Artificial intelligence-driven ERP solutions are no longer just a promising technology on the horizon—they are here, reshaping enterprise management as we know it. Advanced AI tools can now automate complex processes, predict trends, and make recommendations for smarter decision-making. The technology is already helping enterprises boost their performance and profit margins. This makes AI adoption more vital than ever for companies wanting to protect their competitive edge.

However, choosing the wrong AI capabilities can prove costly, wasting precious resources and stunting future growth. With a well-planned, strategic approach, businesses can secure a strong return on their AI in ERP investments.

At SAP, we’ve helped customers across industries navigate their AI transformations. Along the way, we’ve found that AI implementation doesn't need to be a dramatic overhaul. Modest, practical changes can still yield rich rewards now, all while laying a solid foundation for future innovation. Consider incorporating these realistic best practices to jump-start your own successful AI adoption journey.

1. Start your AI journey with a cloud-first strategy

AI and cloud connectivity go hand in hand, as cloud-based systems offer the only way for most businesses to access data-driven intelligence. AI models require intense computing power far beyond average on-premises IT systems. AI solutions also need real-time, accurate data to understand your unique business context. Enterprise management cloud applications help resolve these roadblocks by offering an agile, cost-effective platform for deploying new AI models and managing data from multiple sources.

With this in mind, build your cloud infrastructure first before diving into any major AI investments. SAP Business Suite streamlines this process by combining AI and data capabilities with cloud enterprise management applications like SAP Cloud ERP—all supported by SAP Business Technology Platform. Cloud connectivity helps harmonize data across SAP and third-party systems, building a solid foundation to fuel AI. By uniting applications across different business areas, the cloud also enables AI to perform complex, cross-functional roles.

2. Prioritize AI practicality over hype

AI promises sweeping business transformations, changing the way we work. But businesses shouldn’t just adopt AI for AI’s sake. Enterprises should first determine their operational gaps and build their AI strategy from there. To identify AI solutions that target your strategic goals:

Define specific business cases for AI integration

Outline your specific business cases for adopting AI, using data to establish clear baselines and performance targets. Business cases pinpoint exactly what problems AI can help you solve—like reducing costs, improving customer service, or increasing efficiency. With precise numbers, you can also track metrics over time to determine your ROI. This approach guides you toward AI capabilities that actually align with your business goals.

Make end users part of your AI adoption journey

AI solutions ultimately need to fulfill end users’ real-world requirements, so actively engage them in the AI implementation process. They can help identify current pain points in your enterprise resource planning processes that could benefit from AI integration.

3. Start small and build your AI on a foundation of trust

More people are turning to AI in their daily personal lives. But for high-stakes, real-world business scenarios, many naturally feel cautious about the technology’s reliability and accuracy. To earn your team’s confidence, start small. Introduce a few relevant business AI use cases and collect feedback from end users to assess their practical value. From there, you can better identify which areas require additional AI capabilities. This approach also encourages user buy-in by showing how AI can actively improve their work experience.

Examples of AI technology for ERP platforms

AI-powered productivity tools offer end users an accessible and convenient way to explore the technology. At SAP, we’ve simplified the adoption process even further by embedding these tools into SAP business applications, including SAP Cloud ERP. See which of these common productivity features best fit your operational goals:

• Smart search and summarization
  AI-driven search and smart summarization make finding and sharing relevant business information more intuitive and efficient. Built into SAP S/4HANA Cloud Public Edition, AI-enabled features let you simplify complex search filters with natural language queries. You can then use AI to automatically identify and summarize relevant information to share with your team.
• AI virtual assistants
  In-app AI assistants help boost productivity by answering queries and automating manual processes. No special technical skills are required, as end users can give instructions and access insights through simple natural language requests. SAP’s AI copilot Joule integrates these intelligent assistance features into SAP Cloud ERP, using your business data to accelerate tasks and automate complex workflows.
• Intelligent automation
  Reduce manual data processing by automatically extracting and validating information from unstructured sources—transforming scattered data into usable assets. For example, SAP’s AI processing tools can automatically create sales orders by retrieving accurate information from different e-mails and PDF forms. With this tool, sales teams can reduce manual workloads, improve accuracy, and cut order creation costs by 25%.
• Content creation
  Content generation tools can create personalized text and images. Using your business data, SAP’s content generation features produce even more nuanced and relevant materials. Think of AI for HR solutions that can generate job descriptions and performance goals, or AI-driven CX tools that can improve product discoverability with customized descriptions.
• Predictive analytics
  Using machine learning, AI-powered predictive analytics can quickly digest vast amounts of data to reveal actionable insights. This helps businesses better forecast potential trends and outcomes to build resilient strategies. SAP uses AI predictive analytics to enhance our solutions' planning and risk management capabilities. Finance users can deploy these tools to anticipate disruptions like payment delays, while supply chain management teams can use AI to optimize their demand planning.

4. Make autonomous ERP your ultimate goal

AI will reshape your ERP experiences as end users become more familiar with the technology. To realize AI’s full potential, however, businesses should consider autonomous ERP systems their ultimate goal. The end user will still stay in the driver’s seat. They set the task parameters and select the final course of action. But AI will automate the painstaking groundwork that doesn’t require human decision-making, reacting on users’ behalf to automate tasks. Over time, AI can learn from users’ past decisions to manage even more roles. This frees teams to concentrate on what they do best—creative problem-solving and innovation.

Build your autonomous ERP capabilities with AI agents

SAP helps bring businesses far closer to a fully autonomous ERP with Joule Agents. Grounded in your unique ERP data and processes, these specialized AI applications can autonomously perform complex, multistep workflows. Teams of ERP AI agents can also collaborate to harmonize processes across different business areas. The following Joule Agent use cases showcase just some of the technology’s transformative possibilities:

• Dispute Resolution Agents
  Automatically resolve everyday disputes across different business areas, from customer service cases to invoice discrepancies. These agents can analyze communication exchanges and related documents to validate data and find errors. From there, they can recommend resolutions and execute them with your approval.
• Sourcing Agents
  Streamline the sourcing process by automating the research workload. Sourcing Agents can scan scattered supplier information, identify key data, and recommend candidates that best fit your stated criteria. With your confirmation, they can automatically fill and manage purchase orders.
• Case Classification Agents
  Streamline requests with agents that can classify and route complex cases, collect relevant data, and quickly offer solutions aligned with your company's policies. For example, customer service-focused agents can organize customer tickets and proactively offer solutions. These agents can also track results from resolved cases to fine-tune their service performance over time.
• Accounting Accrual Agents
  Improve your accrual and deferral forecasts while reducing your data entry and calculation times by 80%. Available now for beta testing, Accounting Accrual Agents can automatically analyze your historical data and planning information to verify estimations and find any fluctuations. This lets your finance teams avoid the month-end close rush and focus on more value-adding tasks.

Combining business AI and ERP software doesn't have to be an overwhelming task. By starting small and focusing on practical, relevant solutions, you can build trust, foster adoption, and pave the way for future, more ambitious AI-driven initiatives. With this approach, AI can become a powerful ally supporting your resilience and growth.