As we move into 2026, enterprise technology is experiencing a major shift within the systems companies rely on most: their Enterprise Resource Planning (ERP) systems. What were once primarily systems of record are rapidly evolving into intelligent platforms that influence how businesses plan, execute, and compete.
Every major ERP vendor—from SAP to Oracle—is prioritizing initiatives to embed, extend, and operationalize GenAI capabilities for their customers.
This shift marks a turning point: ERPs are no longer just transactional backbones, but emerging decision engines at the center of enterprise technology transformation.
From Embedded AI to Intelligent ERP Ecosystems
Over the past two years, ERP providers have significantly expanded native AI features within their platforms. Embedded AI strategy capabilities such as automated invoice processing, predictive forecasting, exception handling, and intelligent recommendations are becoming standard. This first wave of AI is familiar and incremental. It’s predictable, increasingly mature, and a natural extension of a decade-long push toward automation and analytics inside the ERP.
But the real transformation is only beginning.
ERP vendors are now building open AI ecosystems that extend beyond the core platform. These frameworks allow organizations to create copilots, agents, and intelligence layers that operate across systems—not just inside the ERP. Enterprises can now combine ERP enterprise data with CRM, supply chain, HR, and custom application enterprise data to build GenAI-powered agents that analyze, recommend, and even write back into core systems.
This shift fundamentally changes the role of the ERP from a closed transactional system to an orchestrator of enterprise intelligence. While these ecosystems are still early in maturity, they set the stage for much deeper automation and decision support.
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To learn more about this evolution and what it means for organizations today, watch our recent eChannelNEWS video interview: Syntax: The Future of ERP Systems.
Why Enterprise Data Becomes the Deciding Factor
As ERPs open up, one truth becomes unavoidable: GenAI is only as good as the data behind it.
ERP systems contain the enterprise’s most critical enterprise data, including financials, orders, procurement records, manufacturing signals, and supply chain events. This data is essential fuel for GenAI, but only if it is accurate, governed, and accessible across systems.
Poor data quality inside and outside the ERP, fragmented architectures, and inconsistent governance will quickly undermine trust in AI-driven outcomes.
As model capabilities accelerate in 2026, organizations will face mounting pressure to modernize not just their AI strategy, but the data foundations that support them. Those that invest early in enterprise data integration, governance, and connectivity will unlock meaningful gains in automation and operational intelligence. Those that don’t will see AI strategy initiatives stall under the weight of legacy complexity.
This is what’s driving three major technology shifts we’ll see unfold in 2026.
1. ERP Modernization Will Become the Hidden Battleground for AI Readiness
As AI becomes essential for real-time decision making and operational agility, many organizations will confront an uncomfortable reality: their ERP environments are not ready to support it.
Modern AI workloads require real-time enterprise data access, scalable cloud infrastructure, standardized processes, and open integration patterns. Yet many enterprises continue to rely on heavily customized, on-premises SAP and Oracle systems that were never designed for this level of flexibility.
To bridge this gap, forward-looking organizations will accelerate selective modernization efforts, including:
- Migrating critical ERP modules to SaaS
- Reducing customizations in favor of standard processes
- Harmonizing enterprise data models across systems
- Enabling real-time integration capabilities
Companies that delay ERP modernization can still experiment with AI, but only at the edges. The core processes that drive the most value will remain out of reach.
2. Modernizing to the Cloud Will Become a Now or Never Mandate
For years, many enterprises postponed large-scale modernization initiatives due to cost, complexity, and risk. Incremental improvements felt safer.
GenAI changes that equation.
AI’s value—automation, intelligent decision making, and predictive insights—depends entirely on unified, high-quality enterprise data. Legacy ERP landscapes and disconnected systems trap data in silos, preventing AI from operating with consistency or confidence.
By 2026, the question will no longer be whether to modernize, but whether organizations can modernize fast enough to stay competitive.
Expect IT leaders to:
- Accelerate cloud migrations
- Eliminate long-standing data silos
- Rebuild integration architectures
- Strengthen enterprise-wide data governance
At this point, the cloud is no longer a future initiative. It’s the baseline requirement for operationalizing AI at scale.
3. Data Consolidation Will Become the Foundation for Unlocking Value from Next-Gen Technologies
As AI strategy and initiatives mature, organizations will increasingly recognize that technology alone does not create transformation—data does. AI, analytics, and automation are only as powerful as the data that fuels them.
This year, many enterprises will recalibrate digital transformation initiatives to focus first on building a trusted, integrated, and well-governed data foundation. While ERP data is often structured and reliable, the broader enterprise technology landscape is filled with unstructured, inconsistent, and poorly governed information.
To fully empower knowledge workers and elevate decision making, organizations will prioritize:
- Combining ERP data with business enterprise data outside of the ERP
- Cleansing and transforming data at scale
- Redefining governance, security, and access controls
- Establishing role-based, auditable data usage models
This renewed focus on data discipline will enable organizations to adopt AI with confidence—minimizing risk while maximizing agility. Those that strengthen their data core will be best positioned to capture the full promise of GenAI, analytics, and automation.
Where We Are Headed
This year, ERP, data, and AI strategy will no longer be separate conversations. They will be inseparable parts of a single transformation journey.
Organizations that modernize their ERP environments, dismantle data silos, and invest in strong data foundations will turn GenAI into a competitive advantage. Those that don’t may find themselves with powerful models, but no reliable way to use them where it matters most.
Why Syntax Is Uniquely Positioned to Guide Your Transformation Journey
As organizations accelerate toward an AI‑enabled future, they need more than technology. They need a partner that understands the full intersection of ERP modernization, data readiness, and GenAI adoption. This is exactly where Syntax stands apart.
With decades of deep expertise across SAP, Oracle, cloud platforms, and enterprise integration, Syntax has long supported customers through the complexities of transforming core systems while maintaining operational continuity. Today, that foundation has naturally evolved into a comprehensive approach for helping companies adopt AI safely, strategically, and at scale.
Syntax’s GenAI portfolio is designed to meet organizations wherever they are in their maturity. Our key offerings include:
- Syntax GenAI Starter Pack – Provides a low-risk, low-cost approach to AI experimentation that delivers value in weeks—without the burden of long-term commitment or vendor lock-in.
- Syntax DnA³, Digital Innovation Center of Excellence – Helps organizations build a Trusted Data Foundation that powers AI, automation, and analytics initiatives.
- Syntax AI CodeGenie – Combines streamlined SAP custom code documentation with built-in AI chatbot functionality, empowering teams to query, update, and maintain documentation with ease.
Together, these offerings form an end‑to‑end pathway—from early exploration to data readiness to AI‑enabled development—that enables organizations to operationalize GenAI in a secure and scalable way.
The pace of innovation will only accelerate in 2026. Contact us today to start your transformation journey.
Author
Marcelo Tamassia
Global Chief Technology Officer, Syntax
Marcelo Tamassia, Syntax’s Global Chief Technology Officer, drives the company’s technology and innovation strategies. With over two decades in technology, Marcelo emphasizes empowering individuals to provide exceptional solutions. He holds advanced certifications from AWS, Oracle, and Microsoft, along with an MBA from the University of Florida and postgraduate education from Stanford University, underscoring his commitment to continuous learning and excellence.