Contracts rethought and
redesigned: A new era with AI
Hilja Autto
Faculty of Law, University of Lapland, Rovaniemi, Finland; School of Accounting and
Finance, Business Law, University of Vaasa, Vaasa, Finland; Autto Law & Design,
Espoo, Finland
Helena Haapio
Faculty of Law, University of Lapland, Rovaniemi, Finland; School of Accounting and
Finance, Business Law, University of Vaasa, Vaasa, Finland; Faculty of Information
Technology and Communication Sciences, University of Tampere, Finland; Lexpert
Ltd, Helsinki, Finland
Jouko Nuottila
Faculty of Law, University of Lapland, Rovaniemi, Finland
Abstract
This article discusses the potential of generative artificial intelligence (AI) to revolutionize contract
thinking and design. Experience and research tell us that most contracts focus on the wrong things
—failure rather than success—and are presented in a way that is inaccessible to many people.
Using the principles of proactive contracting and contract design, AI-powered writing assistants
such as ChatGPT can help change the contracting paradigm by facilitating the transition from draft-
ing to design and from reaction to proactive action. They can help transform the content, lan-
guage, structure, and presentation of contracts, simplifying the tedious parts and increasing
stakeholder empowerment and choice. This exploratory article presents examples of using AI
tools to generate ideas and clauses for commercial contracts and to support contract redesign.
This facilitates the creation of easy-to-read explanations, headings, and layered layouts that
make contracts more effective, transparent, and sustainable, leading to better business and societal
outcomes.
Keywords
AI-assisted drafting and design, contract (re)design, generative AI, proactive contracting,
sustainability
Corresponding author:
Hilja Autto, University of Lapland, Rovaniemi, Finland.
Email: hilja.autto@ulapland.fi
Article
Journal of Strategic
Contracting and Negotiation
1-28
© The Author(s) 2024
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/20555636241261278
journals.sagepub.com/home/jsc
1. Introduction
Contracts can help organizations make things happen and put their plans into practice, potentially
enabling better business and a better society. But most contracts do not do this well. Instead, they
focus on the wrong things—failure rather than success1—and are presented as a wall of text that
alienates people.2
The problems of contract content and presentation are not new. In fact, they are well-researched
and well-documented.3 Most people would agree that creating accessible and user-friendly con-
tracts is critical to effective communication and understanding between parties. However, the
ways in which this can be achieved are currently underexplored.
This article looks at strategies and tools that can help make contracts easier to read and write. We
are challenging the current content, language, and style of contracts and are not interested in tools
that replicate them more effectively. Instead, we want contracts that better serve contracting orga-
nizations and the people who work with contracts, helping them to achieve their goals. We also
expect future contracts to address the growing emphasis on environmental, social, and governance
(ESG) objectives in business. Our research strongly suggests that contract redesign, prioritizing
plain language and information design, is an essential step toward stakeholder empowerment and
choice.
The article is structured as follows: first, we introduce the problems with current contract
thinking and design, highlighting the need for a paradigm shift in both areas. In the “Rethinking
commercial contracts” section, we illustrate how today’s mainstream contracts are not what orga-
nizations and negotiators would want them to be. Contracts need to be rethought: their current focus
on protecting against failure makes them ill-suited to fostering good relationships and advancing
ESG goals. After examining the existing shortcomings, in the “Redesigning contracts” section,
we propose proactive contracting and contract design as a solution and explore the potential of
using ChatGPT, a language model developed by OpenAI, to support the necessary redesign. Our
experiments show that ChatGPT can help both contract readers and contract writers in many
ways. For readers, it can provide easy-to-understand explanations of complex information. For
writers, it can suggest topics, alternatives to legalese, headings, summaries, and layered layouts
1. “Most Negotiated Terms 2022: Negotiating in a Time of Turmoil,”World Commerce & Contracting (WorldCC), 2022,
https://www.worldcc.com/Portals/IACCM/Resources/11463_0_Most-Negotiated-Terms-2022.pdf; “Most Important Terms
2022/23: Negotiating for Marriage or Divorce?,” WorldCC, 2023, https://www.worldcc.com/Portals/IACCM/Resources/
11487_1_Most%20Important%20Terms%202022.pdf.
2. A wall of text is often used to refer to a document that is tightly written, sparsely titled and otherwise hard to read. See,
for example, Stefania Passera, “Beyond the Wall of Contract Text: Visualizing Contracts to Foster Understanding and
Collaboration within and across Organizations” (PhD diss., Aalto University, 2017); Robert Waller, “Designing Contracts
for Human Readers,” in Research Handbook on Contract Design, eds. Marcelo Corrales Compagnucci, Helena Haapio,
and Mark Fenwick (Cheltenham: Edward Elgar, 2022), 55–74; Helena Haapio, Next Generation Contracts: A Paradigm
Shift (Helsinki: Lexpert Ltd, 2013).
3. See, for example, Stefania Passera, Emily Allbon, and Helena Haapio, “Contract Transformation: Merging Drafting
and Design to Meet the Needs of Human Readers,” in Research Handbook on Contract Design, eds. Marcelo Corrales
Compagnucci, Helena Haapio, and Mark Fenwick (Cheltenham: Edward Elgar, 2022), 92–112; Helena Haapio and
Stefania Passera, “Contracts as Interfaces: Visual Representation Patterns in Contract Design,” in Legal Informatics, eds.
Daniel Martin Katz, Michael J. Bommarito, and Ron Dolin (Cambridge: Cambridge University Press, 2021), 213–38.
https://doi.org/10.1017/9781316529683.01.8; Eric Martinez, Francis Mollica, and Edward Gibson, “Poor Writing, Not
Specialized Concepts, Drives Processing Difficulty in Legal Language,” Cognition 224 (2022): article 105070. https://doi.
org/10.1016/j.cognition.2022.105070.
2 Journal of Strategic Contracting and Negotiation 0(0)
that follow information design principles. In this way, ChatGPT can help to communicate contrac-
tual information in a clear and accessible way. After presenting our experiments, which show great
potential, we conceptualize our findings, assess the risks and pitfalls, and look to the future of
AI-assisted contract design. Section “Conclusions” concludes the article with some future
prospects.
2. Rethinking commercial contracts
2.1 A shift from problem-focused to goal-supportive contract thinking
Almost 90 years ago, Fred Rodell, a Law Professor at Yale University, observed: “There are two
things wrong with almost all legal writing. One is its style. The other is its content.”4 This criticism
still applies to much of legal writing today. It also applies to contract drafting. What is worse is that
our legal system seems to support this: many administrative and legislative processes, even those
intended to protect consumers or investors, seem to ignore the imperative to communicate
meaningfully.5
While some see contract drafting as a subset of legal writing, we are not alone in arguing that
there are significant differences between the two.6 Contracts contain not only legal but also finan-
cial, operational, and technical information. Companies make contracts not just for their legal teams
or for future disputes and litigation: they make contracts to achieve their goals.
The vast majority of contract readers do not have law degrees. Yet a legal writing style dominates
contracts as if they were written by lawyers just for other lawyers. Newcomers to the world of con-
tracts may question this style at first, but then adopt it as part of the culture; newcomers also want
their contracts to look “professional” and “legal.”7
When we ask what is the purpose of contracts, or what are their key provisions, there may be
differences of opinion within organizations and between different members of the negotiating
teams. The legal department may have a different view of corporate goals and priorities than,
say, the engineering or commercial departments. World Commerce & Contracting (WorldCC)
surveys of negotiators around the world reveal how this tension is reflected in contract negotiations:
the terms that are negotiated most frequently (“Most Negotiated Terms”) are very different from the
terms negotiators consider most important (“Most Important Terms”). The results of the WorldCC
2022 survey are shown in Table 1.8
The left column in Table 1 illustrates that limitation of liability is negotiated with the greatest
frequency. In WorldCC’s annual surveys, year after year, limitation of liability has retained its
top position, with indemnities following as either 2 or 3. This shows that negotiators spend
much of their time preparing for failure and conflict rather than securing success. The list of
Most Negotiated Terms continues to be dominated by clauses dealing with the consequences of
failure, claims, and disputes. As noted by Tim Cummins, the President of WorldCC, contracts
4. Fred Rodell, “Goodbye to Law Reviews,” Virginia Law Review 23, no. 1 (1936): 38–45; Fred Rodell, “Goodbye to
Law Reviews: Revisited,” Virginia Law Review 48, no. 2 (1962): 279–90.
