Its value is not limited to initial deployment. IT environments constantly change through patches, updates, and configuration drift, all of which can introduce operational and compliance risk. Acceptance to Run allows teams to group systems, define custom checks, and generate reports showing which systems are compliant and which are not. For example, a report may reveal that a server fails compliance because its CPU count is below the expected threshold. This makes deviations visible immediately, rather than months later after a service failure, helping organizations maintain control, reduce risk, and keep environments aligned with standards over time.

Apiphani engineers attended AWS re:Invent 2025 to assess what these changes mean for enterprises running complex, mission-critical environments. Rather than cataloging product announcements, we focused on identifying the structural shifts behind them.

Four themes stood out.

1. AWS Is Moving from AI Tools to Autonomous Operations

Across re:Invent 2025, AWS demonstrated a decisive move beyond generative AI assistants toward agentic AI (autonomous agents capable of executing operational tasks across development, infrastructure, and security). Announcements such as Bedrock AgentCore, AWS DevOps and Security Agents, and autonomous software development agents all reinforced the same direction: AI is becoming an active participant in operations, not just an advisory layer.

This represents a meaningful shift for enterprise IT. Incident detection, root-cause analysis, and remediation are no longer envisioned as purely human-driven workflows. Instead, AWS is embedding operational intelligence directly into the platform (as is apiphani), with agents designed to persist, learn, and act across systems.

For enterprises, this challenges traditional support models built around tiered escalation, manual triage, and institutional knowledge concentrated in a small number of senior engineers. Over time, organizations that successfully operationalize autonomous capabilities should see fewer incidents, faster resolution, and less operational noise — while those that don’t may struggle to keep pace with growing system complexity. 

2. Cost Optimization Is Becoming a Native Cloud Capability

Another clear emphasis at re:Invent 2025 was cost. AWS introduced new Database Savings Plans, AI-driven cost forecasting, and expanded automation across storage tiering and resource optimization. Collectively, these announcements signal that AWS is moving cost management closer to the infrastructure and runtime layers of the platform.

The implication is significant: cost optimization is no longer positioned as a separate FinOps function or a retrospective reporting exercise. Instead, it is becoming a real-time architectural and operational concern, informed by usage patterns, system behavior, and predictive models.

For enterprise IT leaders, this increases the need for tighter alignment between finance, architecture, and operations. As environments become more automated and dynamic, manual cost controls and disconnected tooling will become increasingly ineffective. The organizations that succeed will be those that design cost awareness directly into how systems are built and operated.

3. Serverless and Traditional Compute Are Converging

AWS also continued to blur the line between serverless and traditional compute. Enhancements such as Lambda Durable Functions, Lambda Managed Instances, and next-generation Graviton processors point toward a convergence of execution models.

Long-running, stateful workloads can now leverage serverless patterns without sacrificing predictability or performance. At the same time, AWS is assuming more responsibility for availability, scaling, and infrastructure management.

For enterprises, this changes the nature of architectural decisions. The question is no longer simply “serverless versus servers,” but where operational responsibility should live, with application teams, internal platform teams, or the cloud provider itself.

This convergence creates opportunities to reduce operational overhead, but it also raises the bar for design discipline. Poorly architected applications will surface performance and cost issues faster than ever in highly automated environments.

4. Regulated and Hybrid Environments Are Now First-Class Design Targets

Finally, AWS made it clear that regulated, sovereign, and hybrid environments are no longer edge cases. Announcements related to AWS AI Factories, expanded hybrid capabilities, and deeper governance and security integration signal a deliberate investment in supporting industries with strict compliance, residency, and operational control requirements.

This marks an important inflection point for enterprises that have delayed modernization due to regulatory constraints. AWS is signaling that hybrid and on-premises deployments are not temporary compromises; they are strategic architectures that will continue to evolve alongside public cloud services.

For regulated enterprises, the challenge will shift from whether modernization is possible to how automation and AI can be introduced responsibly without increasing operational or compliance risk. Success will depend less on technology adoption and more on operational maturity.

Evolution of Enterprise IT Operations

Looking Ahead

Across these themes, one message from AWS re:Invent 2025 was consistent: the future of enterprise IT is autonomous, cost-aware, and deeply embedded into the operational fabric of the platform.

The organizations that benefit most will NOT be those that adopt the most services, but those that can operationalize automation, governance, and cost control across complex, mission-critical environments intentionally and responsibly.

