Companies have moved from their first steps with AI to adopting the technology more broadly. This means that the question of business benefit is in the foreground for them. By using AI, business leaders want to achieve results they can trust, make consistent decisions, and create experiences that delight customers.
AI will establish itself as a permanent fixture in 2026: It will be an important part of companies’ everyday business, based on their data and processes and reflecting their interaction with customers. With customer-specific AI, daily business processes are supplemented with intelligent functions. It supports teams with complex tasks and enables better decisions across the entire company. Human judgment is clearly the focus here. This development forms the starting point for the next phase of AI introduction. Companies are moving from generic tools to intelligent capabilities that understand their business operations and become more powerful with every customer interaction.
1. Better customer decisions through relevant AI
As AI becomes increasingly important in customer-related decisions, accuracy and relevance are essential. Generic models are often unable to understand context and correctly interpret nuanced customer scenarios with a variety of exceptions. Custom AI trained with company data, on the other hand, can recognize a company’s unique patterns, such as common types of dispute cases, bottlenecks in resolving these cases, or region-specific customer service behaviors. According to the “SAP Value of AI Report,” written by SAP in collaboration with Oxford Economics, 36% of companies have already successfully used AI to address customer-related challenges, including improving interactions with customers. The greatest benefit can be achieved when intelligent functions not only abstractly anticipate but accurately reflect the way customers interact with the company.
2. Scaling complex processes without loss of control
The best results can be achieved with custom AI when customer processes are scaled at a pace that manual intervention cannot keep up with. Returns, exchanging goods, resolving disputes, processing claims and customer service exceptions affect various systems, rules and decision-making processes. AI that understands business context can scale these processes while still ensuring consistency, governance and accountability. This allows companies to manage increasing work volumes while ensuring predictable results and consistent service quality.
3. Supporting increasingly better differentiation from competitors
Unlike general AI capabilities that are accessible to a wide range of audiences, custom AI is largely based on the company’s proprietary information, policies and internal know-how. This allows companies to gradually gain insights that are very closely aligned with their business processes – and are therefore increasingly difficult for competitors to replicate. The more the system learns from real customer interactions, the better the company can use it to differentiate itself from competitors.
4. Where custom AI provides the greatest value
The value of custom AI is particularly evident in high-volume environments, where exceptions abound. A large European consumer goods manufacturer is showing the advantages that AI can bring in managing dispute cases, returns and exchanging goods. The company, which has offices in multiple regions and manufactures various product lines, struggled with lengthy dispute resolution, inconsistent results, and high manual effort. By implementing AI trained on historical disputes, order data, pricing rules, and dispute resolution workflows, the company integrated intelligence directly into its processes. Custom AI can automatically classify incoming cases, retrieve relevant documentation, and recommend solutions based on previous case results and policies. Efficient case routing ensures less coordination and less manual effort is required. Most importantly, the system evolves as policies and customer behavior change. In doing so, it supports people’s decision-making rather than replacing it. In this way, the company benefits from a consistent and scalable approach to processing disputes more quickly.
5. Increasing use of integrated intelligence across industries
These fundamental benefits extend far beyond managing dispute cases. In manufacturing and the supply chain, customer-specific AI supports order fulfillment exceptions and service level agreement resolution cases. In the financial services sector, complaints can be processed in accordance with the legal framework. In healthcare, custom AI enables decisions based on hospital protocols and the patient journey. In retail and service industries, it drives relevance by analyzing and learning from customer preferences, branding guidelines and operational constraints. More and more industry observers are pointing out that it will not be stand-alone AI tools that will drive further growth in artificial intelligence, but rather intelligent functions that are integrated into customer-oriented processes. According to the “SAP Value of AI Report” from SAP in collaboration with Oxford Economics, most companies expect AI to play a central role in their business processes, decisions and offerings to customers by 2030. Only 3% disagree.
In 2026, the focus for companies will be less on whether AI is a new technology and more on whether they can achieve consistent customer and business outcomes through the use of AI. Customer-specific AI makes a decisive contribution to this development as it integrates intelligent functions directly into the processes of companies and their service to customers. This next phase of AI isn’t about replacing human judgment with system-driven decisions – it’s about supporting human decisions. By analyzing complex issues and providing contextual insights, custom AI enables faster responses, greater consistency, and secure scaling of customer-centric decision-making processes. In an increasingly complex and customer-centric landscape, companies will gain real competitive advantage by investing in intelligent solutions that truly understand their business.
Sindhu Gangadharan is Head of Customer Innovation Services and Managing Director of SAP Labs India.
