In 2026, AI has moved from being experimental to being a company’s determinant of its success by how it prioritises and controls its business models according to AI. AI has become deeply embedded in corporate operations, driving productivity, efficiency and innovation.
AI is used for automation and analytics, and since that is the cornerstone of AppConverge's business, the company is teaming up with SAP to address challenges companies encounter, such as high initial costs, complexity and lack of knowledge, security and privacy issues and job displacement, and realise benefits like process automation, improved decision-making, personalisation and customer experience, and efficiency and cost reduction.
To successfully adopt SAP Business AI, companies need to focus on preparing their data, upgrading their technical infrastructure to cloud-based solutions and retraining their workforce to work alongside AI agents like Joule. SAP’s approach embeds AI directly into applications (eg, S/4HANA, SuccessFactors) based on principles of being relevant, reliable and responsible.
Here is a breakdown of what companies need to do:
1. Implement SAP BTP:
- SAP BTP is essential as the central foundation, providing AI services, integration tools and access to the generative AI hub.
Prepare data and infrastructure
- Clean and organise data: AI requires high-quality, structured data to work effectively. Companies must audit, clean and govern their data, often using SAP Master Data Governance (MDG) to ensure consistency.
- Move to the cloud: While some AI features can work on on-premises platforms, maximum capability is achieved through SAP S/4HANA Cloud and SAP Business Technology Platform (BTP).
2. Define AI strategy and use cases
- Identify high-impact scenarios: Focus on areas that offer immediate ROI, such as automating invoice processing, improving demand forecasting or enhancing HR onboarding.
- Set clear goals (SMART): Define specific, measurable objectives, such as reducing invoice processing time by 40% or increasing employee engagement by 20%.
- Establish governance: Develop ethical guidelines for AI use, ensuring data privacy and human-in-the-loop oversight to avoid bias.
3. Implement and configure SAP AI solutions
- Activate Joule Copilot: Deploy Joule, SAP's generative AI assistant, to act as a role-based teammate in tasks.
- Utilise SAP AI Core: Use SAP AI Core and AI Launchpad to manage, deploy and monitor custom machine learning models.
- Leverage pre-built services: Activate specialised AI business services for document information extraction, service ticket classification and data matching.
4. Enable the workforce and culture
- AI enables continuous processes that make annual or quarterly rituals obsolete, transforming performance management from retrospective judgment into real-time development.
- Cultivate an innovative culture: Encourage teams to explore AI use cases and adopt new, AI-driven workflows.
- Adapt roles: Redesign jobs to move away from manual data entry towards supervising AI outputs and focusing on strategic, high-value tasks.
- Upskill employees: Train staff in AI literacy, prompt engineering and managing AI.
5. Manage costs and continuous improvement
- Understand consumption-based pricing: Utilise SAP AI Units for premium, consumption-based AI services, allowing flexibility based on usage.
- Monitor performance: Continuously audit AI performance, retraining models to ensure accuracy and relevance over time.
- By following these steps, companies can turn data-driven insights into actionable business outcomes, such as accelerating invoice processing by 90% or reducing supply chain disruptions.
AppConverge is always committed to driving inclusion, innovation and impact in the technology and implementation space. The company believes AI is more than an emerging technology – it is an opportunity to transform the way organisations collaborate, manage information and make data-driven decisions.
Share
Editorial contacts