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14 February 2024 ·

Integrating Artificial Intelligence (AI) with contracting software speeds up processes



By 2030, virtually every company will be using some form of Artificial Intelligence (AI) contracting software. If you have not done so, you may need to start researching now for an AI contract management system and find the right consulting firm to ease the transition -- because the world of public and private sectors will be moving ahead with AI.  We will all face challenges like the ones that follow, but solutions are not that difficult.  You can do this!

Most of us know how recent technological innovation has again brought new and efficient life into our stream.  Not long ago we pushed for change in contract drafting when the volume of contracts per enterprise began exponentially rising.  Simultaneously, however, we discovered our contract drafting, review, and negotiation processes taking far too long.  A plethora of stories told revealed, for example, how an overlooked mistake in a contract can waste much time and cost companies millions -- take your pick on the currency.

Then, when AI became available, our contracting tasks required mastering AI’s power to produce better and faster efficiency and production.  So, today, whether we manage a procurement team or the contract managers directly, we are all becoming more aware of the various areas in contract management where AI can vastly expedite our processes and make our workflow more efficient and accurate.  But, within that, we still face challenges like data preparation and software integration with AI.

Preparing data for AI integration projects will be essential to ensuring the profitable efficiency that our AI-integrated contract management systems and large language models (LLMs) can yield us. Designating data preparation and setting up the precedence parameters will create several new opportunities for internal growth and hiring within our sector.

A meticulous and proper strategy for selecting operations is fundamental. A few contract management systems like Conga1 continue to develop and improve AI-integrated software to help us manage, execute, and organize contracts more effectively. Although we place high respect for AI and self-learning systems, processing organizational data is absolutely essential for successfully evolving within this new era of contract management. And this evolving includes applying and distributing precedence in agreements by using similar (recognizable) nomenclature.

We need to know how to make the best use of such changes now and more changes to come.  As examples, LLMs used by Robin AI2 or Conga are already reducing contract review times by 82%3 on average and currently pushing to get us all in the 90th percentile! 

Time is of the essence. If your contract management system and processes are not entirely efficient you are wasting time and losing money. The consolation is that you are definitely not alone. Inefficient contract management causes the average company to suffer yearly losses of nine percent to their bottom line.4  Dumping antiquated contract repositories is not advisable.  Instead, augmenting them with an AI and self-learning tools is the only way to avoid wasting time.

We need to first integrate and maintain the information that the AI-integrated contract management system will use. Worldwide, only a handful of consulting firms today can legitimately claim to specialize in working with these LLMs Yet, this specialized part of the contracting sector is about to skyrocket and will require individuals with more expertise and critical thinking. Integrating your organizational data and prior contracts from larger enterprises will be time-consuming and expensive but absolutely worth the effort. Maintaining the management system requires expertise to keep the AI organized in its learning. 

The goal with AI in contracting is to streamline the contract review, drafting, and negotiation processes by using automated data from preceding documentation, including contracts and relevant applicable laws. This practice allows the LLM to be fed with proper information so that accurate predictive contracting becomes the norm in your management system.5 This powerful connection can only be obtained by properly integrating data and past contracts from antiquated repositories and selecting the right LLM and AI software.

The AI’s learning depends on your selected team’s masterful delivery.  Consulting firms will do their best to present you with platform options and tight-knit strategies for integration, but the most important aspect of evolving your contract management system will be the complete and organized inclusion and subsequent maintenance of your contract repositories and cataloged transactions.

When integrating contract management software – use the right data!

Data is the biggest cost deficit we currently have in the actual AI upscaling projects in the contracting space. Many good systems exist out there, but if we don’t adequately prepare the data for the machine to learn and integrate, we will waste this great new AI force. Hence comes the part where we must evaluate the cost versus the reward.

Cost of scanning -- The days are over of lawyers wishing that a computer could scan through hundreds of pages and produce a contract, but the system that will do the work needs need to be fed the correct data! That scanning habit comes from extrapolating data, contracts, regulations and inputting them into a repository to use in a LLM.  As a result, the amount of quasi-legal jobs (appearing legal)  continues growing in the legal sector. This accounts for more than 1% of the global GDP.6 The value of the contract management market is actually forecasted to reach almost $7 billion by 2028.7 According to a study in 2023, 65% of companies with in-house counsel are now using contract-management software.8

Depending on which AI-integrated contracting software you use, you can expect to pay anywhere from $15,000 to $50,000 per month.9 Market leaders will charge $500,000 to $1,000,000. For example, for ten users plus implementation, Conga costs around $39,200 per year. Currently, few people are well versed in the AI contract management space and they can drive up the cost to a company due to their increasing demand.

Creating jobs plus reducing time and litigation

Legal teams today spend too much time on the intricate and nuanced composition stages when dealing with large organizations’ adoption agreements, partial assignments, and renewals of master service agreements (MSAs). Also wasteful is time taken to find proscribed anticipatory measures and initiate requests for guidance on replies to the external parties redlines.  AI can analyze risky clauses in contracts; can flag ambiguous and irregular language that is not industry qualified and can identify potential issues at the negotiation stage.10

It is absolutely necessary to search for the appropriate laws of any given jurisdiction when evaluating specific clauses or reviewing your company’s contracting guidebook for guidance, if one exists. A company’s contract manager or legal team shouldn’t be spending time on tasks that can be automated by AI integration.  Instead, a team should focus on accelerating deal closures while mitigating risk. Part of the contract management process which the AI can be taught to include for legal professionals to review includes observing compliance, analyzing operational data, and integrating precedence. 

