been more cautious. Most businesses acknowledge the technology’s potential, but few have managed to really embrace its everyday use in operations. That is changing, though, as people explore the technology and better understand how it might be used in the business context.”

~ Clare Francis, Partner, Commercial Law, Pinsent Masons

In-house legal teams must get fit now for generative AI age

When it comes to your legal team, one major challenge is a lack of awareness and understanding surrounding generative AI technology.

First up, there’s the issue of limited knowledge about generative AI.  Without a solid understanding, you might miss out on all the amazing things it can do, like streamlining contracting processes, boosting efficiency, and enhancing decision-making.

Then there are the misconceptions and skepticism surrounding AI capabilities. You might have these ideas that AI is going to replace humans and that it can't really grasp complex legal reasoning. But AI has come a long way, and it's more capable than ever before. You need to address these misconceptions and unleash the true potential of AI in the legal field.

All in all, there's a clear need for education and training on generative AI within your legal team. You can’t expect to magically understand this technology without proper support. By seeking out comprehensive learning opportunities, you can equip yourself with the knowledge and skills needed to navigate the world of generative AI.

Roadblock #2: Data privacy and security concerns

As a legal team, the concern for data privacy and security is most burdensome. The sensitive and confidential information within your legal data requires the highest level of protection, irrespective of the costs involved. But as technology advances, so do the risks. Cybercriminals are always on the lookout for vulnerabilities they can exploit to gain unauthorized access to your valuable data. 

A data breach would be nothing short of a disaster. It could compromise sensitive client information, violate attorney-client privilege, and shatter the trust your clients have in you. That's why it's crucial for you to be proactive and take steps to address these risks head-on in order to protect your data.

So, what can you do to tackle these concerns head-on? You need to implement robust strategies for data privacy and security. 

This includes using strong data encryption methods to protect your data, adopting multi-factor authentication to ensure only authorized individuals can access it, regularly updating and patching your software systems to fix any vulnerabilities, and conducting thorough risk assessments to identify potential weak points. 

SpotDraft's AI-powered contract management platform prioritizes data privacy and security, providing a secure environment for storing and managing your legal documents. By using SpotDraft, you can centralize and securely store your contracts, reducing the risk of unauthorized access or data breaches.

Roadblock #3: Ethical and professional responsibility considerations

The role of AI in decision-making processes raises questions about the appropriate extent to which AI should be involved in legal decision-making and the potential implications it may have on fairness, transparency, and accountability. 

Striking a balance between leveraging the benefits of AI and preserving human judgment and oversight becomes crucial to address these concerns effectively.

Moreover, while AI can assist legal professionals in analyzing vast amounts of data and generating insights, there is a need to ensure that professionals retain the ability to exercise their expertise and ethical judgment. 

“Most organizations are realizing that they should have a policy in place for AI adoption, because, otherwise, there's a risk of customer data or confidential data being put into the public tooling.”

~ Ken Priore’s, ex-Director of Privacy, Atlassian
Mastering the Intersection of Law, Technology, and Privacy

To overcome this roadblock, establish ethical guidelines and frameworks for AI adoption in your department. These guidelines should address key aspects such as responsible AI usage, fairness, bias mitigation, data privacy and security, transparency in AI decision-making processes, and preserving professional accountability.

Roadblock #4: Cost and resource constraints

It's no secret that adopting new technology requires a significant investment, and this initial financial burden can pose a challenge, especially if you're a smaller organization or have limited resources.

When I talk about costs, I’m not just referring to the upfront investment. You also need to consider implementation costs, such as purchasing new hardware, acquiring software licenses, upgrading infrastructure, and providing training for your staff. All of these expenses can quickly add up and strain your budget.

You'll need to allocate resources for ongoing training and development to keep your staff proficient in using the new system. Neglecting these long-term requirements can result in inefficiencies, security vulnerabilities, and unexpected costs down the line.

To overcome these cost and resource constraints, carefully weigh the benefits of implementing new technology against the financial implications and resource availability. 

