DocuSign has spent nearly two decades building a business synonymous with electronic signatures, processing billions of agreements annually for more than 1.5 million customers worldwide. Now, under CEO Allan Thygesen’s leadership, the company is embarking on an ambitious transformation that extends far beyond its signature product—leveraging artificial intelligence to reimagine how businesses create, negotiate, and manage the entire contract lifecycle.

In a revealing conversation with The Verge, Thygesen outlined a vision where DocuSign evolves from a transaction platform into an intelligent agreement management system. The shift represents a fundamental rethinking of the company’s value proposition at a time when AI is disrupting traditional software categories and customers are demanding more comprehensive solutions. “We’re moving from being a company that helps you sign documents to one that helps you understand, negotiate, and optimize every agreement in your business,” Thygesen explained, signaling the strategic pivot that could define DocuSign’s next chapter.

The timing of this transformation is critical. DocuSign faces mounting pressure from competitors offering AI-powered contract analysis tools, while simultaneously navigating a mature e-signature market where growth has moderated from pandemic-era highs. The company’s stock has experienced significant volatility over the past two years, reflecting investor uncertainty about its ability to expand beyond its core product. Thygesen, who joined DocuSign in 2022 after leading Google’s advertising business, brings a track record of scaling technology platforms—but his challenge now is convincing the market that DocuSign can capture value from the estimated $50 billion contract lifecycle management opportunity.

The Intelligent Agreement Management Vision

At the heart of DocuSign’s transformation is what Thygesen calls “Intelligent Agreement Management”—a suite of AI-powered capabilities designed to address pain points throughout the contract lifecycle. According to The Verge interview, the company has introduced features that can extract key terms from existing contracts, identify risky clauses, suggest negotiation strategies, and even generate new agreement language based on company preferences and historical data. These capabilities represent a significant departure from DocuSign’s traditional strength in workflow automation, requiring new technical competencies in natural language processing and machine learning.

The company’s AI strategy leverages both proprietary models trained on billions of anonymized agreements processed through its platform and partnerships with leading large language model providers. This hybrid approach, Thygesen argues, gives DocuSign a unique advantage: the company can combine the pattern recognition capabilities of general-purpose AI with domain-specific knowledge accumulated over years of facilitating transactions across industries. “We’ve seen more agreements than probably any other company in the world,” he noted, emphasizing the data moat that DocuSign has built through its market position. “That gives us insights into what makes a good contract, what terms are standard, and where negotiations typically get stuck.”

Addressing the Trust and Accuracy Challenge

However, deploying AI in contract management raises significant concerns about accuracy and liability—issues that Thygesen acknowledges cannot be dismissed. Legal agreements carry enormous financial and regulatory consequences, making hallucinations or errors potentially catastrophic for customers. The CEO emphasized that DocuSign’s AI features are designed to augment rather than replace human judgment, with transparency mechanisms that show users how the system reached its conclusions and confidence scores for extracted information. “We’re very clear with customers that this is about giving legal and business professionals better tools, not automating away their expertise,” Thygesen stated in The Verge conversation.

The company has implemented what it calls “guardrails” to minimize risk, including human-in-the-loop workflows for high-stakes agreements and the ability for customers to customize AI behavior based on their risk tolerance and industry requirements. DocuSign is also investing heavily in explainability features that document the AI’s reasoning process—a capability that becomes crucial when contracts are disputed or audited. These safeguards reflect lessons learned from early AI deployments in other high-stakes domains, where overconfidence in automation led to costly mistakes. Still, the question remains whether customers will trust AI-generated contract language or analysis when millions of dollars hang in the balance.

The Competitive Pressure from Specialized Startups

DocuSign’s AI push comes as the company faces intensifying competition from well-funded startups focused specifically on contract intelligence. Companies like Ironclad, LinkSquares, and Evisort have raised hundreds of millions in venture capital to build AI-native contract management platforms, often targeting the same enterprise customers that form DocuSign’s core base. These competitors argue that their purpose-built approach to contract AI gives them technical advantages over DocuSign’s legacy architecture, which was originally designed for a different use case. The narrative poses a challenge for Thygesen: convincing customers and investors that DocuSign can innovate as quickly as nimbler rivals while managing a large, established business.

Thygesen’s response emphasizes DocuSign’s distribution advantages and customer relationships. With agreements already flowing through its platform at massive scale, the company can introduce AI features to existing customers without requiring wholesale system replacements—a significant advantage in enterprise sales cycles that often span months or years. “Our customers are already sending us their most important documents,” he noted. “Adding intelligence to that workflow is a natural extension, not a rip-and-replace.” The strategy mirrors successful platform expansions by other enterprise software giants, from Salesforce’s evolution beyond CRM to Microsoft’s transformation of Office into a comprehensive productivity suite. Whether DocuSign can execute a similar expansion remains an open question that will likely be answered over the next several quarters as AI features move from pilot programs to general availability.

The Economics of AI-Powered Contracts

The financial implications of DocuSign’s AI strategy extend beyond product differentiation to fundamental questions about pricing and margins. AI capabilities require substantial computational resources, particularly for processing large contract repositories or running complex analysis in real-time. These infrastructure costs could pressure margins if DocuSign cannot price AI features appropriately or achieve sufficient scale to amortize expenses across a large customer base. Thygesen indicated that the company is experimenting with various pricing models, including usage-based fees for AI analysis and tiered subscriptions that bundle different levels of intelligence with core e-signature functionality.

