For months, the big question in management committees was whether artificial intelligence was going to "break" the software business. But the sales teams that are ahead of the curve are asking a much more down-to-earth question: how does AI help us find and retain more customers? AI applied to sales is no longer a promise for the future, but a real change in how commercial work is organized. And what’s interesting for an SME is that most of the advantages don’t come from having "more AI," but from solving a decision-flow problem that already existed.
This reflection stems from a recent SAP article by Jan Gilg ("The AI-Powered Go-to-Market Organization Isn’t Just a Vision Anymore", news.sap.com, 2026). We share it because the diagnosis matches what we see every day: when information, the authority to decide, and the ability to act are separated, value to the customer gets stuck. We’re going to translate those ideas to the terrain of a company that works with an ERP like Microsoft Dynamics 365 Business Central.
The problem isn’t the sale, it’s the system around the salesperson
We tend to think that a salesperson sells little because they don’t knock on enough doors. The reality for many companies is different: the salesperson loses hours waiting for a discount to be approved, for a quote to be generated, for a price to be validated, or for a contract to pass through three hands. The bottleneck isn’t the person, it’s the internal process.
This is where the ERP and automation make the difference. If customer data, order history, credit status, and commercial terms live in the same system, decisions stop depending on scattered emails. AI comes afterward, on top of that organized foundation, to accelerate what previously required human judgment step by step.
AI applied to sales: five moments where the game changes
The SAP article identifies five points in the customer journey where the change is already noticeable. We reinterpret them thinking of an SME with Business Central.
1. Segmentation: from "who they are" to "what they’re signaling"
Classic segmentation sorts customers by sector, size, or geographic area. It’s useful, but static. The approach that AI proposes changes the question: instead of "who is this customer," it asks "what are they signaling right now." Purchasing patterns, order frequency, changes in average ticket, or recurring issues are signals that already live in your ERP. With them, the team stops chasing every opportunity and focuses on those that truly have potential.
2. Outreach: relevance instead of volume
Response rates for cold outreach are at rock bottom. Sending more messages doesn’t fix anything; sending the right message does. When the salesperson knows the real context of an account —what they bought, what they stopped buying, what worries them— the first contact stops being generic. We’re not talking about personalizing the "Dear name," but about being relevant at the account level. That’s where tools like Copilot, integrated into the Microsoft ecosystem, can help prepare a proposal starting from real business data.
3. Order execution: eliminating invisible friction
This is the point that’s most underestimated. Approvals, price validations, quote generation, and contract signing are the places where days are lost and where deals cool off. Not because the customer hesitates, but because of internal complexity.
The SAP article cites the case of Amadeus, which with an autonomous agent reconciled unstructured payment data and resolved some 40,000 incorrect transactions that previously required manual intervention (source: news.sap.com). It’s a large-enterprise example, but the logic is identical in an SME: every administrative task that gets automated is time that returns to selling. With Power Automate and well-designed approval flows, a medium-sized company can reduce those stoppages without setting up a pharaonic project.
4. After-sales: shortening the time to first value
The handover from sales to after-sales is where the promise made during the sale usually evaporates. What the customer expected doesn’t always match what they experience in their first 90 days. The idea of an "account brain" —a living repository of context and knowledge about each customer— means that handover doesn’t depend on a single person. If the salesperson who closed the deal goes on vacation, the knowledge doesn’t go with them. A well-implemented ERP is already the foundation of that repository; AI makes it queryable and actionable.
5. Retention and expansion: being proactive at scale
Revenue retention is the most enduring commercial indicator, and the most dependent on what happens after the sale. The historical problem has been scale: it’s impossible to monitor account by account manually. With continuous scoring of churn risk and expansion opportunities, triggered by behavioral and operational signals, the team acts at the right moment and not when the customer has already decided to leave.
Organized data first, AI second
There’s a conclusion that runs through everything above: without organized and governed data, AI doesn’t perform. It may sound unspectacular, but it’s the part that separates a project that works from a pretty demo. A model that works on scattered or dirty information produces convincing but wrong answers.
That’s why at Tisa we insist on order: first an ERP like Business Central that centralizes sales, purchases, inventory, and finance; on top of it, Power Platform to automate and visualize; and above that, AI applied by measurable use case, not "AI for the sake of having AI." That order protects the investment and avoids chasing fads.
How Tisa brings it down to earth in your company
There’s no need to reinvent your sales organization overnight. The honest starting point is a question: where does value for your customer get stuck because information, authority, and action are separated? From there you prioritize.
- Organize commercial data in Business Central so that decisions don’t depend on emails.
- Automate approvals, quotes, and notifications with Power Automate to remove friction.
- Exploit the information with Power BI and make the leap to a concrete and measurable AI use case.
We are a Microsoft Partner and ISV with more than 30 years implementing management solutions in retail, distribution, construction, industry, hospitality, and services. We know the sector and provide long-term support, without promising what can’t be demonstrated.
If you want to assess where to start, let’s talk. We offer no-obligation advice to detect where AI and automation can deliver real results in your sales process. Write to us at info@grupotisa.com, call us at (+34) 971 305 885, or visit grupotisa.com.
Reference source: Jan Gilg, "The AI-Powered Go-to-Market Organization Isn’t Just a Vision Anymore", SAP News Center (news.sap.com, 2026).