Does your organization have multiple long-term contracts running at the moment? Are the associated business partners scattered across different countries, cities, and jurisdictions?

If you answered “yes” to either or both questions, then you probably relate to the challenges in-house counsel face managing multiple long-term contracts at the local, national, and international scale.

Contracts of this nature are constantly exposed to variable factors such as changes in compliance requirements and performance fluctuations, which can significantly impact the profitability of your organization’s engagements.

To stay on top of these emerging situations, in-house counsel and other contract-facing teams must learn to leverage robust mechanisms like AI-powered predictive analytics.

In this post, we’ve covered everything you must know about AI-based predictive analytics, from how it can future-proof your contracts to how you can get the best results with it.

Keeping up with the dynamic business landscape: The cons of traditional methods

The business ecosystem is hardly ever stagnant. It is constantly changing in response to new market conditions, regulatory updates, technology advancements, and socio-economic variables.

This calls for heightened awareness among contract-facing teams, as failing to keep track of the ever-evolving business landscape can result in missed opportunities, inadvertent non-compliance, and unenforceable provisions, all of which have negative business and legal implications.

Future-proofing contracts involves anticipating these changes and implementing proactive measures to keep agreements agile and resilient.

However, keeping up with constantly changing regulatory and market conditions is a tedious process, much more tedious than traditional methods can handle.

#1 Manual efforts and legacy systems

Traditional methods rely on manual efforts and outdated systems, which are significantly limited in bandwidth and scalability. 

Managing an extensive portfolio of contracts using traditional methods is inherently tough and inefficient. Add regulatory updates, changing market conditions, and the need to implement timely post-execution changes, and your role as a Contract Manager becomes exponentially more complicated.

 #2 Siloed documents

Traditionally managed contracts often reside in disparate silos such as file cabinets, email inboxes, or scattered within hard drives. This makes it nearly impossible to maintain a holistic view of all contractual obligations, as there's no central repository and effective version control.

This lack of visibility makes identifying potential risks, tracking compliance, or finding clauses you need to update incredibly difficult.

Also read: Contract Repository—Everything you Need to Know

#3 Weak analytics

The absence of robust reporting and analytics capabilities poses another severe challenge. Without access to up-to-date data and insights, it becomes hard to proactively manage risk, optimize contract performance, or justify contract management decisions to key stakeholders.

This inability to extract valuable insights from contracts limits contract-facing teams from making proactive, data-driven decisions and maximizing the value of their contract portfolios.

Also read: AI Contract Analysis—Saving Time and Increasing Efficiency

Understanding predictive analytics with AI

Predictive analytics is the use of historical data to uncover trends, define relationships between past events, and make predictions on future occurrences.

This is one of the most fascinating capabilities of AI, especially in contract management processes. In this case, machine learning algorithms learn about outcomes and driving factors of past contracts, identifying patterns and connections to prevailing market conditions and regulatory dynamics.

Then, they deliver insights on potential risks, performance outcomes, and implications of certain decisions based on information derived from historical contracts.

Imagine a manufacturing company negotiating a supply contract for a crucial component, such as semiconductors, steel, or other raw materials. AI-powered predictive analytics could:

• Analyze historical data on similar component supplies to highlight potential price fluctuations, delivery disruptions, and quality control issues.
• Assess the supplier's financial health and past performance to signal any risk of default.
• Identify compliance standards that may have impacted the outcomes of similar contracts, highlighting any changes such regulations may have gone through.
• Offer data-backed recommendations for clauses mitigating risk and ensuring timely delivery at the best price.

Through AI-driven predictive analytics, contract-facing teams can execute resilient agreements that protect their organizations against emerging risks and retain their profitability in the face of changing market dynamics.

Fingers on the pulse: How AI creates resilient contracting strategies through predictive analytics

“Artificial Intelligence just may well be the final frontier in terms of how legal services are utilized and provided.  As in-house counsel, don’t run away from it and don’t ignore it.  Rather, embrace it as, ultimately, it will allow you to do thing things lawyers love to do: thinking, analyzing, and counseling, while leaving the “grunt” work to the computer.”‍

~Sterling Miller, CEO and Senior Counsel for Hilgers Graben PLLC
Ten Things: Artificial Intelligence—What Every Legal Department Really Needs to Know

In a business world prone to disruptions, AI-based predictive analytics can be your game-changer, helping you prepar against potential incidents and future-proofing your legal agreements.

There are several ways it can do this. However, we’ll cover some of the most critical instances.

#1 Risk identification and mitigation

“Over the past five years or so, one of the key responsibilities businesses are placing on in-house lawyers is spotting and managing risk. The business wants its in-house lawyers to be the ones who sniff through virtually every situation looking for risk (legal or otherwise).”

~Sterling Miller, CEO and Senior Counsel, Hilgers Graben PLLC
Ten Things: Spotting, Analyzing, and Managing “Risk”

Thanks to its ability to scan large amounts of contract data, AI can identify market trends, supplier performance records, and patterns in the regulatory landscape.

This allows it to identify risk factors that might escape human notice, such as problematic clauses, ambiguous language, or emerging regulatory changes that could impact a contract's validity. 

With these insights, legal teams can proactively mitigate risks, either through adjustments during the contract formation stage or by incorporating safeguard mechanisms within the contract itself.

Also read: Legal Risk Management—From the Playbook of 11 GCs & Leaders

#2 Compliance monitoring

“Owing to our operations in multiple geographies, a lot of work our team gets is on the lines of contracting and compliance. We are also required to be extremely familiar withthe licensing requirements of the countries within which we plan to expand. Understanding licensing and applying for the same considering all compliance requirements is a major part of what we do.”