SpotDraft AI is an advanced contract lifecycle management platform that offers a seamless and automated solution for optimizing legal processes. By automating tasks like contract drafting, negotiation, and management, it significantly improves the efficiency of your legal operations while reducing the expenses typically associated with conventional contract management processes.

Also read: The Basics of Contract Management Software

Roadblock #5: Integration challenges with existing systems and workflows

When you bring in a new system, compatibility issues can pop up, requiring some extra development or customization to make everything work seamlessly. You probably already have well-established processes and databases in place, so introducing something new can be quite a headache.

Achieving a seamless integration of generative AI tools in your legal team demands careful planning. Key integration challenges to anticipate include:

  • Compatibility issues: Generative AI tools may have specific software requirements or data format preferences that differ from your existing systems. This misalignment can create compatibility issues, hindering the effective integration of generative AI into your current infrastructure
  • Data synchronization: Effectively integrating generative AI tools necessitates the synchronization of data across multiple systems. Ensuring that data remains consistent and up-to-date between the generative AI tool and your existing databases or case management systems is crucial. Failure to synchronize data properly can lead to discrepancies, duplication, or inconsistencies in information, impacting the accuracy and reliability of AI-generated outputs
  • Workflow adjustments: Integrating generative AI tools may require adjustments to your existing workflows and processes. You need to carefully evaluate and modify your workflows to incorporate the use of generative AI effectively. This may involve redefining roles and responsibilities, adapting processes to leverage the AI-generated outputs, and ensuring smooth collaboration between the AI tool and your team members

To address these integration challenges effectively, undertake a comprehensive assessment and planning process to identify compatibility issues and determine the required adjustments. 

One potential solution to consider is utilizing a platform such as SpotDraft, which seamlessly integrates with your existing CRM systems, making it easy for other teams to gain visibility into your contract lifecycle management. 

Also read: 6 Must-Have CLM Integrations with Business Tools
Also read: Generative AI for Contract Management: Best Practices to Ensure Safety

Strategies to overcome roadblocks and facilitate AI adoption for in-house legal teams

Strategies to overcome roadblocks and facilitate AI adoption for in-house legal teams

There are a few best practices and strategies you can employ to overcome these roadblocks and successfully integrate technology into your operations. You might need to align data formats, sync information between different systems, or tackle differences in software and hardware requirements. 

Dealing with all these complexities takes up valuable time and resources, causing disruptions to your day-to-day operations and potentially slowing down the adoption of the new system. It can be a real challenge to make everything fit together smoothly.

#1 Foster collaboration between your team and technology teams

When legal and tech teams come together, their collaboration forms a powerful synergy. Open lines of communication and frequent knowledge-sharing sessions create an environment where legal and technology professionals can exchange ideas, insights, and challenges.

Here are several approaches to promote collaboration between legal and tech teams:

  • Establish regular meetings or workshops where both teams can come together to discuss projects, share insights, and brainstorm ideas
  • Encourage open and transparent communication channels between legal and tech professionals to facilitate the exchange of information and ensure alignment on project goals
  • Provide opportunities for cross-training and education, where legal professionals can gain a deeper understanding of the technology and technical professionals can learn about legal considerations
  • Create a culture of collaboration and mutual respect, emphasizing the value of each team's expertise and the importance of working together to achieve common goals
  • Involve legal professionals in the early stages of technology projects to ensure legal compliance and address any potential legal issues or risks from the outset
  • Engage legal professionals in the development and review of policies, guidelines, and ethical frameworks related to generative AI, leveraging their expertise to ensure responsible and ethical implementation

Or you could simply upgrade to SpotDraft AI. It enables collaboration and version control of your contracts as well.

“[SpotDraft] is very easy to use and sending directly to the customer hasn't been this smooth. Would definitely recommend others to try the platform and automate the complete work.”

~ Steve Nash, Sales development representative
Review hosted on G2
Also read: Contracts are not built on hope, but on collaboration

#2 Start with pilot projects and gradually implement generative AI

“With generative AI, you can't really define what the use cases are right now. So, to ensure people aren't coming to legal for every test use case, you can just create a sandbox to let them explore and come to you when they're ready to expose something to the customer or they've got a product behind it. It's going to create a better environment for both your technologists and for you.”