The pricing challenge is compounded by customer expectations shaped by consumer AI products, many of which are offered for free or at minimal cost. Enterprise buyers increasingly question why they should pay premium prices for AI features when they can access powerful language models directly from providers like OpenAI or Anthropic. DocuSign’s answer revolves around vertical integration and workflow embedding—the value proposition that its AI is specifically trained for contracts, integrated into existing business processes, and backed by enterprise-grade security and compliance guarantees. “Generic AI tools might help you draft a contract,” Thygesen argued, “but they don’t understand your company’s specific terms, they’re not connected to your approval workflows, and they can’t automatically route documents to the right signers.” The bundled value proposition will be tested as customers make build-versus-buy decisions in an environment where AI capabilities are rapidly commoditizing.

The Broader Implications for Knowledge Work

DocuSign’s transformation reflects broader questions about how AI will reshape professional services and knowledge work. Contracts have traditionally required significant human expertise to draft, review, and negotiate—expertise that commands high billing rates from law firms and corporate legal departments. If AI can handle routine contract analysis and generation, it could dramatically reduce the time and cost associated with agreement management, potentially disrupting business models throughout the legal industry. Some legal professionals view AI contract tools as threats to their livelihoods, while others see opportunities to focus on higher-value strategic work while delegating routine tasks to machines.

Thygesen positions DocuSign’s AI as an enabler rather than a replacement, arguing that automation will expand the total addressable market by making contract management accessible to smaller businesses and non-legal professionals who currently avoid formal agreements due to complexity and cost. “There are millions of business relationships that should be governed by contracts but aren’t, simply because the process is too painful,” he observed. “If we can make it as easy to create a customized contract as it is to send an email, we open up entirely new use cases.” This market expansion thesis is critical to DocuSign’s growth story, as the company seeks new revenue streams beyond its mature core business. Whether small businesses will adopt formal contract management at scale remains speculative, but the potential market size is substantial if friction can be sufficiently reduced.

Technical Architecture and Integration Challenges

Implementing AI capabilities across DocuSign’s existing infrastructure presents significant technical challenges that Thygesen’s team must navigate. The company’s platform was built primarily for workflow orchestration and secure document storage—not for the compute-intensive tasks required by modern AI models. Retrofitting AI into this architecture requires careful engineering to maintain the reliability and security standards that enterprise customers demand, while adding new capabilities for model training, inference, and continuous learning. DocuSign has been hiring aggressively in AI and machine learning, competing for talent with better-funded tech giants and well-capitalized startups.

Integration with customers’ existing technology stacks adds another layer of complexity. Enterprise organizations typically use dozens of systems for contract creation, approval, storage, and analysis—from Microsoft Word and Salesforce to specialized legal tech platforms. For DocuSign’s AI to deliver maximum value, it must connect seamlessly with these tools, extracting data from various sources and pushing insights back into the applications where business users work. Thygesen acknowledged that building and maintaining these integrations requires ongoing investment, but argued that DocuSign’s market position gives it leverage in partnership negotiations. “We’re often the system of record for executed agreements,” he noted, “which makes us a natural hub for contract intelligence regardless of where documents originate.” The hub strategy echoes successful approaches by other enterprise platforms, though execution will determine whether DocuSign can deliver on the integration promise.

Regulatory and Compliance Considerations

As DocuSign deploys AI across global markets, it must navigate an increasingly complex regulatory environment for both contracts and artificial intelligence. Different jurisdictions have varying requirements for electronic signatures, data residency, and AI transparency—requirements that can conflict or create compliance burdens for multinational customers. The European Union’s AI Act, for example, classifies certain contract-related AI systems as high-risk, triggering additional documentation and testing obligations. Thygesen’s team must ensure that DocuSign’s AI features comply with these evolving regulations while remaining flexible enough to adapt as rules change.

The company’s approach to AI governance includes what Thygesen described as “responsible AI principles” that prioritize transparency, fairness, and human oversight. DocuSign has established internal review processes for AI features, including bias testing and adversarial evaluation to identify potential failure modes before customer deployment. These governance mechanisms add development time and cost, but Thygesen argues they’re essential for maintaining customer trust and avoiding regulatory penalties. “We can’t afford to move fast and break things when we’re dealing with legally binding agreements,” he emphasized, acknowledging the tension between innovation speed and risk management. How effectively DocuSign balances these competing pressures will influence both its competitive position and its ability to operate across global markets.

The Path Forward for Agreement Intelligence

Looking ahead, Thygesen envisions a future where contracts become dynamic, machine-readable documents that can automatically adapt to changing circumstances and trigger actions across business systems. Instead of static PDFs that require manual interpretation, agreements could include structured data and embedded logic that enables automated compliance monitoring, renewal optimization, and risk assessment. This vision requires not just AI capabilities but also new standards for contract representation—an area where DocuSign is participating in industry working groups alongside competitors and customers. “The ultimate goal is to make every agreement intelligent and actionable,” Thygesen stated, describing a multi-year transformation that extends well beyond current product capabilities.

Realizing this vision will require sustained investment at a time when investors are demanding profitability and return of capital from software companies. DocuSign must balance R&D spending on AI with shareholder expectations for margin expansion and cash generation—a tension that has challenged many enterprise software companies in the current market environment. Thygesen’s background scaling Google’s advertising business may prove valuable as he navigates these tradeoffs, but the path forward is far from certain. DocuSign’s ability to execute its AI strategy while maintaining its core business will determine whether the company successfully transforms into an agreement intelligence platform or remains primarily an e-signature provider facing commoditization pressure. For an industry built on trust and reliability, the stakes of this transformation extend far beyond DocuSign’s own financial performance to the broader question of how AI will reshape the fundamental infrastructure of business relationships.