~Juliette Thirsk, Head of Legal, Peach Payments
Streamlining Legal at a FinTech Startup

AI can track real-time contract performance against compliance frameworks. Machine Learning algorithms can proactively monitor contracts, providing alerts for deviations, potential breaches, or upcoming deadlines.

This minimizes exposure to legal ramifications and penalties, promoting a more reliable and legally sound contracting process.

#3 Data-driven negotiation strategies

AI can equip negotiators with powerful insights gleaned from historical data and market trends.

By analyzing past contracts, success rates, and even industry benchmarks, AI can provide a clearer understanding of reasonable terms, areas for assertive negotiation, and concessions that align with both parties' objectives.

Equipped with this data, businesses can enter negotiations with a more informed, confident strategy increasing their chances of securing favorable outcomes.

Also read: How AI Accelerates Contract Negotiations

#4 Contract renewal prediction

Through predictive analytics, AI can forecast the likelihood of contract renewals based on customer behavior, satisfaction levels, and market conditions.

By analyzing past renewal patterns and key indicators, AI algorithms can recognize early signs of potential renewal or churn. This enables organizations to proactively engage with customers, address issues or concerns, and tailor renewal offers to maximize retention rates.

By predicting contract renewals accurately, businesses can maintain stable revenue streams and minimize the impact of customer attrition on their bottom line.

Also read: Automatic Renewal Clauses—How to Mitigate Risks and Protect Your Interests

#5 Performance tracking

“Most C-Suite executives bank on data and hard metrics and not word-of-mouth. When you have certain metrics that shed light on how legal teams have contributed to growing the revenue stream of the company, it becomes easier for the GC to make business cases.”

~Gitanjali Pinto Faleiro, General Counsel, Company Secretary & CCO at Greenhill & Co.
Navigating the C-Suite as a GC

AI enables organizations to track contract performance in real-time by analyzing key metrics, such as deliverables, milestones, and service level agreements.

By monitoring performance against predefined benchmarks and thresholds, AI can identify areas of exceptional performance and highlight potential bottlenecks before they can impact business operations.

How to get the best out of AI-powered predictive insights

While predictive analytics is capable of making your contract management strategy significantly better, its capabilities hinge on your expertise, implementation approach, and long-term strategy.

Here, we’ve covered some of the best practices you must incorporate to ensure maximum results from AI-driven predictive insights.

#1 Feed your AI with the right data

Like any other machine learning system, AI-powered predictive analytics is only as effective as the data the system feeds on. Organizations must provide their AI systems with high-quality, structured, and relevant contract data. This can involve:

• Historical contracts: A vast repository of previously executed contracts offers the baseline for AI to identify trends and make predictions.
• Market data: Supplement contract data with external market trends, regulatory updates, and competitor insights for a more comprehensive picture.
• Metadata: Tag contracts with appropriate metadata (e.g., contract type, jurisdiction, parties involved, key terms) to facilitate organized analysis and pattern recognition.

By feeding your AI with the right data, you ensure that the insights derived from predictive analytics are comprehensive and actionable, empowering your team to make informed decisions with confidence.

Also read: How Contract Data Management Helps Maximize Legal Impact

#2 Support insights with human validation

While AI provides powerful insights, it's essential to remember it's still a tool, not a replacement for human expertise. Human oversight adds a layer of context, interpretation, and critical thinking that complements the analytical capabilities of AI. 

Legal professionals should scrutinize the suggested changes, risks, or trends to ensure they are factually sound, legally correct, and aligned with the overarching business strategy.

#3 Invest in training and employee upskilling

To fully leverage the capabilities of AI’s predictive insights, organizations must invest in training and upskilling their employees. Employees need to develop proficiency in interpreting the insights generated by AI systems, as well as utilizing them effectively in decision-making processes.

Training programs should cover various aspects, including data literacy, AI fundamentals, contract analysis techniques, and strategic thinking.

#4 Monitor its performance and adjust strategies accordingly

Like any technology, sustainable AI deployment requires ongoing evaluation and refinement. Ensure you have a process for evaluating the impact of predictive insights on business outcomes and collecting feedback from stakeholders.

This ensures your AI tool continues to learn from fresh data and remains aligned with evolving business conditions and objectives.

#5 Don’t shy away from external expertise

“One of the most important tasks faced by in-house lawyers is deciding what work will be done in-house and what gets sent outside.”

~Sterling Miller, CEO and Senior Counsel for Hilgers Graben PLLC
Ten Things: When To Send Work To Outside Counsel (And When To Bring It In-House)

While developing in-house expertise in AI-driven predictive analytics is valuable, it's also essential to recognize when to seek external expertise and collaboration.

AI technology is complex and rapidly evolving, and staying at the forefront of innovation requires access to specialized knowledge and resources that may not be available internally.

Utilizing external consultancy services such as Lex by SpotDraft can provide valuable insights, best practices, and support in various areas like:

• Tool selection and implementation
• Employee training
• Data preparation and cleansing
• Strategic guidance
• Performance management

Accelerate AI-driven predictive insights with Lex

The impact of predictive insights on business outcomes is becoming more apparent as more forward-thinking businesses continue to turn it into their competitive advantage.

However, implementing AI for any use case can sometimes be more complex than anticipated, especially when in-house teams lack the necessary expertise in AI solutions. In this situation, leveraging external expertise is the way to go. This is where Lex by SpotDraft shines.

Lex by SpotDraft is a suite of AI-driven, on-demand, and platform-agnostic services designed to help businesses streamline legal processes for maximum impact.

With Lex, you get access to a team of 100 seasoned legal professionals ready to help you leverage cutting-edge technologies like AI in the best way possible. Through Lex, you can reduce your legal workload by 60%, gain granular insights from your contract data, and mitigate risk at scale.

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