~ Ken Priore’s, ex-Director of Privacy, Atlassian

Mastering the Intersection of Law, Technology, and Privacy

Instead of implementing generative AI on a large scale, consider starting with pilot projects. Identify specific areas or tasks within your legal workflow that can benefit from AI automation. 

You can utilize SpotDraft’s AI contract analysis capabilities on a limited basis to test the effectiveness and feasibility of generative AI. This approach allows you to gain insights, evaluate performance, and make any necessary adjustments before scaling up the implementation.

Also read: How to Use Contract Analytics Software to Uncover Insights

#3 Monitor and evaluate AI systems to build trust

Trust is crucial when it comes to AI systems because it affects decision-making, impacts individuals and society, influences user adoption, and contributes to organizational reputation and credibility.

You can implement robust monitoring and evaluation practices for generative AI systems through the following strategies:

  • Establish clear objectives: This includes identifying key performance indicators (KPIs) and metrics that align with your team's goals and the needs of your organization
  • Define evaluation criteria: Develop specific evaluation criteria to assess the performance, accuracy, reliability, and ethical considerations of the generative AI system. This may involve evaluating factors such as response time, error rates, bias detection, fairness, and compliance with legal and ethical standards. 
  • Collect diverse and representative data: To enable effective monitoring and evaluation, ensure that the generative AI system is trained on diverse and representative data. By incorporating a wide range of legal cases, documents, and scenarios, you can minimize bias and improve the system's performance. Continuously update and expand the training data to adapt to evolving legal trends and challenges
  • Implement real-time monitoring: Establish mechanisms for real-time monitoring of the generative AI system. This can involve integrating monitoring tools or dashboards that provide visibility into the system's performance, outputs, and behavior. Real-time monitoring allows you to promptly detect anomalies, errors, or bias-related issues, enabling timely interventions and adjustments.

SpotDraft offers monitoring and analytics capabilities for your generative AI system and, by leveraging the platform’s monitoring features, you can ensure the continuous integrity and effectiveness of your generative AI system.

“Easy to use, very efficient in managing all important legal documentation under one roof, easily customisable according to user preferences. The Gmail plug-in feature is time-saving and gets things done in a jiffy.”

~ Aruna M., Manager Legal

Review hosted on G2

Also read: Contract Monitoring: 6 Best Practices for Legal Teams

#4 Address data quality and security concerns

Ultimately, it's all about protecting sensitive information and preserving that vital client trust, while also steering clear of any potential legal or reputational risks. You'll even gain a competitive edge!

So, when you implement robust data protection strategies, you're effectively safeguarding all that confidential data, maintaining the sacred attorney-client privilege, and keeping any unauthorized access or breaches at bay. This not only strengthens your relationships with clients but also helps establish your team as a trusted partner.

Here are several approaches to enhance your data privacy:

  • Develop and enforce strict data privacy and security policies within the legal team
  • Provide regular training and awareness programs for all team members to educate them about data privacy best practices and potential risks
  • Implement strong data encryption methods to protect sensitive and confidential legal data
  • Adopt multi-factor authentication to ensure only authorized individuals can access the data
  • Regularly update and patch software systems to address any vulnerabilities
  • Conduct thorough risk assessments to identify potential weak points in data security
  • Establish secure systems for storing and managing legal documents, such as using SpotDraft's AI-powered contract management platform
  • Regularly review and audit data privacy and security measures to ensure compliance and effectiveness
Also read: Contract Security: Hacks and tips for safeguarding your contracts

Enable the successful adoption of Generative AI 

Adopting generative AI in the legal field can face obstacles such as lack of awareness, data privacy concerns, ethical considerations, and cost constraints. To overcome these challenges, you should educate yourself, prioritize data privacy, establish ethical guidelines, and manage costs effectively.

Implementing the strategies in this blog post and embracing innovative solutions like SpotDraft will empower your team to seamlessly integrate generative AI, optimize operations, and drive remarkable value for their organizations.

Try out SpotDraft AI to overcome roadblocks. Request a demo now!

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