5. Wendy E. Wagner and Will Walker, Incomprehensible!: A Study of How Our Legal System Encourages
Incomprehensibility, Why It Matters, and What We Can Do About It (Cambridge: Cambridge University Press, 2019).
6. See, for example, Haapio, Next Generation Contracts, 46.
7. Haapio, Next Generation Contracts, 46.
8. WorldCC, “Most Negotiated Terms 2022,” 6, 9; WorldCC, “Most Important Terms
2022/23,” 3.
Autto et al. 3
have often become “a battleground, in which the parties abandoned the search for mutual ground
or interests and instead became focused on relative power and the ability to allocate risks.”9
Contracts—and the most frequently negotiated terms—seem to focus on the legal issues that will
be important in a courtroom, rather than tackling the underlying causes of claims and disputes.10
Yet in light of these surveys, disagreement over contract scope is the number one cause of
claims and disputes, and “material disagreement over scope and goals is several thousand times
more likely to occur than litigation.”11
What the left column of Table 1 shows is not what the negotiators would want to spend their time
on. When WorldCC asked participants to describe where they think negotiating time should be
focused in the future, they responded what the Most Important Terms listed in the right column
of Table 1 show. Their responses indicate that negotiators see a need to change their current
agenda. They see more value in negotiating terms related to scope and goals, price, delivery, and
service levels than terms such as liability and indemnities. The latter “occupy the place they
should—as last-resort fall-backs in the event that well-crafted intentions become derailed.”12
The documents that are being negotiated do not necessarily represent a true statement of the
parties’ expectations and understanding. Instead, they may reflect what the participating companies’
lawyers typically find necessary to protect their clients in a dispute. So, the focus of contract nego-
tiations may be guided by a template rather than the parties’ true intent and discussions. If the tem-
plates focus on the wrong things, automating them will only make things worse.13 Where legal
objectives dictate the drafting and design choices, they may be so strong that the business side
Table 1. World Commerce & Contracting (WorldCC) most negotiated versus most important terms 2022.
Most negotiated terms Most important terms
1 Limitation of liability Scope and goals/specifications
2 Price/charge/price changes Price/charge/price change
3 Indemnities Delivery
4 Liquidated damages Service levels
5 Termination Responsibilities of the parties
6 Scope and goals/specification Acceptance
7 Payment/payment options Amendments/changes to contract
8 Warranties Payment/payment options
9 Cybersecurity/data privacy Product specification
10 Intellectual property Limitation of liability
9. Tim Cummins, “Strategic Contracting as a Source of Organizational Success,” Journal of Strategic Contracting and
Negotiation 1, no. 1 (2015): 7–14, https://doi.org/10.1177/20555636155795.
10. Cummins, “Strategic Contracting as a Source of Organizational Success,” 12.
11. Cummins, “Strategic Contracting as a Source of Organizational Success,” 12. See also International Association for
Contract and Commercial Management (IACCM) and National Audit Office, “Attitudes to Contracting,” Research material
2013/2014. Accessed June 5, 2023. https://www.worldcc.com/Resources/Content-Hub/View/ArticleId/2768/Attitudes-to-
Contracting-Are-they-undermining-performance?
12. “The Top Negotiated Terms: Negotiators Admit They Are OnWrong Agenda,” IACCM, 2009. https://www.worldcc.
com/Portals/IACCM/resources/files/2008_Top_Negotiated_Terms.pdf.
13. See, for example, Verity White, “Bad contract templates are the ocean plastic of the business world,” LinkedIn,
January 13, 2023. https://www.linkedin.com/pulse/bad-contract-templates-ocean-plastic-business-world-verity-white.
4 Journal of Strategic Contracting and Negotiation 0(0)
becomes alienated.14 In the words of Thomas D. Barton, one recurring barrier to successful contract-
ing is the “exaggerated and largely unnecessary separation between the business goals that clients seek
to achieve, and the legal methods by which contractual relationships are created and managed.”15 Put
more bluntly, in the words of Irene Etzkorn, a simplification expert, it is a common mistake of com-
panies to “allow the Legal department to tyrannize the rest of the company.”16
2.2 From a legal focus to an operational focus: From reaction to proactive action
Traditionally, contract drafters and scholars have primarily addressed the needs of the legal com-
munity. The emphasis has been on using contracts reactively after a conflict or dispute has
already arisen.17 Even management scholars and economists have viewed contracts primarily as
tools for safeguarding the interests of the parties (often just one of them).18 Although essential
for commercial contracts, this narrow focus has overshadowed other important functions of con-
tracts, including facilitating communication and coordination, clarifying expectations, guiding
behavior, and promoting shared understanding.19
While some contracts may need to be used as evidence in court, most contracts do not.
Instead, their primary function is to serve as effective business tools that enable the parties
involved to achieve their desired outcomes. However, most contracts are still primarily
drafted by lawyers for lawyers, with the aim of creating legally functional and airtight agree-
ments that will provide the winning argument in a legal dispute.20 Most lawyers are trained
to protect their client, their side, rather than thinking in terms of protecting the collaboration
or relationship. Instead of focusing on the happy path, they focus on the opposite.21 In the
14. See, for example, Deepak Malhotra, “Great Deal, Terrible Contract: The Case for Negotiator Involvement in the
Contracting Phase,” in The Psychology of Negotiations in the 21st Century Workplace: New Challenges and New
Solutions, eds. Barry M. Goldman and Debra L. Shapiro (New York, NY: Routledge, 2012), 363–98.
15. Thomas D. Barton, “Collaborative Contracting as Preventive/Proactive Law,” in Proactive Law in a Business
Environment, eds. Gerlinde Berger-Walliser and Kim Østergaard (Copenhagen: DJOF Publishing, 2012), 107–27.
16. Irene A. Etzkorn, “Ten Commandments of Simplification.” Center for Plain Language. Accessed June 15, 2023.
https://web.archive.org/web/20131013040154/http://centerforplainlanguage.org/about-plain-language/ten-commandments-
of-simplification/.
17. For example, Haapio, Next Generation Contracts.
18. For example, Oliver E. Williamson, “Transaction-Cost Economics: The Governance of Contractual Relations,”
Journal of Law and Economics 22, no. 2 (1979): 233–61. https://doi.org/10.1086/466942.
19. For example, Anna Hurmerinta-Haanpää, “The Many Functions of Contracts: How Companies Use Contracts in
Interorganizational Exchange Relations” (PhD diss., University of Turku, 2021). http://urn.fi/URN:ISBN:978-951-29-
8433-6; “The Purpose of a Contract: An IACCM Research Report.” IACCM, 2017. https://www.worldcc.com/Portals/
IACCM/resources/files/9876_j18069-iaccm-purpose-of-contract-a4-2017-11-14-v1-webready.pdf.
20. For the prevailing focus on the safeguarding function of contracts, see, for example, Hurmerinta-Haanpää, “The Many
Functions of Contracts” and Haapio, Next Generation Contracts, with references. For a practitioner’s perspective, see Chris
Simkins, “L2L Contracts: Thinking beyond B2C and B2B,” Improving Contracts (blog), August 9, 2023, https://
improvingcontracts.com/l2l-contracts-thinking-beyond-b2c-and-b2b/ (discussing contracts where lawyers lead the process of
writing, reading, negotiating, and finalizing the contract documents on both sides). Such lawyer-to-lawyer (L2L) contracts are
not the focus of this article.