An abundance of job opportunities will now spring forth for people to learn and affect the data preparation process for AI upscaling. Major companies will have tens of thousands of contracts that will need to be organized and prepared so that the new AI contracting systems can learn and use them as precedent.

For starters, business histories with providers, invoices, and various laws will have to be included. The work will be immense and during the data preparation for AI upscaling, we will ask ourselves if this will actually be worth it -- given the cost of the systems, resources, and the reallocated efforts in labor. Yet every legal professional knows that the task must be done, even when it is overwhelming and the projections are distant.

Forward-thinking vision

Investors have a growing concern about how far AI will be allowed to develop. However, in contracting we will see few, if any, blockades to our strategies for maximum efficiency. The United States federal government and international counterparts are enacting legislation to ensure oversight of AI systems, but the legislation is more geared towards determining how the machines use consumers’ private and sensitive information, rather than how AI is developed for commercial contracting.

Kyle Hauptman, Vice Chair of the U.S. National Credit Union Administration Board11 explained this regulatory concept best at the 2023 Chicago AI Conference in October when he stated that the AI sector has been consistently working hand in hand with the federal government to develop and place restrictions on AI. He stated that “unlike with crypto, where people tried to develop without oversight, made their money, then dealt with adverse consequences, AI developers have been in constant contact with the government whose trust and cooperation will allow for faster growth in the market.” He further explained that the main concern with AI is actually that we won’t maximize the opportunities for job creation and expansion that AI can deliver.  He cited Detroit’s hostility towards foreign automakers like Toyota and Honda.

Future is bright

So, again, my prognosis is that by 2030, every company with a contracting team, whether Fortune 100 or fifteen employees, will be using some form of AI contracting software. While we can all wait until the cost goes down, a tenth of our profits that we are losing to inefficiencies could pay for the upscale in a quarter. So, why not seek an AI contract management system and the right consulting firm to make the transition easier. While my money backs experience, there will be a lot of new entities out there in the next year that can surely help your organization take a step in the right direction.

This is an exciting time to be in contract management. The labor is laid out and the benefits are observable. Contracts that would normally take a contract manager two hours to draft based on prior negotiations or existing Master Service agreements will now take 15 minutes to review and finalize. Members of this new AI contracting community will be able to better serve their customers, partners, and business interests like never before. Let’s begin the preparations.


Alan Aguirre-Rivera, originally from Texas, pursued his Juris Doctor degree at the University of Tennessee, and upon graduating relocated to Chicago, Illinois. Alan is a former Chicago Police Officer, American Bar Association Representative, and litigation Associate. Aided by his past experience in Negotiations, litigation, and Contracts, he now leads the North America Learning & Development team at Nexdigm, where he prepares lawyers in the use and understanding of AI Automated Contracting systems, helps prepare and launch automated contracting integration projects, and creates training programs to serve Nexdigm’s clients and business partners. Alan enjoys traveling to mountainous regions to hike and explore nature, playing soccer with his friends, and is training to participate in mixed martial arts. He lives in Chicago with his wife, Lize-Ann and their dog, Ragnar FurSon.

Swapnil Shah has over 16 years of extensive experience and demonstrated history of working in the corporate law and healthcare practice industry. Swapnil has provided tactical direction to drive business outcomes and achieving business goals. He has led multiple commercial contracting teams in various organizations and provided objective, practical, results-oriented assistance to address the ever-evolving business challenges facing healthcare companies.  Swapnil has also been responsible for enterprise-wide strategic plans, company positioning, business plan development, validation, and researching/capitalizing on new market opportunities. Swapnil has sat on a policy making board at Blue Cross and Blue Shield to introduce and implement ideas that improve the daily lives of heath care patients. In his previous role at CVS Healthcare, Swapnil served as the Director of an adaptive contract management and rebating team that was responsible for mitigating risk, negotiating, and maximizing profitability for a variety of multi-million-dollar healthcare pharma contracts.


  1. Conga – Reference also: Conga CLM article
  2. RobinAI – Reference also:  How does RobinAI function? What is it?
  3. Reference also: Robin AI Plugs AI Contract Copilot Directly into Microsoft World
  4. AI-Based Contract Management: The Complete 2022 Guide, Misra, Sarvarth, ContractPodAi, (2022).
  5. Predictive Contracting, Williams, Spencer, Colum, Bus. L. Rev. 621 ( (2019).
  6. Team Behind New Generative AI ‘Copilot’ Says Tool Can Reduce Contract Review Time by 82% on Average, Lawlor, Mason,, (2023).
  7. Enterprise Contract Management Market Size, Challenges, Scopes, Market Share, Revenue, and Forecasts 2023 to 2030, 360 Industry Insights, (2023).
  8. How Your Legal Team Can Avoid Contract-Management Software Land Mines, Guzman, Hugo,,,no%20other%20type%20coming%20close. (2023).
  9. How Much should AI Cost?, AI Partnerships Corp. ( (2022).
  10. How AI Could Reduce Contract Inefficiencies And Drudgery, Nelson, Cynthia,, (2023).
  11. Kyle Hauptman, Vice Chair of the U.S. National Credit Union Administration Board.  See also:

By 2030, virtually every company will be using some form of Artificial Intelligence (AI) contracting software. If you have not done so, you may need to start researching now for an AI contract management system and find the right consulting firm to ease the transition -- because the world of public and private sectors will be moving ahead with AI.  We will all face challenges like the ones that follow, but solutions are not that difficult.  You can do this!

Alan Aguirre-Rivera Swapnil Shah
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