Why Customer Workflows Are Becoming The Moat In The AI Era
Customer workflows are becoming the ultimate AI moat as deep integration into business operations creates sustainable competitive advantages, driving major corporate acquisitions, strategic alliances, and high-value platform deployments across industries.
Consider an insurance firm testing a pair of artificial intelligence assistants. Both comprehend customer inquiries, converse naturally, and excel during demos. Half a year later, however, the first assistant manages policy updates within the insurer’s infrastructure, adheres to authorization guidelines, and routes exceptions to human staff. The second remains a peripheral tool that workers open only occasionally.
While a superior model might emerge tomorrow, swapping out the initial assistant would demand altering the organization’s entire operational structure. This scenario highlights where a vital artificial intelligence moat is currently taking shape: directly inside customer workflows.
Recent corporate buyouts and strategic alliances point to three key takeaways for founders, investors, and corporate boards.
Workflow access creates strategic value
Schneider Electric’s deal to buy PTC for an equity value close to $22.6 billion grants it software utilized for designing, producing, and servicing tangible goods, embedding the company into client decision-making throughout the complete lifecycle of a product.
In parallel, the collaboration between Synopsys and OpenAI demonstrates a comparable rationale by merging cutting-edge artificial intelligence with specialized semiconductor design instruments and know-how, underpinned by revenue-sharing and licensing terms.
These corporate moves underscore how strategically valuable it is to control the operational setting where artificial intelligence carries out productive tasks. Enterprises already integrated into intricate sectors offer the client connections, specialized knowledge, and reliable procedures that AI creators require to monetize their innovations.
Consequently, founders should aim to secure a foothold inside a defined client process, while legacy enterprises can leverage their existing workflow access to gain negotiating leverage.
Completing recurring work builds defensibility
ElevenLabs revealed that its automated agents manage upwards of 15 million dialogues every week—spanning insurance renewals, healthcare scheduling, and refunds—alongside disclosing an employee share buyback at a $22 billion valuation. This level of practical deployment is especially significant for the conversation surrounding competitive moats. Once an application links to backend infrastructure, respects security parameters, manages edge cases, and dependably executes assignments, removing it introduces migration hurdles, validation costs, re-education, and operational hazards.
Such integration can boost customer retention while opening doors to manage adjacent workflows. Still, connectivity by itself provides minimal shielding. Users must rely on the solution and track the concrete benefits it generates. Investors ought to investigate the volume of repetitive tasks traversing the platform, the specific procedures dependent on it, and the true cost of switching providers.
Companies can acquire their way into workflows
ServiceNow’s purchase of Moveworks merges conversational intelligence and corporate search capabilities with mature process automation. At the time of closing, Moveworks served 5.5 million workers, with roughly 250 clients already utilizing the platforms of both businesses.
The core strategic goal is linking staff inquiries straight to the platforms and pathways that fulfill them across human resources, information technology, and other departments. This establishes a distinct corporate development agenda: pinpoint the client workflows the enterprise wishes to infiltrate, analyze the obstacles, and evaluate whether a partnership or buyout can speed up market entry.
A compelling acquisition target typically delivers proprietary technology, client ties, system integrations, and a firmly established function in everyday business activities.
Due diligence must examine the extent of user dependence on the solution, whether those bonds will endure the buyout, and if the combined portfolio can produce verifiable enhancements. As artificial intelligence functions advance, securing the ideal spot within client operations may prove to be a robust pathway toward sustainable expansion.
Frequently Asked Questions
01What is an AI moat in the context of customer workflows?
An AI moat refers to a sustainable competitive advantage. When an AI tool is deeply embedded into a company’s daily operations, workflows, and systems, it becomes very difficult and risky to replace, even if a superior AI model becomes available.
02Why are major acquisitions happening around workflow software?
Transactions like Schneider Electric’s acquisition of PTC show that owning the environment where AI does its work provides immense strategic value. It combines advanced AI with established industry tools, customer relationships, and domain expertise.
03How does handling recurring work increase defensibility?
When an AI product connects to internal systems, follows specific rules, and reliably completes repetitive tasks like refunds or renewals, replacing it involves significant operational risk, migration effort, and retraining costs.
Itay Sagie is a strategic adviser to tech companies, investors, CEOs and boards, specializing in strategy, growth and M&A. He is a guest contributor to Crunchbase News and a university lecturer on strategy, finance and entrepreneurship. Learn more at SagieCapital.com and connect with him on LinkedIn.
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Illustration: Dom Guzman