21. Our primary focus in this article is to examine issues from the perspective of businesses and their operational needs in
the context of commercial contracts. While we recognize the importance of legal objectives, enforceability, and risk
management, particularly in the relationship between law firms and their clients, these issues are beyond the scope of our
current analysis. Our goal is to explore how commercial contracts can be (re)designed to better align with and support
the overarching business objectives of organizations.
Autto et al. 5
world of software development and testing, the “happy path” refers to the desired software exe-
cution path where everything goes as expected.22 This, we argue, should be the guiding prin-
ciple for contract design as well: successful outcomes without ever having to go to court.
In contrast to the traditional view, we propose viewing contracts as proactive tools that are
designed and used to help parties to (a) achieve their objectives and promote mutual success, (b)
advance ESG goals, and (c) prevent problems from arising and conflicts from escalating into
legal disputes and litigation. This, in a nutshell, is the essence of Proactive Contracting.23
Initially, the approach focused on using contracts to promote better business. In recent years, it
has expanded to also include the promotion of societal goals, and responsible and sustainable con-
tracting has become a topic of growing interest in research and practice.24
A proactive contract has been described as one that is “crafted for the parties, especially for the
people in charge of its implementation in the field, not for a judge who is supposed to decide about
the parties’ failures.”25 In what follows, we propose a proactive approach to contracts and contract
design: one that focuses on the business, ESG, and operational needs of contracting organizations
and the people who work with contracts. Our aim is to strike a balance that accommodates business
and legal users as well as society at large. Rethinking contracts leads to the need to redesign them.
Otherwise, they will not be fit for the purposes we expect them to serve.
3. Redesigning contracts
3.1 Moving from drafting to design: Plain language and information design
Existing contracts have been criticized for their poor design or lack of design. Proponents of
Proactive Contracting have suggested that we should move from drafting contracts to designing
them.26 The principles of information design can help us make this transition.
The aim of information design is to make communication as effective and understandable as pos-
sible. Hayhoe defines information design as the process of identifying, selecting, organizing, syn-
thesizing, and presenting information to an audience in such a way that the audience can use it
effectively and appropriately to achieve a particular goal.27
22. We are not the first to discuss the happy path in contract related research: Mark D. Flood and Oliver R. Goodenough,
“Contract as Automaton: The Computational Representation of Financial Agreements.” Office of Financial Research
Working Paper 15-04. March 26, 2015. http://financialresearch.gov/working-papers/files/OFRwp-2015-04_Contract-as-
Automaton-The-Computational-Representation-of-Financial-Agreements.pdf. See also Helena Haapio and Vesa Annola,
“Contracting for the Happy Path: Promotive Legal Thinking for Better Business and Better Society.” ALSB Annual
Conference 2023, on File with the Authors.
23. See, for example, Anna Hurmerinta-Haanpää and Jouko Nuottila, “The Proactive Contracting Approach: The First 25
Years and Beyond.” Forthcoming.
24. See, for example, Juho Saloranta and Anna Hurmerinta-Haanpää, “Proactive Contract Theory in the Context of
Corporate Sustainability Due Diligence,” Journal of Strategic Contracting and Negotiation 6, no. 3–4 (2022): 221–236,
https://doi.org/10.1177/20555636231165901.
25. Gerlinde Berger-Walliser, Robert C. Bird, and Helena Haapio, “Promoting Business Success Through Contract
Visualization,” Journal of Law, Business & Ethics 17 (2011): 55–76.
26. Marcelo Corrales Compagnucci, Helena Haapio, and Mark Fenwick, eds., Research Handbook on Contract Design
(Cheltenham: Edward Elgar, 2022).
27. George F. Hayhoe, “Telling the Future of Information Design,” Communication Design Quarterly 1, no. 1
(September 2012): 23–26. https://doi.org/10.1145/2448917.2448922.
6 Journal of Strategic Contracting and Negotiation 0(0)
Figure 1. A summary of our experiments with OpenAI’s ChatGPT to help us plan and design the content,
language, and presentation of contract clauses in the context of the proposed EU Ecodesign Regulation. Our
experiments are described in the sections “Content design,” “Language design,” and “Presentation (layout
and structure) design,” and extracts and results from our conversations with ChatGPT are shown in Figures
2–5. © 2024 The Authors.
Autto et al. 7
Language is an important part of information design. Contracts are traditionally text-based, and
the language used plays a central role in contract design. Some might say that language is the con-
tract designer’s most important tool. We argue that text and language are critical for contract
designers and that writing and design must go hand in hand for contract design to be successful.
The principles of plain language can be useful to contract designers. Plain language is not just
about the choice of words, it is also about relevance, findability, understandability, and usability.
According to the International Plain Language Federation, “a communication is in plain language
if its wording, structure, and design are so clear that the intended readers can easily find what they
need, understand what they find, and use that information.”28 The International Organization for
Standardization (ISO) recently adopted this definition in its standard on the governing principles
of plain language.29 A follow-up standard on legal writing and drafting30 is under development.
These standards can also help to shape the drafting and design of contracts.
Contract design can mean different things to different people. While some people use contract
design as a synonym for drafting choices, others understand it to mean how the content is presented.
For the purposes of this article, contract design refers to both the content of a contract and the way
in which it is presented. Our approach combines contract content and presentation, drafters, and
designers, recognizing the importance of audience and purpose to successful communication.31 For
us, contract design is about content, language, structure, and document design, as well as user-centered
relevance, findability, understandability, and usability—all to achieve the parties’ objectives.
3.2 Exploring the potential of AI-assisted contract design
In the following, we explore the potential of using ChatGPT to support the (re)design of contracts.
We discuss our observations with examples of contract design in anticipation of forthcoming new
legislation that will force many organizations to review their existing contracts to ensure compli-
ance and may require updating or adding new provisions to meet the new requirements. The
ideas presented in our examples are also applicable to other contexts of commercial contracting,
whether the purpose is to advance business or societal goals.
We have chosen our examples from an area that will be subject to significant change as a result of
the proposed EU Regulation setting out ecodesign requirements for sustainable products,32 not only
because of our interest in the topic, but also to illustrate a scenario where those responsible for
28. International Plain Language Federation, “Plain Language Definitions.” Accessed June 28, 2019. https://www.
iplfederation.org/plain-language/.
29. International Organization for Standardization (ISO), “ISO 24495-1 Plain Language—Part 1: Governing Principles
and Guidelines.” Accessed June 15, 2023. https://www.iso.org/standard/78907.html.
30. International Organization for Standardization (ISO), “ISO/AWI 24495-2 Plain Language—Part 2: Legal Writing and
Drafting.” Accessed June 15, 2023. https://www.iso.org/standard/85774.html.
31. Thomas D. Barton, Helena Haapio, Stefania Passera, and James G. Hazard. “Reframing Contract Design: Integrating
Business, Legal, Design, and Technology Perspectives,” in Research Handbook on Contract Design, eds. Marcelo Corrales
Compagnucci, Helena Haapio, and Mark Fenwick (Cheltenham: Edward Elgar, 2022), 33–54. See also Passera, “Beyond the
Wall of Contract Text” and Haapio, Next Generation Contracts.
32. European Commission, “Proposal for a Regulation of the European Parliament and of the Council Establishing a
Framework for Setting Ecodesign Requirements for Sustainable Products and Repealing Directive 2009/125/EC.”