SAP S/4HANA 2023 marks a decisive step toward the intelligent enterprise vision. Beyond being another technical upgrade, it delivers a platform where automation, embedded analytics, and AI-driven decision support come together to simplify operations and improve business outcomes.

1. Smarter Processes Through Automation

SAP has expanded automation capabilities across core business functions, eliminating repetitive tasks and enabling continuous operations. Here’s how.

SAP Build Process Automation Integration

S/4HANA 2023 integrates natively with SAP Build Process Automation (BPA) on SAP BTP, allowing customers to design low-code bots that execute SAP transactions, validate data, and trigger workflow approvals. Examples include automatic journal posting approvals, purchase order release workflows, and background invoice verifications.

Situation-Handling Enhancements

New Situation-Handling Templates automatically alert users when events deviate from expected business rules, such as delayed production orders, migration job failures, or overdue inspections. This enables the following proactive response model: The system detects, informs, and suggests corrective actions before users notice an issue.

Predictive and Preventive Maintenance

Manufacturing and supply-chain processes now benefit from machine-learning models embedded in S/4HANA 2023 that forecast equipment failures or quality issues. SAP calls this Predictive Quality Inspection — leveraging HANA ML and AI Core services. This brings true autonomous maintenance closer to reality.

2. AI and Machine Learning in Core Finance

Financial departments gain from the following intelligent features that reduce manual reconciliation and speed up close cycles:

• Machine-Learning Intercompany Reconciliation (ICR): Automatically detects and proposes matches for cross-company postings.
• Predictive Cash Flow Forecasting: Learns from historical patterns to estimate future liquidity positions.
• Smart Accruals and Automated Adjustments: Rules and ML-based triggers generate accrual postings automatically.

Together, these features redefine the Finance function as data-driven and exception-managed, rather than transaction-driven.

3. Embedded Analytics and Citizen Reporting

The 2023 release brings a new level of flexibility in embedded analytics:

• Drag-and-drop measure ordering, autofill capabilities, and bookmark sharing in the multidimensional grid.
• The “Manage KPIs and Reports” app now allows business users to create and publish analytical apps without developer help.
• PDF export and transportable bookmarks streamline management reporting.

This self-service analytics experience reduces dependency on IT, empowering functional users to become citizen analysts.

4. Governance, Security, and Master Data Intelligence

Data privacy and compliance remain a cornerstone. The new Business Partner Data Controller concept within S/4HANA 2023 introduces up to 10 controllers per record with new authorization objects for fine-grained data governance (B_BUP_DCPA, B_BUP_DCPD).

For master data synchronization, SAP Master Data Integration (MDI) enables federated governance across S/4HANA, Ariba, Concur, and SuccessFactors — a key step toward enterprise-wide data harmonization.

5. Connected Work Experiences

SAP continues bridging business processes with collaboration tools. Examples include:

• Native Microsoft Teams integration, which brings chat, file sharing, and approvals directly into Fiori apps.
• SAP Concur integration, which automates expense reconciliation and approval chains.
• Unified Attachment Service, which allows versioning, line-item attachments, and Outlook shortcuts — reducing manual document management.

The result: A connected, collaborative user experience that blends ERP transactions with modern workplace tools.

6. User Experience and Fiori 3.0 Evolution

With S/4HANA 2023, SAP further refines the Fiori 3.0 Quartz theme, improving accessibility, personalization, and tile organization.

Users can now reorder measures, create favorites, and personalize spaces according to their daily tasks. The interface feels faster, cleaner, and more consistent, which is key for adoption success.

7. Why Version 2023 Matters

S/4HANA systems running on versions 2020 or 2021 will reach end of mainstream maintenance in 2026. Upgrading to S/4HANA 2023 not only extends support but also delivers immediate value in the following ways:

• Reduced manual effort via automation
• Predictive insights embedded in business processes
• Stronger security and compliance posture
• Seamless integration with BTP automation and analytics services

8. Apiphani’s Perspective

At apiphani, we see S/4HANA 2023 as the turning point between digital core modernization and intelligent enterprise enablement.

Our AMS and BASIS teams are already helping customers upgrade to 2023 FPS03, implementing automation use cases in Finance, Supply Chain, and Basis operations (e.g., automated transport handling, archiving, and health monitoring via SAP Build).

The message to our clients is clear. Don’t treat your upgrade as a technical event. Make it a foundation for automation and intelligence.

Final Thoughts

SAP S/4HANA 2023 is more than a version update. It’s a shift toward autonomous ERP operations. By leveraging embedded AI, predictive analytics, and low-code automation, organizations can move from reactive management to proactive optimization.

