How AI in SAP AMS is Redefining SAP Application Management

As SAP landscapes continue to evolve across cloud and hybrid environments, traditional support approaches are struggling to keep pace. Organizations today need more than reactive ticket resolution. They need intelligent, scalable support models that improve visibility, increase efficiency, and help teams focus on higher-value initiatives.

In the lead up to SAP Sapphire, Syntax introduced its AI-First Application Managed Services (AMS). Syntax’s SAP AMS combines AI-driven automation with deep SAP expertise and dedicated teams to help organizations meet those changing expectations and get more value from their SAP investments.

To discuss why application support is evolving and how Syntax is ahead of the trend, we sat down with Alain Dupont, Global Senior Vice President, AMS at Syntax. The following is Part One of our conversation.

Q: Why are traditional support models no longer enough to manage SAP environments and deliver business-aligned incremental value?

There are really three reasons why traditional SAP AMS models aren’t enough anymore.

• First: The expectations placed on SAP have changed significantly. Businesses are under constant pressure to adopt new technologies, move faster, and support growth and transformation initiatives. SAP is no longer just a system of record. It’s expected to help drive business outcomes. Many traditional support models were designed primarily to keep systems running, not to help organizations evolve their environments as business needs change.

• Second: SAP landscapes have become much more complex than they were even a few years ago. If you look at what most organizations are managing today, it’s a very different environment from the traditional on-premises ERP world. We’re dealing with cloud adoption, hybrid environments, increasing cybersecurity requirements, AI-driven innovation, and much higher expectations from the business. In many cases, that complexity has outgrown the capabilities of legacy support structures.

• Third: Many organizations are still measuring SAP AMS success using metrics that belong to a different era. Traditional SAP AMS models were built around tickets and SLAs. Those things still matter, of course, but they can’t be the only measures of success anymore. Today, organizations are looking for ways to reduce complexity, improve resilience, support transformation initiatives, and create more capacity for innovation. Simply reacting to incidents isn’t enough.

What we’re seeing from leading organizations is a shift toward a much more proactive model. They want to prevent issues before they occur, automate repetitive work, improve visibility across their environments, and align IT operations more closely with business priorities.

The conversation is becoming less about resolving tickets and more about eliminating unnecessary work altogether while creating better business outcomes.

Q: How does AI-First SAP AMS deliver incremental business-aligned value and meet the demands of modern SAP environments?

At Syntax, we think about this through a framework we call Run, Grow, Innovate. We developed it because, in our experience, organizations need more than support that simply keeps systems running. They need a model that helps them operate efficiently today while creating the capacity to improve and evolve.

The first priority is to Run the environment effectively. If the business doesn’t trust the stability and reliability of its core systems, everything else becomes more difficult. That’s where we focus on reducing operational noise, improving visibility, automating routine work, and identifying issues before they become business disruptions. AI plays an important role here because it helps us monitor environments more intelligently, accelerate analysis, and reduce the amount of manual effort required to support day-to-day operations.

Once that foundation is in place, organizations can focus on Grow. At that stage, the conversation shifts from maintaining systems to getting more value from them. We help customers optimize business processes, improve performance, identify efficiencies, and ensure their SAP environment is aligned with changing business priorities. The goal is to help organizations get the maximum return from their SAP investments.

From there, organizations are in a much better position to Innovate. That could mean cloud adoption, increased automation, AI integration, process modernization, or broader transformation initiatives. One thing we’ve consistently seen is that innovation is much easier when teams aren’t spending their time dealing with operational issues. Organizations move faster when they have confidence in the stability of their core systems.

The progression is intentional. One mistake companies sometimes make is trying to accelerate transformation while still struggling with operational complexity. In our experience, the organizations that get the most value from innovation initiatives are usually the ones that have already established operational discipline and stability.

That’s where AI-First AMS comes in. We use AI throughout the support lifecycle to automate repetitive activities, improve traceability, surface insights, and help our teams respond more effectively. This isn’t about replacing SAP expertise. It’s about allowing experienced SAP professionals to spend less time on repetitive support tasks and more time helping customers solve business problems and drive improvement.

Ultimately, our objective is straightforward: help customers reduce the amount they spend keeping the lights on so they can invest more in growth, innovation, and transformation.

Through our flexible “Syntax Bank” approach, customers can redirect Run spend toward higher-value activities such as change requests, enhancements, and continuous optimization initiatives.

Q: Do you have any real-world results of adopting AI-First AMS?

Yes, and what we’ve found is that the benefits tend to show up relatively quickly.

When AI is embedded directly into SAP operations, it helps automate repetitive tasks, accelerate root cause analysis, identify optimization opportunities, and provide insights that would otherwise require significant manual effort. The result is a support organization that spends less time reacting and more time improving the environment.

What we’re seeing in customer engagements today includes:

• Up to 40% reduction in support efforts
• Up to 20% decrease in support costs
• 51% faster resolution times
• 84% human-equivalent accuracy
• 12% of tickets resolved without any human in the loop

We have strong customer examples that support those results. Novexco, one of our early adopters, reported a 96% solution-accuracy rate while reducing turnaround times from hours to less than an hour.

Other customers have highlighted benefits such as accelerated solution design, reduced total cost of ownership, and greater ability to focus internal resources on strategic priorities rather than day-to-day support activities.

The biggest difference between AI-First AMS and traditional support models is that we’re not simply trying to react faster when something goes wrong. We’re preventing avoidable work, identifying issues earlier, and continuously improving the environment over time. That’s what drives the results we’re seeing today.

Q: What kind of business impact can organizations expect beyond operational efficiency?

This is where the conversation gets really interesting. Reducing tickets and improving support metrics is valuable, but that’s not the outcome most business leaders care about. The real value comes from the capacity organizations regain when support operations become more intelligent and more automated.

When teams spend less time dealing with repetitive issues, they have more time to focus on process improvement, user experience, modernization initiatives, and innovation. Instead of constantly reacting, they can spend more time moving the business forward.

That’s also when organizations begin to realize more value from their SAP investments. IT operations become better aligned with business priorities, decision-making becomes faster, and teams can support change more effectively.

We also see a significant impact on an organization’s ability to grow and transform. A stable, transparent, and optimized SAP environment gives leaders greater confidence to modernize processes, adopt new technologies, and pursue strategic initiatives.

There is an economic dimension to this as well. Modern SAP AMS needs to be evaluated differently than it was in the past. It’s not just about how quickly tickets are closed. It’s about how much avoidable work never had to happen in the first place. It’s about how many hours can be redirected toward higher-value activities. It’s about how effectively the organization can absorb change without increasing operational complexity.

That’s why we don’t view AI-First AMS as simply a more efficient support model. We see it as a way to help organizations operate more strategically, create additional capacity for growth, and build a stronger competitive position over time.

Stay tuned for Part Two of our blog series, which will focus on what organizations should consider in SAP application management services from a partner.

In the meantime, to learn more, read our AI-First AMS brochure and contact our team today.