COM(2022) 142 final, March 30, 2022. See also “Ecodesign for Sustainable Products,” European Commission. Accessed
June 20, 2023, https://commission.europa.eu/energy-climate-change-environment/standards-tools-and-labels/products-
labelling-rules-and-requirements/sustainable-products/ecodesign-sustainable-products_en.
8 Journal of Strategic Contracting and Negotiation 0(0)
preparing contracts do not necessarily have access to precedents or clauses used in previous con-
tracts, and those responsible for implementation need to understand what is expected. These EU
requirements apply to products intended for the EU market and will also affect non-EU manufac-
turers and suppliers of such products. The examples are intended to be generic, cross-jurisdictional,
and cross-industry, affecting organizations of all sizes, whether they are suppliers or purchasers,
manufacturers or distributors.
As mentioned above, contract drafters rarely start from scratch; the language of a contract is
usually based on existing contracts, templates, or pre-approved clauses in clause libraries.33
Figure 2. ChatGPT suggesting contract topics. Extract from a conversation with OpenAI’s GPT-4, using
Browse with Bing (beta), accessed via the ChatGPT interface (May 24 2023 version).
33. Giulio Messori, “Legal Tech Solutions for the Management of the Contract Lifecycle,” in Contracting and Contract
Law in the Age of Artificial Intelligence, eds. Martin Ebers, Cristina Poncibò, and Mimi Zhou (Oxford, England: Hart
Publishing, 2022), 99–114; Passera, Allbon, and Haapio, “Contract Transformation,” 99.
Autto et al. 9
These templates and clauses could greatly benefit from a redesign to improve their content, lan-
guage, structure, and presentation, and we find that our examples are particularly useful for
people responsible for redesigning templates and clause libraries. The principles and findings can
be applied to any contract, as well as to other contexts and documents beyond contracts.
Figure 1 shows a summary of our experiments with ChatGPT and how the interactive work
between us (the human contract designer) and ChatGPT (the AI assistant) progressed at different
stages of our experiment.
Our experiment started with the context phase, where we instructed ChatGPT to use its browse
function to search for requirements in relevant EU legislation. ChatGPT provided us with summar-
ized results, from which we selected the clause topics that we found most useful for the purposes of
our experiment. This was followed by the content phase, where we moved from the selected clause
topics to the actual contract language: we requested and received suggestions for clauses and clause
explanations, which we validated. In the presentation phase, we selected the design patterns we
wanted to test. We instructed ChatGPT to apply them and present the selected clauses and explana-
tions in a table with a layered layout and frequently asked questions (FAQ)-style headings, all repre-
senting design patterns we had found helpful in other contract (re)design work.
In the following sections, after a brief overview of the basics of generative AI and ChatGPT, we
present examples of our experiments with ChatGPT in the context of contract design for the pro-
posed Ecodesign Regulation.
Figure 3. ChatGPT suggesting contract clauses. Extract from a conversation with OpenAI’s GPT-3,
accessed via the ChatGPT interface (May 24, 2023 version).
10 Journal of Strategic Contracting and Negotiation 0(0)
3.2.1 Generative AI and ChatGPT basics related to contract design. Generative Pretrained
Transformer (GPT) is a large language model developed by OpenAI.34 GPT is made commercially
available to third-party developers via the OpenAI application programming interface.35 For the
general public, GPT features are available as different versions of ChatGPT web applications.
Like other similar generative AI applications, GPT is based on several advanced technologies
that are combined and run on servers with enormous computing power to process huge amounts
of data at lightning speed. The core technology of these applications is based on a complex
neural network architecture, a form of technology we now call artificial intelligence (AI).36 A
neural network is a series of algorithms, often called nodes, linked together to mimic the way
Figure 4. ChatGPT explaining contract clauses. Extract from a conversation with OpenAI’s GPT-3,
accessed via the ChatGPT interface (May 24, 2023 version).
34. “Transforming Work and Creativity with AI,” OpenAI. Accessed February 5, 2024. https://openai.com/product;
Abdullah Malak, Alia Madain, and Yaser Jarahweh, “ChatGPT: Fundamentals, Applications and Social Impacts,” in
2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS), Milan, Italy
(Piscataway, NJ, USA: IEEE, 2022), 1–8. https://ieeexplore.ieee.org/document/10062688.
35. “Welcome to the OpenAI Platform,” OpenAI. Accessed February 5, 2024. https://platform.openai.com/overview.
36. Jianyang Deng and Yijia Lin, “The Benefits and Challenges of ChatGPT: An Overview,” Frontiers in Computing and
Intelligent Systems 2, no. 2 (2022): 81–83. https://doi.org/10.54097/fcis.v2i2.4465.
Autto et al. 11
Figure 5. ChatGPT suggesting a layered layout and FAQ-style headings for previously generated content.
Extract from a conversation with OpenAI’s GPT-3, accessed via the ChatGPT interface (May 24, 2023
version).
12 Journal of Strategic Contracting and Negotiation 0(0)
the human brain and neurons work. An algorithm37 is a small software procedure containing a finite
sequence of rigorous instructions to perform data processing simplified into a form of computational
problem.
ChatGPT (and similar applications) can be categorized as autoregressive, multimodal, genera-
tive, and large language models.38 Autoregressive means that the application produces content,
for example, text, based on previous observations of how words are related together in the large
amount of data on which it has been trained.39 Multimodal refers to the ability to produce a
variety of content, including text, audio, tables, images, and code. Generative means that the appli-
cation can create content. A large language model means that the application has been trained on a
large amount of data and is capable of bi-directional natural language processing; both receiving
and producing.40 Although large language models are very powerful, it is important to note that
there are several limitations related to their capabilities and that there are many risks associated
with their use, not only due to the data on which they have been trained,41 but also due to their
limited trustworthiness.42 This needs to be taken into account when applying generative AI such
as ChatGPT to the world of contracts.
3.2.2 Content design. By content design, we mean the design of the content—the actual substance
—of contracts. This includes both commercial terms, which may be technical, financial, or oper-
ational, and legal terms. These all vary from context to context and are influenced by the
purpose and type of the contract, the objectives of the parties, their roles, rights, and obligations,
and the legal framework. Put simply, in our context, content design is about “what to say,” as
opposed to presentation design, which is about “how to say it” in a contract.
Our first experiment43 was to see how ChatGPT could help with content creation. We asked it to
suggest topics that contracting parties should pay attention to and agree on in light of the proposed
Ecodesign Regulation that will replace and expand the scope of the existing Ecodesign Directive.
Our goal was to test ChatGPT’s ability to search for information and to identify and suggest reliable
and relevant content from a variety of sources.
37. Charles L. Forgy, “Rete: A Fast Algorithm for the Many Pattern/Many Object Pattern Match Problem,” Artificial
Intelligence 19, no. 1 (September 1982): 17–37. https://doi.org/10.1016/0004-3702(82)90020-0.
38. Deng and Lin, “The Benefits and Challenges of ChatGPT.”
39. Dieuwertje Luitse and Wiebke Denkena, “The Great Transformer: Examining the Role of Large Language Models in
the Political Economy of AI,” Big Data & Society 8, no. 2 (July 2021): 1–14. https://doi.org/10.1177/20539517211047734.
40. Luitse and Denkena, “The Great Transformer”; Malak, Madain, and Jarahweh, “ChatGPT: Fundamentals,
Applications and Social Impacts.”
41. Malak, Madain, and Jarahweh, “ChatGPT”; Charles Yu, Sullam Jeoung, Anish Kasi, Pengfei Yu, and Heng Ji,
“Unlearning Bias in Language Models by Partitioning Gradients,” in Findings of the 61st Annual Meeting of the
Association for Computational Linguistics (ACL 2023), July 9–14, 2023 (Association for Computational Linguistics,
2023), 6032–48. https://aclanthology.org/2023.findings-acl.375.pdf.
