How much does PowerApps cost per user in 2026?

PowerApps Premium costs $20 per user per month ($240/year). Organizations with 2,000+ users can negotiate volume pricing at $12 per user per month. The pay-as-you-go option runs $10 per active user per app per month through Azure. That doesn't include Power Automate flows, premium connectors, AI Builder credits, or Dataverse storage, all of which cost extra.

Is the PowerApps per-app plan retired?

For new customers, yes. Microsoft ended new sales of the PowerApps per-app plan on January 2, 2026, removing the $5 per user per app per month SKU from the licensing guide with no prior announcement. Existing Enterprise Agreement (EA) and Cloud Solution Provider (CSP) customers can still renew their per-app licenses. Microsoft Products and Services Agreement (MPSA) customers can use it until their agreement expires, then have 60 days to migrate. New customers must choose PowerApps Premium ($20/user/month) or pay-as-you-go ($10/active user/app/month), which represents a 100-300% higher starting cost compared to the per-app plan.

What is the cheapest PowerApps alternative?

Most PowerApps alternatives use per-user SaaS pricing, ranging from $8 to $50+ per user per month. The cheapest long-term alternative is a perpetual license platform like m-Power, a low-code development platform built by mrc, which charges a one-time fee with no per-user costs and unlimited users. At scale, m-Power costs significantly less than any per-user platform over a 3-5 year period.

Is there a low-code platform with no per-user fees?

Yes. m-Power by mrc offers a one-time perpetual license with unlimited users, unlimited applications, and no recurring per-user costs. m-Power runs directly over existing databases (DB2, SQL Server, MySQL, Oracle, PostgreSQL) and can be deployed on-premise or in the cloud. mrc has served over 1,500 customers since 1981.

Can I replace PowerApps with an on-premise solution?

Yes. While PowerApps is primarily cloud-based with limited on-premise options, platforms like m-Power let you deploy fully on-premise within your own infrastructure. This gives IT complete control over data, security, and compliance. m-Power connects directly to your existing on-premise databases without requiring data migration to a cloud service like Dataverse.

Shadow AI refers to the use of AI tools by employees without IT approval or oversight. This includes consumer AI platforms like ChatGPT, unsanctioned AI coding assistants, and AI-built applications that were never reviewed, secured, or documented by IT.

How is shadow AI different from shadow IT?

Shadow IT was typically one unauthorized tool or subscription. Shadow AI produces output: AI-generated code, applications, automations, and workflows. IT teams don't just inherit an unauthorized tool — they inherit artifacts that are running somewhere, touching company data, with no documentation or defined owner.

Why won't stricter policies stop shadow AI?

According to Gartner, shadow AI is the number one indicator of unmet business needs. Employees aren't using unauthorized tools because they're careless — they're using them because the approved path is too slow. If IT takes six weeks to deliver what an AI tool can produce in an afternoon, policy alone won't change the math. Block one tool and employees find another.

What risks does shadow AI create for IT teams?

Shadow AI creates two main categories of risk. First, data exposure: 60% of organizations have already experienced a data exposure event from employees using public AI tools, according to Cisco. Second, maintenance burden: AI-generated applications often have no security model, no documentation, and no defined IT owner. When something breaks or an audit asks questions, IT inherits the problem.

How can IT teams get ahead of shadow AI?

The most effective approach is making the governed path faster than the workaround. When IT can deliver AI tools connected to your existing data — running inside your environment, under your security model — fast enough to satisfy business demand, shadow AI stops being the default option.

What is an AI workflow?

An AI workflow is a business process that includes AI at one or more steps. The AI analyzes data, makes decisions, or triggers actions as part of the larger process.

What is a data-driven AI workflow?

A data-driven AI workflow runs over your existing business data. The AI reads from your systems and reacts to what it finds. The workflow writes results back to your systems.

How is AI changing workflow automation?

Traditional automation follows pre-defined rules. AI brings intelligence to workflows by interpreting text, detecting tone, classifying content, making judgment calls, and providing suggestions based on policies.

What types of workflows are good candidates for AI?

Workflows involving analysis, content generation, interpretation, and decision making. Examples include support ticket routing, document classification, lead scoring, invoice processing, and anomaly detection.

How can I create an AI workflow over my data?

You need a platform that works over your data and lets you design workflows visually. With m-Power, you connect to your existing data, create AI Assistants and Agents over select parts of your data, and add them to your workflows.

2026 – mrc's Cup of Joe Blog

A PowerApps Alternative That Lets You Own the Platform (No Per-User Fees)

By Sal Stangarone / Low-code

If you’re evaluating PowerApps for the first time in 2026, the pricing just changed.

I know…SaaS pricing changes all the time. So what? The business world has gotten used to it.

But here’s the thing. When you’re dealing with a low-code platform that creates and runs your business applications, it’s different. Your business often relies on the applications that it’s created. A pricing change can have major implications for everything you’ve built and everyone who depends on it.

I want to dig into this idea, using PowerApps’ recent change as an example. Is SaaS really the best approach for low-code?

…

A PowerApps Alternative That Lets You Own the Platform (No Per-User Fees)Read More »

Shadow AI Is the New Shadow IT (and Better Policies Won’t Stop It)

By Sal Stangarone / Artificial Intelligence

Something is happening in your organization right now that you probably don’t have full visibility into.

It’s happening in organizations across the globe.

Business analysts are building reporting dashboards with AI tools, connected to live company data, with no IT involvement.

Finance staff are pasting budget projections into consumer AI platforms to run analysis faster than waiting on a request.

HR employees are running sensitive policy documents through a chatbot to get quick summaries.

Staff in operations are building workflow automations using free AI builders they found online.

None of it went through IT.

That’s shadow AI. And the reason it matters isn’t just that data is leaving your environment…though it is. It’s that this behavior is accelerating faster than any governance policy can catch up with.

Eventually, everything these people built becomes your problem to secure, maintain, and explain to auditors.

…

Shadow AI Is the New Shadow IT (and Better Policies Won’t Stop It)Read More »

How to Build AI Workflows Over Your Data

By Sal Stangarone / Artificial Intelligence, Workflow

Some things don’t really “click” until you see them in action. You hear people talking about some new technology, trend, or tool. But you don’t really “get it” until you see it.

That’s how data-driven AI workflows were for me.

I’d heard the AI hype. Then I saw an AI assistant working over live business data. My wheels started spinning. It opened up so many possibilities.

Then I saw that AI assistant added to a workflow. Data was passed to the assistant, which then made a decision…and led to another workflow step, which could then lead to another assistant and so on.

That’s when it really clicked. You can do anything with this.

In this article, I’ll explain more about AI workflows and why they’re so important to businesses. What are they? How do they work? Why should you care?

Also, we’ve included a video that walks through the whole process of creating an AI workflow from start to finish. After all, some things don’t really “click” until you see them in action.

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How to Build AI Workflows Over Your DataRead More »

Year: 2026