Artificial intelligence is, of course, on your organization’s roadmap. Even if you’re taking a cautious, measured approach to AI, the future includes artificial intelligence, and it is clear.
Having technology and being ready to use it are not the same thing, however. Even if your organization knows it must put AI in place as a foundational technology, there’s still the laying of the foundation for its actual use before AI can impact operations positively.
Evaluating your organization’s AI readiness and laying the foundation is the first step before investing in an AI solution or rolling it into operations. To evaluate your organization's AI readiness, you must take a comprehensive look at your people, processes, and data to identify your starting point and avoid costly missteps.
There is a difference between human readiness and technological readiness.
Start by looking at your employees and operations with an eye toward AI adoption. Will roles change? Will automation shift responsibilities? Will people be ready to keep pace? Will your employees embrace AI or push back against it and create shadow processes instead?
This is an organizational change step, and it ultimately feeds into change management. How ready is your company and your employees for the introduction of widespread AI within the business?
Once you’ve looked at your people and organization, evaluate where AI meaningfully can help your business today.
Get specific and pinpoint actual processes within your business where AI can automate or enhance existing workflows. Where is the low-hanging fruit? Where should your organization focus on first when rolling out AI?
Be mindful to differentiate between AI opportunities today and the wishlist for the future, too. AI might be able to radically transform your business, but starting with these larger opportunities could cause project creep, create disruption, and stall adoption momentum.
So define where AI can help today and also where AI can assist with strategic direction in the future. Emphasize the processes where AI can improve today, though.
Artificial intelligence is only as good as the data you feed it.
Giving embedded AI access to your organizational data can turn AI from a slop factory into a revolutionary technology for business productivity, but only if your organization has clean data that is centrally managed.
So as part of your AI readiness assessment, you need to look at organizational data accessibility and the quality of the existing data in your system. Is the data clean, reliable, consistent, and actionable? Without strong data quality, your AI initiative will prove underwhelming or even counterproductive in some use cases.
If you already are using a modern ERP solution such as SAP Cloud ERP, the answer to this part of the assessment likely will be “yes, our data is ready.” But if you’re not already on a modern ERP solution, this is an important question and potentially an area that must be addressed before widespread AI rollout.
Even if your organization and people are ready for AI, there’s still the question of internal capabilities to use AI effectively.
After assessing data quality, you should evaluate internal resources and skills currently within the organization to understand the infrastructure and skills that need development as part of AI implementation.
These internal capabilities include backend infrastructure that can hook into AI and deliver data in real-time, and also employee skills for effectively taking advantage of AI. While some AI opportunities might center around automation and require little from employees, other opportunities in the area of analytics or agentic AI could require employee education before they can be fully leveraged.
Prior to starting your AI rollout, you also should create a realistic view of the requirements needed to implement AI at your organization.
This look at project requirements should include a realistic assessment of budgetary needs to make it happen, and the creation of an accurate timeline for project implementation.
Basic project management planning, in other words. But given the buzz around AI and how it puts pressure on businesses to become AI-ready, this is a critical step that should not be forgotten. Successful projects start with accurate planning.
Businesses that run on a modern cloud ERP start with an advantage.
That’s because cloud ERP is foundational technology both for being ready for AI adoption and deeply embedding it within the processes of an organization.
A modern ERP such as SAP Cloud ERP both ensures that business data is ready for AI, and it comes with embedded AI from leading providers such as ChatGPT and Anthropic. Businesses that run on SAP Cloud ERP still must handle employee skills and change management, but the foundation is in place already for taking advantage of AI for greater levels of automation, intelligent AI-driven analysis, and self-serve agentic AI assistance at all points in the company’s backend system.
If you’re already running a modern ERP such as SAP Cloud ERP, get to know its AI capabilities. If you’re not currently using a modern ERP solution to run your business, now is the time; you’re going to need it for AI adoption.
To learn more about the AI implementation journey, download our Path to AI Implementation Guide. You can also learn more about cloud ERP and its role in empowering your organization with AI by calling one of our experienced US consultants at (801) 642-0123 or by writing info@nbs-us.com. We love talking shop, and we’re happy to help.