42. Luitse and Denkena, “The Great Transformer”; Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang,
Chenhui Zhang, Chejian Xu, et al. “DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPTModels.” June
20, 2023. https://arxiv.org/pdf/2306.11698.
43. The full texts of our conversations with ChatGPT in June and July 2023, labeled by ChatGPT as “Contracting Parties’
Ecodesign Concerns” and “Eco Contracts: Product Sustainability” are on file with the authors. The AI-generated responses
were provided by OpenAI’s GPT-4 model for Figure 2 and GPT-3 model for Figures 3–5, accessed through the ChatGPT
interface. At the time of our first experiment, GPT-4 had access to a browser and Bing (beta). Due to space limitations, we
only show extracts from our conversations in Figures 2–5.
Autto et al. 13
We first tasked ChatGPT, equipped with browsing functionality, with searching for information
related to existing and proposed EU ecodesign legislation. The experiment focused on ChatGPT’s
ability to navigate through different types of sources, including official EU databases, to ensure a
wide range of information. We then observed how it approached these queries, where it looked for
information and its effectiveness in selecting sources. Emphasis was placed on ChatGPT’s ability to
identify and prioritize sources that were authoritative and relevant to the context. ChatGPT demon-
strated a remarkable ability to identify a range of sources and to effectively filter and suggest content
that was closely aligned with our experimental goals.
These suggestions give the person responsible for preparing a contract a good starting point for
planning its content. As shown in Figure 2, ChatGPT’s suggestions included references: the official
website of the European Union44 on ecodesign for sustainable products, and the website of the law
firm Bird & Bird45 describing their insights into the proposed new Regulation.
Rob Waller, a pioneer of information design, has identified criteria for good documents. For
content, he has identified four: relevance, subject, action, and alignment: how relevant the
content is to the recipient; whether it is clear what the communication is about; what action is
required of the user; and consistency with the organization’s intended goals and values.46
Waller’s four criteria have also been applied to contracts.47
Measured against Waller’s criteria, the content provided by ChatGPT seems to succeed—it is
what we asked for. It should be relevant in that it indicates (as we asked) topics that the contracting
parties should pay attention to and agree on. It gives a quick overview of the proposed EU legisla-
tion which is not easy to read. Obviously, the contract designer would need to dig deeper and find
out more details—here the references could be helpful as far as new legal requirements are con-
cerned. ChatGPT’s text does not contain irrelevant material: it gets to the point. It also clearly
states the subject and purpose of the communication (“… here are some key points that Parties
should note and agree on”). However, for someone new to the field, the vocabulary may not
mean much and it may not be clear what the requirements are, what actions are required of the
parties, let alone which party is responsible for what: more information is needed to translate the
text into actionable contract terms and specifications. Which brings us to our next experiment:
how might ChatGPT help us to create actual contract language and clauses?
3.2.3 Language design. Our second experiment builds on and goes beyond the first: from the initial
ideation to the actual suggestion of a first draft of contract clauses. We continued our earlier discus-
sion with ChatGPT regarding the proposed Ecodesign Regulation and asked ChatGPT to suggest
contract clauses. In a matter of seconds, it generated four clauses, covering the topics it had
listed in our first experiment: 1. Expanded Scope of Product Groups; 2. Sustainable and Circular
Products; 3. Right to Repair; and 4. Digital Product Passport. Figure 3 shows an unedited extract
from the outcome of our conversation, items 2 and 3 on the list of topics suggested by ChatGPT.
44. “Ecodesign for Sustainable Products,” European Commission.
45. Lisette den Butter, Nina Dorenbosch, and Sander Wagemakers, “The New Right to Repair and EcoDesign Rules in
the EU.” Accessed July 4, 2023. https://www.twobirds.com/en/insights/2023/global/the-new-right-to-repair-and-ecodesign-
rules.
46. Rob Waller, “What Makes a Good Document? The Criteria We Use.” Simplification Centre Technical Paper 2, April
2011, 5.
47. See, e.g., Haapio, Next Generation Contracts, 59.
14 Journal of Strategic Contracting and Negotiation 0(0)
ChatGPT’s suggestions can make it easier to get started without having to start from scratch.
Depending on the context and the organizational goals and values, it can be used as a first draft
by the contract designer, for review by subject matter experts and for further development. In
terms of content, we found that the clauses proposed by ChatGPT were rather one-sided in favor
of the buyer, with obligations only binding the supplier—no obligations binding the buyer, and
no shared responsibilities.48 If the contract drafter was working on the buy side, this might be
normal—but working for the sell side, would not be desirable.
Figure 6. Conceptual model of an artificial intelligence (AI)-assisted contract design process. © 2024 The
Authors.
48. For shared responsibility contracting, see, e.g., “Contractual Clauses Project,” American Bar Association. Accessed
July 7, 2023. https://www.americanbar.org/groups/human_rights/business-human-rights-initiative/contractual-clauses-
project/. See also David Snyder, Susan Maslow, and Sarah Dadush, “Balancing Buyer and Supplier Responsibilities:
Model Contract Clauses to Protect Workers in International Supply Chains, Version 2.0,” The Business Lawyer 77, no. 1
(2021): 115–82.
Autto et al. 15
In terms of language, we found ChatGPT’s proposal rather jargony and not very user-friendly.
So, we continued our experiment by asking ChatGPT if it could explain these two clauses in ordin-
ary language to an engineer responsible for developing new products and product information.
Figure 4 shows the output.
In this experiment, ChatGPT successfully explained some of the jargon in a clearer language that
should be understandable to a wider audience. It explained the meaning and background of the text
and gave instructions to the engineer directly, addressing the engineer as “you.” It improved the
sentence structure and did not use expressions such as “shall.” This should make it easier for the
intended reader to understand the content. In many ways, this text meets Waller’s criteria for
good documents better than the earlier version. Obviously, this is only the beginning, as the engin-
eer needs to know more about the requirements for the products and related information and how to
design them to meet regulatory ecodesign requirements.
Language models such as ChatGPT have already revolutionized language processing by gener-
ating human-like text. There are also other AI-assisted applications that can be used as language
tools for contract designers, such as DeepL Translate or Google Translate. ChatGPT, too, can trans-
late between languages—and translate legalese to understandable language. In addition, it can sum-
marize, paraphrase, refine, and structure language. DeepL49 can be used to translate from one
language to another using the Translation feature, as well as to improve spelling using the
Write50 feature. Whole files can be translated with DeepL Translate. Google Translate can not
only translate text from one language to another, it can also pronounce written text and translate
web pages directly.
3.2.4 Presentation (layout and structure) design. We then moved from content and language—what
is said—to presentation: how it is said. Layout and structure play an important role in presentation.
Layout refers to organizing the content so that it is easy to find, read, and understand. A well-
executed layout expresses at a glance the content, the hierarchy of the content, and its overall
order. This makes it easy for readers to find the information they need, understand what they
find, and use that information.51 Contracts are typically dense with information, and it is often
necessary to extract only parts of them for reading, so the layout should be designed to support stra-
tegic reading. TheWorldCC Contract Design Pattern Library, for example, provides a range of tools
to support strategic reading.52
The WorldCC Contract Design Pattern Library goes beyond tools and guidance by incorp-
orating real-world examples from various companies. This is particularly evident in the layout
and layering sections. Companies such as Airbus and Shell have provided practical examples of
how they have successfully implemented these patterns in their contract designs. By showcas-
ing these real-world applications, the Library not only provides a resource for learning and
inspiration, but also demonstrates the tangible impact of these patterns in the business world.
49. “DeepL Translate: The World’s Most Accurate Translator,” DeepL. Accessed June 15, 2023. https://www.DeepL.
com/translator.
50. “DeepL Write: AI-Powered Writing Companion,” DeepL. Accessed June 15, 2023. https://www.DeepL.com/write
51. This is in line with the definition of plain language by the International Plain Language Federation and the new ISO
standard on plain language; see Section 3.1 above.