If you’re still on an earlier release, the upgrade path to 2023 isn’t only about compatibility, it’s about capability.

About the Author

José López is a senior SAP technology leader with 20+ years of experience managing and optimizing mission-critical SAP environments. As Principal Director of SAP AMS, he leads end-to-end service delivery for large, complex SAP landscapes.

I recently attended Tanium’s Converge 2024 conference where IT automation was on full display. In this piece, I’ll highlight three IT automation trends I found particularly interesting along with examples of how Converge showcased these trends in action.

Real-Time Information Gathering

“The Power of Certainty” was the overarching conference theme, and Tanium put an emphasis on their ability to view your entire environment and provide immediate, accurate information. The idea is that once you understand your environment you can control it. We continue to see organizations shift towards real-time information gathering versus relying on data that could be hours or days old. For instance, Tanium can query an environment in real time to help identify systems vulnerable to zero-day exploits.

Automation tool providers, like Tanium, continue shifting towards real-time information gathering to support this need. At Converge, Tanium announced a new Automate Endpoint Management (AEM) feature which provides a confidence score for operating systems and Predefined Package Gallery updates. This confidence score is based on worldwide deployments of updates and metrics such as application crashes after the update is installed or the number of updates removed after installation. Automated playbooks can be created based on achieving a minimum confidence score, thus reducing the chance of having an update cause a problem in the environment. This automates what would typically be a burdensome administrative process to approve patches and updates. Rather than relying on people to guess that the system worked okay, organizations can now depend on automated confidence scores based on real data.

Integration and Automation Across Platforms

Due to the industry shift towards cloud-based SaaS solutions (e.g. the cloud versions of Tanium and ServiceNow), more teams are operating in cloud environments and looking for ways to automate across platforms and improve data integration. APIs have made integrating data more straightforward compared to on-premises solutions that are typically more difficult and time consuming.

At Converge, we saw how ServiceNow and Tanium are using modules in ServiceNow that can trigger actions in Tanium enabling two-way communication and automating the process of patching through the ServiceNow change control process.

As more solutions make additional functionality available through APIs, we’ll continue to see the trend of automation across toolsets. Apiphani is already taking advantage of similar integration across systems and our team is excited to see what additional capabilities will become available in the year ahead.

The Role of AI

The final trend I’d like to highlight is how artificial intelligence (AI) is being used to achieve automation. At Converge, it was interesting to see how AI is aiding features such as Tanium Ask, a natural language using AI to interpret the need and then interpret that into code that Tanium can use to fetch the information.

This is part of a larger industry trend where more tool providers are leveraging AI to assist developers with natural language coding and scripting.  For example, rather than doing research, a time intensive task, I can ask AI to put together a script that performs a task and proofread it to achieve speed and accuracy. That’s exactly how AI is being leveraged in this scenario. In the military this is referred to as a force multiplier – the idea that you can make an individual more efficient and achieve greater productivity.

Converge also highlighted an interesting integration between Tanium and Microsoft Copilot for Security In this instance, Tanium collects information that is both current and accurate, and feeds that into Microsoft’s security platform. AI is then used to identify potential security vulnerabilities. This allows Copilot to more effectively summarize vast data signals into key insights. We can expect this trend to continue as more tools integrate AI for various use cases to aid automation in security and beyond.

Closing Thoughts

Having accurate, reliable data that you can analyze quickly is a powerful tool in any IT stack. Through the power of IT automation, that process is constantly improving so we can all leverage these solutions to pair the best tools with the most skilled people to achieve the right approach. Tanium has provided a framework for integration to achieve the level of automation that organizations can then build upon to import or export data and processes to realize desired outcomes. The innovative solutions and partnerships highlighted at Tanium Converge 2024 will enhance how we serve our customers at apiphani, and we’re eagerly anticipating next year’s event.

The pipeline enables integration across cloud environments, databases, and third-party applications while supporting domain-driven data strategy and structured investment prioritization. It also includes migrating existing analytics environments using modern best practices for development and deployment, with the stated goal of accelerating data delivery and reducing total cost of ownership.

Deep Automation™ leverages machine learning to detect anomalous behavior, propose remediation actions to engineers, and execute approved solutions automatically, reducing dependence on traditional L1 and L2 support layers and significantly accelerating resolution times. The model combines automation with senior technical expertise, aiming to improve reliability, reduce human error, and enhance operational performance for mission-critical systems.