Oh, such a nice dream -- the idea that implementing artificial intelligence (AI) into our workflows will automatically help us solve human problems faster! And yet that is exactly the wish legal teams too often embrace when first trying to implement AI, especially contract-focused technologies. Too many do not realize that getting these solutions up and running is far more complex than most lawyers -- as well as business leaders -- can manage. So how can we all bring automation onboard to do business better and faster while avoiding implementation hiccups? It takes only five steps to rise above the challenges and discover better ways of working. You can absolutely do this! It just takes diving deeper into research, making the right choices, and training the right people.
FOCUS ON IMPLEMENTATION CHALLENGES FIRST
I suggest that you focus on two major implementation challenges before doing the five steps. As contract-focused technology continues to become more available and advanced, a speedy and healthy implementation – along with integrations and ease of use – is imperative now and will later become increasingly important to accurately select and successfully adopt AI technologies for your organization.
First, realize that implementation and onboarding can make or break any component of a successful contract review technology. Lawyers who start embattling within an implementation process that is taking “too long” -- or is creating obstacles -- can end up frustrated after wasting money and sometimes abandoning the solution altogether. Worst case is a botched implementation that can be so damaging it warrants taking legal action. No one wants to go there.1
Second, because implementing a new technology is a significant undertaking, it is essential to have team effort working well between customer and vendor. Recognizing the potential for error is the first step in avoiding mistakes. So, unwanted challenges can result if you lack any of the following:
- process -- If the customer lacks the necessary processes to facilitate technology and is using technology as a band-aid or a quick fix -- the solution will fail.
- time -- Because most companies are deadline-heavy, they rarely have time for implementation. Not carving out time or personnel to oversee the implementation will result in a lengthy process that featuring sub-par onboarding and use.
- leadership -- If the customer lacks an internal advocate or someone dedicated to and invested in making the implementation succeed -- the project is more likely to fail.
- documentation or input -- Automation solutions that use AI and/or machine learning require historical data to begin the learning process. Without examples of problems to learn from, or data that reflects problems to solve -- a natural language processing (NLP) system won’t be of much use.
For example, if you’re trying to teach a machine learning system how to redline contracts according to your playbook, you need historical contract data reflecting rounds of contract redlines. Without this data, the solution won’t produce output that closely reflects how your company reviews and marks up contracts and avoiding this step will only waste time and money. Part of the responsibility lies with the vendor of the solution who should procure redlined versions of previous contracts from customers to extrapolate preferred terminology, changes, or clauses.
- trust -- Any mistrust of the new technology in the customer’s organization will inhibit proper implementation and onboarding. Of course, it’s natural for employees to look cautiously at new solutions – especially when it comes to cyber threats and security – but working closely with the vendor should alleviate these fears and build trust.
AND NOW FOR THE FIVE STEPS!
- Apply change management principles
Getting a return on investment (ROI) is not just implementing technology simply because it’s available, affordable, and you heard it’s a good idea. Such a strategy also won’t solve any real problems that contribute to long-term growth. Instead, you need to apply several change management principles that involve people and processes:
- Gather the right stakeholders – including future users – for a brainstorming and mapping session that will identify your gaps and potential roadblocks. Evaluate how your departments and your people work before you try to understand how the technology will help them. Only then can you draw out what new processes will look like, and you’ll be sure your solution solves real problems. You’ll also be able to ensure your organizational culture supports this change and is ready to integrate the solution into existing processes.
- Organize your processes. To improve your organization’s functionality through automation, you must organize your processes and data first. If you don’t, you’ll end up with “automated rubbish” that fits no purpose. Your data should be clean because the efficacy of AI and machine learning-based technologies depends on high-quality data. Unify and eliminate silos to ensure clean data so you don’t get messy outcomes.
- Ensure everyone is on board with the new technology
After you’ve gathered your people in step one, go more in-depth with your team to ensure you have buy-in acceptance on all levels. Some people are quick to embrace new technology while others are more resistant and prefer their familiar tools. To draw in those resistant ones, involve them in the selection and planning process to demonstrate how the new technology will benefit them and solve their tangible problems.
Preparing leadership to invest in the technology is part of this process because subordinate employees will see leadership’s willingness and excitement and will want to get involved. Make sure you especially include workflow managers who must alter how work gets done and lawyers who must trust the technology’s outputs.
- Ask the vendor the right questions
Knowing what to ask of the technology vendor is a crucial part of your decision making so that you can understand whether the implementation process will be a good fit for your organization. Questions can include:
- What does a typical implementation process look like?
- What information do I need to provide to facilitate the implementation process?
- What does the onboarding process entail?
As more contracts-based technologies enter the market, the more power you, as the customer, will have over the vetting process. Consider asking any of the following questions as well, because you are in control (hold the cards). So, ask yourself:
- Can you provide contact information for current users of the product?
- Can you provide evidence that your solution does what you say it will do?
- What is the typical time-to-value for a user, a department, and the organization?
- What recommendations would you provide to help an organization get the most ROI out of your product?
- What are you doing to address cybersecurity requirements?
- What pitfalls do you need to watch for and avoid during and after implementation?
- Do you provide immediate and on-going support for virtual and on-site operations?
Vendors also have a responsibility to be up front and answer questions the customer should be asking in the spirit of transparency and integrity.
- Make time for training
We’re all busy – particularly lawyers. No one wants to take too much time for non-billable hours, especially when experiencing tight deadlines. But taking the time to learn the new system and train the people is vital for product success.
Put together a small implementation team that will help support the implementation process and keep people and projects on time and motivated. Be sure that team can set clear, realistic deadlines for rolling out the solution, provide incentives for employees to use the new software, and work with the vendor.
Be sure the team is equipped to train others using the most successful formats. Because day-long sessions in a conference room rarely work, you should explore other formats for training such as interactive demos, gamification, videos, other microlearning resources, and geofencing (setting up virtual geographic boundaries using technology).
Here's an option for AI-based, user-generated tools
There’s no excuse today for solutions – particularly software-based ones – that involve onerous, lengthy implementations. The right tools will employ advanced features such as AI and machine learning that allow users to implement the technology in minutes with minimal vendor handling.
Look for solutions that:
- easily integrate with your existing tools;
- require time for training and learning the system, not actually implementing the technology;
- don’t require advanced user expertise to get up and running quickly;
- can demonstrate clear ROI from other users with organizations like yours;
- have demonstrable security provisions; and
- offer vendor support post-implementation.
Remember, you’re in the driver’s seat when onboarding a new technology. Although it’s a team effort between customer and vendor to see through a successful implementation, you have the power to ask questions of your vendor, inspire buy-in from your staff, and ultimately deliver game-changing technology that introduces untold efficiencies and savings. As upticks in funding for legal technology continue, you will have more to choose from in the future. No better time than today to consider change – agreed?
ABOUT THE AUTHOR
Dan Broderick, CEO and Co-Founder, leads BlackBoiler’s strategic planning and operations. Through deep domain expertise and passion, he’s built a vision for BlackBoiler to transform status quo contract negotiation. Before founding BlackBoiler, Dan was an attorney with Kilpatrick Townsend & Stockton LLP, an AM 100 law firm. There, he specialized in negotiation-related disputes, and developed more efficient processes for contract review. Additionally, Dan holds a degree in engineering management.
BlackBoiler, is a National Science Foundation backed, legal technology company that seeks to revolutionize the delivery of legal services. Their automated contract review system automates contract review and negotiation with the desired outcome of relieving attorneys of redundant and costly work.
- Ref article: ARTIFICIAL LAWYER, Icertis Sued Over Alleged Failings of CMS Implementation (Nov 2021)