52. WorldCC, Stefania Passera, and Helena Haapio, “Layout.” Contract Design Pattern Library, WorldCC Foundation.
Accessed June 15, 2023. http://contract-design.worldcc.com/library/layout.
16 Journal of Strategic Contracting and Negotiation 0(0)
Layering is an approach to presenting information in a way that gives more relevance to key
points and less to extraneous details. This approach creates a hierarchy of information that helps
readers avoid information overload. It makes it easy to find the important information and allows
the reader to skip the extraneous details if necessary. This approach also works for a more motivated
reader who can read the details.53 The different layers for different reader needs might include: (a)
an action layer for quick skim reading; (b) an explanation layer for a deeper understanding, contain-
ing clear text written from the user’s perspective; and (c) the full text.54
The Creative Commons (CC) licensing system is an early example of a layered layout. CC pro-
vides standardized copyright licenses with three layers of information: a human-readable summary
with plain language and icons, the full text of the license, a lawyer-readable “legal code,” and a
machine-readable version. “Taken together, these three layers of licenses ensure that the spectrum
of rights isn’t just a legal concept. It’s something that the creators of works can understand, their
users can understand, and even the Web itself can understand.”55
Structure is an important part of contract design, especially if the aim is to avoid the
wall-of-text effect. Organizing patterns helps to structure content so that it is logical, meaningful,
and relevant to the readers. They help to organize and present information in a way that maxi-
mizes clarity and comprehension. Organizing patterns can help contract designers make the
core content and meaning of the contract visible so that people who read strategically can find
the answers they need. These patterns can be used to illustrate how different parts relate to
each other, or in which document(s) or clause(s) particular content is presented. They can also
be used to clarify what is and is not part of the contract. Examples of organizing patterns
include accordion (used online), icon system, tables, and skimmable headings.56 FAQ-style skim-
mable headings allow the reader to move quickly through a document to understand its structure
and access its content. To work well as a layered explanation, there should be one for each clause
or paragraph.57
AI can also help with layout design and layering. Some research and testing has already been
done in this area. Corrales Compagnucci, Fenwick, and Haapio present an example of using a
GPT-3-generated explanation and merging it with the layering approach. The authors envision
“a future where computable language models such as GPT-3 will enable and empower both contract
readers and writers, allowing writers to provide their readers—whether humans or machines—with a
new genre of operationally and legally functional and understandable contracts.”58
In our final experiment, we asked ChatGPT to suggest a contract clause in which the information
it had generated in our previous experiments was presented in a layered layout format, with the
53. WorldCC, Stefania Passera, and Helena Haapio, “Layering.” Contract Design Pattern Library, WorldCC Foundation.
Accessed June 15, 2023. http://contract-design.worldcc.com/library/layering.
54. Marcelo Corrales Compagnucci, Mark Fenwick, and Helena Haapio, “Digital Technology, Future Lawyers and the
Computable Contract Designer of Tomorrow,” in Research Handbook on Contract Design, eds. Marcelo Corrales
Compagnucci, Helena Haapio, and Mark Fenwick (Cheltenham: Edward Elgar, 2022), 421–44.
55. “About the Licenses”, Creative Commons. Accessed July 6, 2023. https://creativecommons.org/about/
56. WorldCC, Stefania Passera, and Helena Haapio, “Organizing.” Contract Design Pattern Library, WorldCC
Foundation. Accessed June 15, 2023. http://contract-design.worldcc.com/library/organizing.
57. WorldCC, Stefania Passera, and Helena Haapio, “Skimmable Headings.” Contract Design Pattern Library, WorldCC
Foundation. Accessed June 15, 2023. http://contract-design.worldcc.com/skimmable-headings.
58. Compagnucci, Fenwick, and Haapio, “Digital Technology,” 433.
Autto et al. 17
original clause text in the right-hand column, the explanation in the middle, and related FAQ-style
headings in the left-hand column. Figure 5 shows the outcome.
This experiment was about both content and how content is presented. The experiment was suc-
cessful: ChatGPT produced the content and implemented the requested presentation, a layered
layout that included not only the full text and its explanation, but also FAQ-style headings that it
was able to generate based on the earlier conversations. The different sections were separated by
columns. For the FAQ-style headings, ChatGPT suggested “What does the clause on
‘Sustainable and Circular Products’ imply?” and “What is meant by ‘Right to Repair’ in the con-
tract?” The Explanation section contains the human-friendly version of the contract clause gener-
ated earlier in our third experiment and the Original Clause Text section contains the full text
generated in our second experiment.
This conversation shows that ChatGPT is able to pick up ingredients for its output from previous
sessions. This experiment also shows that ChatGPT is capable of producing elements other than
text, including tables, columns, and bolding. The entire output can be copied into a word processor,
so that the contract designer can easily continue work and add other desired elements, such as
visuals, which we excluded from our experiments but plan to explore later.59
3.3 Conceptualizing our findings
Our experiment described above is practice-oriented, exploring the possibilities of an AI assistant in
contract design. As our theoretical contribution, we present a conceptual model of an AI-assisted
contract design process that serves as a generalization of our findings for different contexts. The
conceptual model is illustrated in Figure 6.
The contract design process starts within the business and legal context, reflecting the legal require-
ments and business objectives for the particular contractual arrangement. The design process (with or
without AI) is iterative and often includes several design cycles. The cycles typically include stakeholder
reviews to ensure the legal and business relevance of the designed contract. Generative AI can be used
by the human contract designer in multiple tasks through interactive sessions with the AI: contextual-
izing the contract in the legal framework, gaining more information on the topic, and optimizing the
content, language, and presentation of the contract. Based on our research, these tasks can be performed
with generative AI regardless of the context of the contract. Next, we discuss the future potentials and
risks of AI-assisted contract design.
3.4 Potentials, risks, and pitfalls of AI-assisted contract design
Our experiments focused on identifying and filtering sources for and generating ideas, suggestions,
and first drafts of contract clauses. We found that ChatGPT can suggest contract topics, content, and
language as well as navigation and organization aids (using different font sizes, boldface, FAQ-style
59. We recognize the existence of potential challenges related to issues such as copying and plagiarism when using
AI-based tools such as ChatGPT in this context. Future research should focus on developing guidelines and best practices
for the ethical and responsible use of AI in contract design. However, we think it is important to recognize that lawyers
already engage in a form of copying and plagiarism without a language model, as they often copy templates, forms, or
other pre-existing work in a manner similar to adopting the output of a language model, as this article states: Michael
L. Smith, “Language Models, Plagiarism, and Legal Writing,” University of New Hampshire Law Review 22, no. 2
(2024): 361–91.
18 Journal of Strategic Contracting and Negotiation 0(0)
headings) and layering (using skimmable headings, explanations, and text in a layered layout). In
this way, ChatGPT can help us break out of old templates by giving us ideas on what the contract
could say and how it could be presented.
We discovered the same thing as many other ChatGPT users: engineering (or designing) a
well-working prompt is a prerequisite for using AI tools successfully. The more carefully
one thinks through the prompt, with the desired outcome in mind, the better the AI tool will
produce. For example, if we want columns and text in them, it is a good idea to express precisely
what we want in each column. If the prompt is carefully crafted, ChatGPT can be a great help in
a variety of ways, including brainstorming and contract drafting. It is important to emphasize
the usefulness of ChatGPT specifically as an assistant to the contract designer, rather than as
a stand-alone tool. ChatGPT output should always be reviewed and verified by a qualified
professional.
Based on our findings, we can highly recommend using ChatGPT as a contract design assistant,
but under close human supervision. By default, it interacts with its users in a conversational way,
which is a good starting point. However, there are also some factors that undermine its usefulness
and raise serious concerns.
