Side-by-side

Workday AI vs Make

Workday AIMake

Bottom line: Workday AI for large enterprises already using Workday; Make for operations and marketing teams automating multi-step, cross-app processes.

	Workday AI Workday AI is a suite of AI capabilities embedded within Workday's enterprise HR and finance platform, designed to help large organizations automate workflows, improve talent strategies, and streamlin Visit	Make Make is a visual workflow automation platform that connects over 3,000 apps and services, enabling users to build automated workflows without extensive coding Visit
Votes	0	0
Pricing	Freemium	Freemium
Category	Automation	Automation
Tags	automate-workflowsanalyze-data	automate-workflows
Best for	Large enterprises already using Workday HR and talent teams pursuing skills-based strategies Workforce planning and analytics functions	Operations and marketing teams automating multi-step, cross-app processes No-code and low-code builders who want visual control over complex logic Businesses running high-volume workflows sensitive to per-operation cost
Pros	AI capabilities live inside the same system of record used for core HR and finance, so insights and automation act on live organizational data instead of disconnected exports. Skills Cloud and skills intelligence give large employers a structured way to map, match, and develop workforce capabilities across recruiting, internal mobility, and planning. The Flex Credits model bundles AI agents and platform capabilities into a subscription pool, offering more budget predictability than pure per-token consumption pricing. Deep footprint across HR, finance, and workforce planning means AI features can span talent and financial workflows within one governed platform. Enterprise-grade governance, security, and administrative controls come with the broader Workday platform rather than being bolted on.	The visual scenario builder makes complex, multi-branch automations far easier to design and audit than linear step-based tools, with data flow and logic represented clearly on a single canvas. A library of 3 000+ pre-built app connectors, backed by generic HTTP, webhook, and custom app modules, means nearly any API can be reached even when a native integration is missing. Make is genuinely AI-native, offering agentic automation, ready-made AI agents, and an MCP server that lets AI assistants trigger real actions across connected apps rather than just generating text. The pricing is competitive for high-volume workflows, with an operations-heavy allowance at entry-level tiers and a no-time-limit free plan for experimentation.
Cons	The AI features are only meaningful for organizations already running Workday, so there is significant platform lock-in and no standalone value for non-customers. Total cost is opaque and enterprise-negotiated; Flex Credit consumption and implementation services can make real spend hard to forecast upfront. Realizing value depends on clean, well-structured data and often a multi-quarter implementation, which adds meaningful upfront effort and cost. It is aimed squarely at large enterprises, leaving small and mid-market organizations underserved by both pricing and complexity.	The visual canvas is powerful but has a real learning curve; newcomers to automation often find its data mapping, iterators, and error handling harder to grasp than simpler competitors. The recently introduced credit-based billing model can make costs harder to predict, since advanced and AI-powered actions may consume more credits than a standard operation. Complex scenarios can become difficult to maintain and debug at scale, and heavy reliance on the platform creates a degree of workflow lock-in. There is no self-hosted or offline option, so teams with strict on-premise or air-gapped requirements will need an alternative.

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