with the rise of generative ai in recent years—particularly following the launch of chatgpt—monday, like countless other enterprises, began exploring and incorporating the technology.
however, the platform’s initial integration of generative ai didn’t yield the desired return on investment. this prompted the company to reassess its approach, focusing on developing ai-powered tools that genuinely enhance enterprise workflows. this shift led to the introduction of “ai blocks” and the preview of its agentic ai technology, known as “digital workforce.”
at its core, monday’s ai journey is an extension of the company’s founding vision.
“we wanted to accomplish two things: first, to give people the same capabilities we had as developers so they could create freely and experience that power. second, to build something they truly love,” mann told venturebeat in an exclusive interview.
monday’s enterprise ai evolution: from internal tools to customer-centric innovation
like many enterprise software providers, monday continuously seeks to enhance user experience and efficiency. its ai strategy has evolved through distinct stages:
- ai assistant: the platform’s first integration of ai across its ecosystem.
- ai blocks: modular ai features designed for workflow customization.
- digital workforce: advanced, agent-driven ai capabilities.
initially, monday introduced an ai assistant as part of its formula builder, allowing non-technical users to create and automate processes more easily. while valuable, it became clear that organizations needed ai more deeply embedded in their workflows.
monday’s ai product lead, or fridman, explained that the key takeaway from the ai assistant deployment was that users preferred ai integration within their daily operations—leading to the development of ai blocks.
ai blocks: a foundation for smarter enterprise workflows
recognizing the limitations of ai assistants, monday shifted focus to embedding ai capabilities directly into key workflow components.
ai blocks are pre-built ai functions integrated into monday’s workflow and automation tools. for example, in project management, ai blocks enable risk mapping and predictability analysis, allowing teams to focus on higher-level decision-making while ai handles repetitive, data-driven tasks.
this modular approach is particularly valuable given that 70% of monday’s user base consists of non-technical businesses. ai blocks provide ai-powered functionality without requiring extensive technical knowledge or disrupting workflows.
a model-agnostic approach to ai integration
while many companies rely on a single ai model, monday has opted for a model-agnostic strategy. mann believes ai models are increasingly becoming commodities, so instead of developing proprietary models, monday builds products and solutions on top of existing ai technologies.
ai director assaf elovic shared that the company uses a mix of models, including openai’s gpt-4o via azure and others through amazon bedrock, ensuring flexibility and robust performance. monday also adheres to strict data residency and encryption standards to maintain security and privacy.
the rise of agentic ai and monday’s digital workforce
as the industry moves toward agentic ai—where ai operates more autonomously—monday is taking a unique approach. unlike companies leveraging frameworks like langchain or crew ai, monday’s agentic ai is built on its ai blocks infrastructure.
elovic explained that the platform’s agentic ai uses tools such as sentiment analysis, information extraction, and summarization to enhance workflow automation. instead of standalone ai agents, monday’s “digital workforce” seamlessly integrates into existing processes, offering contextual awareness of user data and workflows.
the first digital workforce agent, set to launch in march, will be called “monday expert.” this ai-driven tool will allow users to describe their challenges, and the system will generate relevant workflows, boards, and automations to address them.
differentiation in a competitive market
monday competes across multiple industries, from project management to customer relationship management (crm), facing well-established players like salesforce and atlassian.
according to mann, monday differentiates itself through the deep integration of ai blocks across its platform. rather than treating ai as a standalone feature, the company embeds it directly into workflows, ensuring accessibility and usability for all users.
monday’s evolution showcases an enterprise software model where ai is not just an add-on but a deeply integrated, customizable tool. the company’s approach addresses a key challenge in enterprise ai adoption—delivering powerful yet user-friendly solutions.
looking ahead, monday’s ai strategy emphasizes empowerment over replacement.
“if a technology makes large companies more efficient, what does it do for smbs?” mann noted, highlighting how ai can level the playing field between businesses of all sizes.