Because large language models are trained on massive amounts of data, they are biased by the
content and language used in their training data.60 If they are trained on the most common contracts,
which contain one-sided clauses and are written in legalese, they will reflect that. When asked to
suggest contract clauses in our experiment, ChatGPT automatically started to produce typical
legal language, even though it was otherwise good at colloquial speech. In order to get it to help
simplify contracts or move from unilateral contracts to shared responsibility, it needs to be specif-
ically prompted to do so.
We experienced a few other setbacks during our research. In the middle of our experiments,
OpenAI disabled the Browse with Bing beta feature, stating that this was done “out of an abundance
of caution while we fix this in order to do right by content owners.” Now OpenAI has re-enabled
Browse, which is essential for contract designers to create and review content. Hopefully, format-
ting slowdowns such as the GPT-4 limit of 25 messages every 3 h will soon be removed; this cur-
rently slows down the use of ChatGPT as a contract design assistant.
ChatGPT and generative AI in general have other risks and limitations. ChatGPT is known for
generating incorrect answers sometimes.61 It does not ask clarifying questions when the user pro-
vides an ambiguous query, but simply guesses what the user intended.62 It may also respond to
60. For example, Partha Pratim Ray, “ChatGPT: A Comprehensive Review on Background, Applications, Key
Challenges, Bias, Ethics, Limitations and Future Scope,” Internet of Things and Cyber-Physical Systems 3 (2023): 121–
54, https://doi.org/10.1016/j.iotcps.2023.04.003; Wang et al., “DecodingTrust.”
61. For example, Sara Merken, “New York Lawyers Sanctioned for Using Fake ChatGPT Cases in Legal Brief.” Reuters,
June 26, 2023. https://www.reuters.com/legal/new-york-lawyers-sanctioned-using-fake-chatgpt-cases-legal-brief-2023-06-
22/; Bor Gregorcic and Ann-Marie Pendrill, “ChatGPT and the Frustrated Sokrates,” Physics Education 58, no. 3 (2023):
article 035021, https://doi.org/10.1088/1361-6552/acc299; Konstantinos C. Siontis, Zachi I. Attia, Samuel J. Asirvatham,
and Paul A. Friedman, “ChatGPT Hallucinating: Can It Get Any More Humanlike?” European Heart Journal 45, no. 5
(2024): 321–23. https://doi.org/10.1093/eurheartj/ehad766.
62. For example, Adam Hulman, Ole Lindgård Dollerup, Jesper Friis Mortensen, Matthew E. Fenech, Kasper Norman,
Henrik Støvring, and Troels Krarup Hansen, “ChatGPT- Versus Human-Generated Answers to Frequently Asked Questions
About Diabetes: A Turing Test-Inspired Survey Among Employees of a Danish Diabetes Center,” PLoS ONE 18, no. 8
(2023): article e0290773. https://doi.org/10.1371/journal.pone.0290773; Malak, Madain, and Jarahweh, “ChatGPT.”
Autto et al. 19
harmful instructions or give inaccurate or biased answers.63 These affect its usability as a contract
design assistant. ChatGPT is not free from the biases of existing contracts, so it may suggest clauses that
only work to the advantage of one party (and thus do not represent a proactive, shared-responsibility
approach favored in this article).
According to a recent WorldCC report, the quality of data output is not the biggest barrier to the
adoption of AI in organizations’ contracting processes: security and privacy are.64 AI tool vendors,
including OpenAI, are aware of this and are actively working to improve the privacy and security
of their offerings. On its Security & privacy page, 65 OpenAI states that it complies with the
General Data Protection Regulation (GDPR)66 and the California Consumer Privacy Act,67
adding that OpenAI can execute a Data Processing Agreement if the user’s organization or use
case requires it.68
In the context of contract design projects, one of the biggest concerns is the handling of sensitive
information, such as trade secrets such as customer data, and the issue of confidentiality.69 For
example, OpenAI’s terms of use70 do not secure the confidentiality of user input.71 However,
after investing $1 billion in OpenAI, Microsoft is now moving quickly to integrate ChatGPT and
other AI products into Microsoft Azure Cloud Computing Services.72 This will improve the
current situation for the users of Azure OpenAI services: these are run in a customer-specific
63. These are also recognized by OpenAI, see, for example, “Introducing ChatGPT,” OpenAI, https://openai.com/blog/
chatgpt. At the end of each conversation, the user is reminded of the fact that ChatGPT may produce inaccurate information
about people, places, or facts.
64. WorldCC, “AI in Contracting: An Untapped Revolution. Insights from the Global Contracting Community.” July
2023. https://www.worldcc.com/Portals/IACCM/Resources/11556_0_AI%20in%20contracting%20an%20untapped%
20revolution.pdf.
65. “Security & Privacy,” OpenAI. Accessed February 4, 2024. https://openai.com/security.
66. European Parliament and Council. Regulation (EU) 2016/679 of the European Parliament and of the Council of 27
April 2016 on the Protection of Natural Persons with Regard to the Processing of Personal Data and on the Free Movement of
Such Data, and Repealing Directive 95/46/EC (General Data Protection Regulation GDPR) [2016] OJ L119/1.
67. California Consumer Privacy Act of 2018, Cal. Civ. Code §§ 1798.100 et seq., https://leginfo.legislature.ca.gov/faces/
codes_displayText.xhtml?division=3.&part=4.&lawCode=CIV&title=1.81.5.
68. For OpenAI’s Data Processing Addendum (DPA) regarding personal data that a customer provides to OpenAI and
that OpenAI processes on behalf of the customer (the controller), see “Data Processing Addendum,” OpenAI, January 12,
2024, https://openai.com/policies/data-processing-addendum. For the data protection impact assessment required by
Article 35 of the GDPR, see Fabienne Ufert, “AI Regulation Through the Lens of Fundamental Right: How Well Does
the GDPR Address the Challenges Posed by AI?” European Papers – A Journal on Law and Integration 5, no. 2 (2020):
1087–97. http://doi.org/10.15166/2499-8249/394.
69. Bernd Fiten and Geert Somers, “AI-Based Legal Tech Solutions: Discover the Legal Pitfalls.” Timelex (blog).
February 20, 2023. https://www.timelex.eu/en/blog/ai-based-legal-tech-solutions-discover-legal-pitfalls; Anirudh Gotety,
“Regulating the Ethics of the Unknown: Analysing Regulatory Regimes for AI-Based Legal Technology and
Recommendations for Its Regulation in India.” NUJS Law Review 14, no. 3 (2021): 335–59.
70. “Europe Terms of Use,” OpenAI, November 14, 2023, https://openai.com/policies/eu-terms-of-use/. See under
Content: “We can use your Content worldwide to provide, maintain, develop, and improve our services, comply with
applicable law, enforce our terms and policies and keep our services safe.”
71. Skye Witley, “ChatGPT Tempts Big Law Despite AI Accuracy, Privacy Worries (2).” Bloomberg Law. Accessed
July 4, 2023. https://news.bloomberglaw.com/privacy-and-data-security/chatgpt-tempts-big-law-despite-ai-accuracy-data-
privacy-worries.
72. “What Is Azure OpenAI Service?—Azure Cognitive Services,” Microsoft. Accessed June 28, 2023. https://learn.
microsoft.com/en-us/azure/cognitive-services/openai/overview.
20 Journal of Strategic Contracting and Negotiation 0(0)
virtual space and the data is not available to third parties.73 The approach is similar to how emails,
files, and other data are stored when using outsourced cloud services. This approach of dedicated
virtual spaces seems to be the current market trend. Other major players, including Amazon74
and Google,75 have also announced the availability of a similar implementation. The use of genera-
tive AI in the secure cloud space will remove many concerns related to sensitive information and
enable efficient operations in contract design. In this case, AI is used within the organizational
boundaries of the using party, which also makes it easier to comply with data protection laws.
