Your AI strategy is only as good as its first move

Most artificial intelligence (AI) strategies are sound—ambitious, well-researched, tied to real business goals—but they are still sitting on the shelf.

A plan that never turns into action is just a nice idea. That distinction is driving the shift from enterprise resource planning (ERP) to enterprise resource execution (ERX), from systems that record what happened to systems that act on what is happening. The same gap shows up one level down, between having an AI strategy and having a first move you can defend in a budget meeting.

The numbers bear it out. In a survey of 1,000 decision-makers, 49% were stuck in the early stages of AI: pilots only, paused or not yet started. Nearly a quarter said an unclear return on investment (ROI) was stopping them entirely. These are not organisations short on ambition or capability. 80% believed they could manage an AI implementation themselves. They have a strategy on paper and no agreement on what to do Monday morning.

So yes, you need a strategy. What stalls most companies is the absence of a specific, sequenced starting point, chosen because it is where the value is highest.

Start where the value is highest

The instinct with AI is to go broad. Survey every process, build a transformation roadmap, align the executive team on all of it, then begin. It feels rigorous, but it is why so many plans stall. The effort to decide everything at once exceeds the effort to start somewhere that matters.

The organisations pulling ahead do the opposite. They identify the one or two use cases with the clearest line to a business outcome, prove them and use that proof to fund what follows. Momentum is what earns the budget for everything after it.

This is the principle Infor™ Velocity Suite is built around. You start where the value is highest, adopt at the pace your business demands and scale with predictable cost and governance already written into the core rather than bolted on afterward.

From there, the value compounds. Every use case that goes live makes the next one faster because the data foundation, governance, and integration work are already done. Team Air Distributing started with AI agents for accounts receivable and saw a 90% improvement in credit decision speed, freeing its team to take on the next process instead of starting from scratch. Infor's forward-deployed engineers see this pattern repeatedly, with most AI solutions now going live in under four weeks. The first use case is the hardest. It is also the one that makes the rest less costly.

Becoming an agentic enterprise is a sequence, not a leap

Becoming an agentic enterprise is not a single procurement decision. It is a sequence of precise industry agents, adaptive experiences, autonomous orchestration and governed velocity, arriving in an order that makes sense for your operation. Gartner's ERX maturity model describes a similar progression and notes that much of the market still sits at its earliest stages, meaning the gap does not close by moving faster. It closes by moving in the right order.

This is also where generic AI makes the first move harder than it needs to be. A model built for every industry at once does not account for your supplier confirmations, audit requirements or seasonal demand patterns. The work of turning a general capability into a specific outcome falls entirely on you.

Industry-specific agents reverse that dynamic. When the use case already reflects the workflow, compliance rules and data model your business runs on, you are choosing from options that already fit rather than designing from scratch.

If you already run Infor, you are closer than you think

For information technology (IT), operations, and finance leaders still running Infor on-premises, this is worth sitting with. Data readiness is the largest constraint on AI accuracy, and your operational data is already structured around the processes agents need to understand. That is a foundation many organisations are still trying to build.

So, the question changes. Not "can we do AI?" but "which use cases first, and in what order?"

Find your first move in two minutes

You do not need a six-week discovery to know where AI fits your business.

Our AI Opportunity Assessment asks seven questions and takes about two minutes. You will get an AI readiness score plus the AI agent use cases most likely to deliver for your operation, drawn from a catalog of more than 300 built for industries like yours.

If the results point somewhere worth pursuing, a guided session with an Infor Velocity Suite expert turns them into a phased roadmap, sequenced from quick wins to long-term value.

Your strategy is probably sound. Let's find its first move.

Get your score →