By Bernadette Bulacan, Icertis.
Contracts form the foundation of commerce and govern every dollar in and out of the enterprise. This makes them a vast and untapped source of data to help businesses increase revenue, reduce costs, improve compliance, and manage risk by structuring and connecting contract data across the enterprise and integrating it with major software systems so business moves faster, with every intent realised, and every obligation met in commercial relationships.
Today, forward-looking businesses are moving beyond traditional Contract Lifecycle Management (CLM) into contract intelligence to continuously discover, assess and monitor risk in today’s volatile market. This new approach to CLM enables companies to leverage AI to turn contracts into powerful levers for avoiding risk by breaking down siloes across business functions, improving visibility across jurisdictions and geographies, and surfacing unique insights.
What challenges do laws, regulations, and compliance measures (i.e., ESG) pose to UK businesses? Why are contracts foundational to ESG goals?
Heightened expectations around Environmental, Social, and Governance (ESG) measures are driving companies to commit to more socially responsible approaches to commerce and improve their ability to demonstrate compliance as new regulations become increasingly widespread. With EU and UK regulations like the Corporate Sustainability Reporting Directive (CSRD) materially changing the regulatory landscape, it is essential for companies that don’t prioritise sustainability to comprehend and operationalise their ESG commitments with each contractual relationship – or risk regulatory penalties and reputational damage. In fact, approximately 50,000 companies fall under the CSRD’s current remit, as the legislation seeks to transform sustainability reporting for organisations both inside the EU and companies headquartered outside the EU that conduct operations or business activities within its jurisdiction.
The most powerful way businesses can achieve compliance and mitigate risk in today’s regulatory environment is by memorialising and operationalising their ESG commitments within each contractual relationship. McKinsey reports that a company’s carbon footprint is largely determined by Scope 3 emissions, which account for 80 to 90 % of emissions in the upstream supply chain. Companies need to have a deep understanding of their contractual partners and commitments in those relationships – identifying trusted third-party partners who have agreed to ESG clauses and obligations. This will help with reporting and audit requirements and mitigate noncompliance with evolving regulations.
An Economist Impact report sponsored by Icertis found that 70% of companies consider contract language an effective way to enforce ESG standards, including climate commitments. Still, less than one-third are utilising contractual language to operationalise ESG policies. The complexity of ESG regulations, limited visibility and transparency across large-scale enterprises that manage hundreds – if not thousands of contracts, and lack of standardisation can be challenging for businesses aiming to prioritise sustainability and meet new regulations. Such challenges present a golden opportunity for emerging technologies like AI and contract intelligence to demonstrate business value.
Contract intelligence solutions and contract data are key to automating the analysis of contracts across millions of commercial agreements. Integrated solutions that connect and analyse enterprise-wide data using AI can give finance and procurement teams the visibility they need to ensure that ESG commitments are met throughout their supply chain. Leveraging AI capabilities, businesses can ensure the right clauses (such as certifications), adherence to ethical labour and governance practices, and performance indicators specific to sustainability, are included in contracts during negotiations. This creates the opportunity to minimise risk and promote compliance, and then extract data post-signature to flag if obligations are left unmet – ultimately holding organisations accountable for common goals so sustainability promises become a reality and don’t get lost in complexity.
What financial risk does manual contract management pose to large businesses?
Today, increasing revenue, reducing costs, accelerating cash flow, and minimising risk are all business imperatives for financial performance. World Commerce & Contracting estimated that poor contract management could cost companies 9% of their bottom line in 2020, and the cost of mismanagement is likely even higher in today’s economy. Unfortunately, too many organisations have an overly simplified way of managing their contracts and rely on manual, paper-based processes that do not provide visibility into cash flow and the realisation of discounts driven by contracts. This leaves companies susceptible to hidden fees and the potential to leave savings on the table through unfulfilled obligations. Aside from the impact on financial performance, non-compliance with ESG regulations resulting from manual contracting can result in reputational damage, potential penalties, and even subject a company to claims of greenwashing.
A CLM platform that utilises AI and integrates with core financial systems enables enterprises to minimise revenue leakage by ensuring contract terms are met, while also avoiding potential penalties the company might incur. AI-powered contract management also delivers efficiency and automation to decrease expenses associated with the time employees dedicate to managing contracts.
What are the implications of AI in discussions about risk, and how will it change the way businesses manage contracts?
AI is certainly having its moment as forward-looking businesses consider the benefits of using large language models to change how they work. But, it’s important to acknowledge that AI is only powerful when paired with the right data.
When legal, finance, and procurement teams think of AI as a partner, it can be used to accelerate the drafting, negotiating, and execution of commercial agreements. And, combining AI with a rich data lake through integrations into core systems of record – like an ERP, for example – also positions enterprises to derive deep insights from their contracts and ensure the full intent of those agreements is realised post-execution. Especially with the increasing utilisation of large language models and generative AI. With contracts, security is paramount, so it’s important that businesses look to secure platforms like Microsoft Azure OpenAI rather than just ChatGPT as they consider how to leverage AI in contract management.