There is an emerging debate on the role of intellectual property rights in the process of training
AI and generative AI products.76 Most generative AI products are trained on publicly available data
from the Internet, including also copyrighted content.77 For this reason, the generated output of AI
may in some cases produce content that, if used, will lead to copyright infringement.78 Contract
designers need to be aware of this risk and consider it carefully when using the output.
In the EU, many of the risks related to privacy79 and other concerns of generative AI are
addressed in the recently agreed upon AI Act80. For example, privacy risks related to data crawlers
and scrapers81 are recognized as well as the commercialization of private data without consent on
social media.82 The European Parliament’s position,83 adopted in June 2023, includes so-called
foundation models in the Act. It imposes specific obligations on providers of generative AI, with
the aim of ensuring transparency and preventing the generation of illegal or infringing content.
Providers of these models are responsible for ensuring the protection of fundamental rights,
health and safety, and the environment. They are also required to assess and mitigate risks,
73. “Data, Privacy, and Security for Azure OpenAI Service – Azure Cognitive Services,”Microsoft. Accessed June 23,
2023. https://learn.microsoft.com/en-us/legal/cognitive-services/openai/data-privacy.
74. “Generative AI—Use Cases and Solutions—AWS,” Amazon. Accessed July 4, 2023. https://aws.amazon.com/
generative-ai/.
75. James Vincent, “Google Opens up Its AI Language Model PaLM to Challenge OpenAI and GPT-3,” The Verge,
March 14, 2023. https://www.theverge.com/2023/3/14/23639313/google-ai-language-model-palm-api-challenge-openai;
“How Google Cloud Plans to Supercharge Security with Generative AI,” Google. Accessed July 4, 2023. https://cloud.
google.com/blog/products/identity-security/rsa-google-cloud-security-ai-workbench-generative-ai.
76. Alain Strowel, “ChatGPT and Generative AI Tools: Theft of Intellectual Labor?” IIC – International Review of
Intellectual Property and Competition Law 54, no. 4 (April 2023): 491–94. https://doi.org/10.1007/s40319-023-01321-y.
77. Jessica L. Gillotte, “Copyright Infringement in AI-Generated Artworks,” UC Davis Law Review 53, no. 5 (June
2020): 2655–91; Jenny Quang, “Does Training AI Violate Copyright Law?” Berkeley Technology Law Journal 36, no. 4
(2021): 1407–35.
78. Matthew Sag, “Copyright Safety for Generative AI,” Houston Law Review 61, no. 2 (2023): 295–347.
79. Rossana Ducato and Alain Strowel, “Limitations to Text and Data Mining and Consumer Empowerment: Making the
Case for a Right to Machine Legibility,” IIC – International Review of Intellectual Property and Competition Law 50, no. 6
(2019): 649–84.
80. European Commission, “Proposal for a Regulation of the European Parliament and of the Council Laying Down
Harmonised Rules on Artificial Intelligence (Artificial Intelligence Act) and Amending Certain Union Legislative Acts.”
COM(2021) 206 final, April 21, 2021.
81. Ducato and Strowel, “Limitations to Text and Data Mining and Consumer Empowerment.”
82. Norwegian Consumer Council, “Ghost in the Machine: Addressing the Consumer Harms of Generative.” June 2023.
https://storage02.forbrukerradet.no/media/2023/06/generative-ai-rapport-2023.pdf.
83. European Parliament, Committee on the Internal Market and Consumer Protection and Committee on Civil Liberties,
Justice and Home Affairs, “Draft Compromise Amendments on the Draft Report Proposal for a regulation of the European
Parliament and of the Council on harmonised rules on Artificial Intelligence (Artificial Intelligence Act) and amending
certain Union Legislative Acts.” COM(2021)0206—C9 0146/2021–2021/0106(COD), rapporteurs: Brando Benifei and
Ioan-Dragoş Tudorache. May 9, 2023.
Autto et al. 21
comply with design and information standards, and register with the EU database. In this way, the
AI Act aims to make generative AI more accurate and safer and to foster an environment in which
AI tools can be used responsibly and effectively. However, the role of users remains crucial.
4. Conclusions
Experience and research, including studies by WorldCC, have highlighted the need for a new way
of thinking about contracts. It is time to move away from seeing them as a mere formality, contain-
ing over-legalistic terms and dense legal jargon—time to focus more on the business and commer-
cial terms at their heart. Elements such as scope and goals, specifications, delivery, and acceptance
should be at the forefront, defining the operational relationship between the parties. But we should
not stop there. With the increasing global focus on ESG and sustainability, related objectives and
commitments should also be included and clearly communicated in our contracts.
When contracts are rethought, it becomes clear that they need to be redesigned. Redesigned con-
tracts, in turn, open up a possible new way to change mindsets, refocus and reframe contract
content, and improve the operational functionality and usability of contracts. In this exploratory
article, we investigate the potential of generative AI tools to improve contracts and facilitate the
generation of their content, language, structure, and presentation.84 We use the example of the pro-
posed new EU Regulation on Ecodesign for Sustainable Products, which will require many orga-
nizations to review their contracting practices and possibly develop new contract content without
the help of existing templates or models.
We hope that the practical applications of AI, together with observations from our AI experi-
ments, will provide inspiration and insight into the possibilities of using AI in contract design.
While recognizing the opportunities and benefits, we have also highlighted the importance of
addressing the challenges and ethical considerations involved. Those using these AI tools should
be aware of their limitations: the tools need to be used responsibly, and their outputs need to be
reviewed by a qualified professional. In our experiments, some of ChatGPT’s suggestions
proved to be affected by biases such as one-sided contract terms and the legalistic language
typical of traditional contracts. However, these can be overcome by human oversight.
Richard Susskind, Professor Emeritus of Law, who has been studying AI and the law since
the 1980s, recently said that ChatGPT is the most remarkable development he has seen in AI in
over 40 years.85 Like him, we see the future of generative AI in law and contracts as very prom-
ising, especially as these tools undoubtedly evolve and become more powerful and accurate.
When they do, we believe they will revolutionize the creation and design of contracts, stream-
lining the process and ensuring legal soundness. We share Professor Susskind’s view that AI’s
greatest potential lies in dispute avoidance.86 But we also see a proactive, promotive dimension,
where generative AI can be used not only to prevent the causes of problems from arising, but
also to promote what is desirable and to help parties find and stay on the “happy path.”
84. The four categories of content, language, structure, and presentation are not our own. We are indebted to Rob Waller
and the Simplification Centre, who have used similar criteria in several reports available at https://www.simplificationcentre.
org.uk/resources/technical-papers.
85. Richard Susskind, “AI in the Law—Six Thoughts,” LinkedIn, July 5, 2023. https://www.linkedin.com/pulse/ai-law-
six-thoughts-richard-susskind.
86. Susskind, “AI in the Law.”
22 Journal of Strategic Contracting and Negotiation 0(0)
However, as we move toward this future, ethical and legal issues such as privacy and confiden-
tiality will need to be addressed.
Overall, our results from the experiments are promising and argue for further exploration of
ChatGPT in contract design, both in terms of content and presentation. While further research
and solutions are needed to protect sensitive information and third-party rights, we are confident
that harnessing the power of AI-assisted contract design will spearhead the development of more
efficient, transparent, and sustainable contracts. Such innovation promises not only improved busi-
ness outcomes, but also a more positive societal impact.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/
or publication of this article.
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or
publication of this article: This work was supported by the Research Council of Finland, (grant
number 332819).
ORCID iDs
Hilja Autto https://orcid.org/0000-0001-9466-6054
Helena Haapio https://orcid.org/0000-0001-5452-9872
Jouko Nuottila https://orcid.org/0000-0002-9348-2584
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