Systems of record are becoming systems of action in the era of AI-first intelligence

Craig Fidler, Lead Business Consultant at Braintree, talks about Microsoft’s move to AI-first and how this helps organisations extract more value from existing systems and solutions.

The systems underpinning finance and customer relationships have primarily served as systems of record. The CRM and ERP are designed to preserve transactions, interactions and operational history to ensure the organisation has an accurate account of everything that has happened within the business. Now, these systems are slowly evolving into active platforms that use AI agents to interpret what has happened while providing insights that can be used to define what happens next.

This strategy can be seen in AI-first CRM and ERP systems that are slowly entering and disrupting the market. From Oracle to Microsoft, ERP systems are becoming more reliant on the potential of AI and its ability to automate workflows, provide recommendations and enhance decision-making. The direction is visible in the Microsoft ecosystem as the Dynamics 365 release wave 1 plan, which saw Microsoft introduce AI-powered and agentic functionality across sales, customer service, supply chain, commerce and HR. While the depth of agentic automation differs between applications, the scale and potential are there.

The broader software market is moving in the same direction. The Deloitte August 2026 research undertaken across more than 500 US leaders found that 43% were expanding their agent deployments across business functions, while 15% had reached scaled, orchestrated multi-agent adoption. The study also found that data foundations, trust and governance and integration cost remained the primary barriers to scale.

For companies already using these enterprise business applications, the change is taking place inside already familiar systems and workspaces and it is making a difference. Perhaps the biggest difference felt by the organisation right now is how processes are easing into autonomous workflows. For example, most companies require that employees submit expense claims that conform to specific rules. Someone opens the claim, goes through it and makes a decision. With autonomous workflows, it is possible to create company policy and then the AI will apply that policy to the submitted claim. It is capable of approving it, rejecting it or, if it isn’t sure, pushing it to a human being to approve. This type of workflow takes a lot of the grunt work out of day-to-day processes that eat into time and can be applied to anywhere a clear rule can be written down and checked against reality at volume.

In the fast-moving consumer goods and manufacturing (FMCG) environment, this value shows up in demand management and stock level efficiencies. AI systems are capable of assessing where demand is highest and ensuring that the business has the right stock levels to meet that demand and proposing adjustments on a continuous basis. AI is a fast and efficient way of doing the housekeeping that has been left behind because teams are too busy and the admin too demanding. The business benefits from streamlined systems and capabilities but remains in control – companies can see the recommendations and the data beneath them before deciding to go ahead. It is not blind trust in AI but rather greater visibility into systems and processes because of AI.

Decision-support follows the same logic. Take utilisation. This can be a number that has a direct impact on the business bottom line, particularly in certain sectors. Companies want more control over this and more visibility into when utilisation starts dropping. AI provides a more granular level of insight into which people are pulling the figures down and directs attention to the right departments and individuals. A blunt solution that’s usually a company-wide email becomes a sharp one when the company can directly manage expectations with the right individuals.

Making changes to systems and platforms to ensure they are secure and can withstand the threats doesn’t meant that companies have to throw away what they already have in place. The AI adds a layer over the top of your existing investment in ERP and CRM, reading your records that already sit across your different departments and silos and turning the data into information you can act on. It shortens the distance between your investment and the value it can deliver.

The value of AI inside your ERP and CRM comes out in both the expected and unexpected value felt by teams and decision-makers. It turns a system into an intelligent ecosystem capable of identifying and optimising actions, refining processes, automating workflows and turning your recording systems into action-based systems that change the way you do business.