In recent years, many technologies have been touted as disruptive, with words like “game-changer” and “revolutionary” overused to the point of becoming buzzwords. At SAP, we’ve been helping businesses bring out their best through technology and expert guidance since 1972. Over the years, we’ve seen many technologies dubbed disruptive, but if there’s one real game-changer today that we think companies shouldn’t miss, it’s AI.

At its best, AI can be a true catalyst of human potential, helping get things done faster and simplifying routine tasks. Advancements in generative AI and machine learning have made a wide range of AI applications universally accessible—such as conversational assistants, sentiment analysis, coding copilots, gaining insights from unstructured data, information summarization, and content generation. The value of AI for enterprises is clear: it helps organizations become more efficient, empower their people, and elevate operational excellence. However, an ineffective AI adoption strategy can hinder implementation and turn introducing AI in companies into a challenge.

Organizations across the globe are already finding countless uses for AI. For example, one of our customers, American food company Chobani, uses SAP Business AI embedded in SAP Concur solutions to automate expense processes, reducing time spent on expenses by 75%. Another, professional e-sports organization Team Liquid, uses SAP Business AI-generated opponents for a competitive edge in e-sports and saved 10,000 hours of manual work by using generative AI to get insights from match data. The list goes on, and the potential is clear.

In enterprises, AI adoption requires strategic planning, a cultural shift in the organization, and purposeful integration with existing business processes. Through SAP MaxAttention, customers can take advantage of our extensive expertise in business transformation to make their company-wide AI adoption smooth and effective.

What is SAP MaxAttention?

SAP MaxAttention is a long-term, premium engagement that helps companies achieve their expected results with SAP solutions and offerings, including RISE with SAP, SAP S/4 HANA Cloud, SAP Business Technology Platform (SAP BTP), North Star service, and the SAP cloud ERP portfolio. It supports companies through long-term transformation journeys and maximizes the value of their SAP investments by providing on-site SAP expert advisors, tools, training, support, methodologies, and other resources. With agile cloud solutions and innovative capabilities, SAP MaxAttention helps businesses build a clean core strategy and future-ready enterprise architecture capable of smooth adoption of innovations, including AI.

This engagement supports large-scale business transformation across multiple solutions, lines of business, and processes—now including SAP Business AI.

What is SAP Business AI?

SAP Business AI refers to AI features and capabilities embedded into solutions across the SAP portfolio. SAP Business AI empowers enterprise efficiency and smart decision-making at scale, while maintaining commitment to responsibility, compliance, and building trust.

SAP Business AI capabilities and SAP applications work in synergy—here are just a few examples that’ll give you an idea how impactful it can be:

• In SAP S/4HANA Cloud, there are many embedded AI use cases

• In the SAP HANA Cloud Vector engine, we can vectorize tabular SAP data, which allows it to be processed for generative AI use cases

• SAP SuccessFactors solutions provide AI-assisted personalized learning recommendations to millions of learners every month

• In SAP Concur Invoice Management, AI helps automate the processing of invoices, which allows customers to save time and money

• On SAP BTP, AI helps compress upgrade cycles and simplify IT stacks by modernizing legacy code through automated code generation

• Through capabilities like AI-powered code generation and test script creation, AI can support application development, saving time and effort

In other words, SAP Business AI enables generative AI use cases that bring tangible value across our entire portfolio. Moreover, SAP fine-tunes generic large language models (LLMs) on anonymized SAP data and even creates proprietary foundation models based on our structured business data. These models can address organization-specific objectives that generic models cannot, such as predicting invoice payment dates or proposing improvements to a business process based on your enterprise-specific data.

Customers can also interact with SAP software in a natural, intuitive way through Joule, SAP’s AI copilot that leverages the company’s business data and process context to assist with various tasks. Thanks to its generative AI capabilities, Joule can interpret input in natural language: users can simply tell Joule what to do—or ask a question, in their own words, just like they’d ask a colleague.

SAP MaxAttention for AI transformation

What makes SAP MaxAttention well-positioned to help organizations introduce AI? To help companies proactively shape their IT strategy and enterprise architecture, SAP MaxAttention offers a structured engagement model with teams of SAP experts, for example the SAP Mission Control Center and the SAP Transformation Hub. And now that its coverage extends to SAP Business AI, SAP MaxAttention brings all its resources and extensive business transformation expertise—to support company-wide AI adoption journeys.

How to effectively introduce the use of AI in companies

So, let’s imagine an effective and smooth AI transformation across an organization: no bottlenecks, no inefficient use of resources, no slowdowns—the absolute best-case scenario. What would it take to make this vision reality? To answer that, we considered the common challenges and needs seen across our customers’ AI-adoption journeys. That’s how we identified several elements key to supporting a holistic company-wide AI transformation:

Building foundations for AI adoption

Research and preliminary evaluation of AI readiness and potential lay a strong foundation for introducing AI in companies. In other words, this stage is all about planning and preparation. We use it to establish a clear understanding of the business value from introducing AI: what it’ll do for the company, and which AI use cases are relevant.

Companies can approach this stage in a few different ways, but here’s how we do it at SAP. The SAP MaxAttention team conducts a deep-dive assessment and some preliminary research to address objectives like:

• Assess the customer’s business processes for areas that AI can improve

• Identify and prioritize SAP Business AI solutions that would benefit the customer

• Clearly outline the business benefits of suggested solutions: for example, generative AI capabilities, data-driven insights, and automation

• Explain integration aspects and transition possibilities from the architecture standpoint

• Design and discuss a to-be architecture

• Explain data, process, and technical requirements

• Provide a live system demo of AI use cases

Tailored AI strategy development

The next crucial objective in the process is to build a comprehensive AI strategy tailored to the organization’s specific needs and starting conditions. Again, some companies might approach it differently, but our recommendation is to create a customized roadmap for AI adoption and already start to prioritize security and compliance.

Here’s how SAP MaxAttention experts would approach this task when supporting our customers:

• Assess innovation maturity: collect relevant quantitative and qualitative data and define roles and stakeholders involved in the AI adoption journey—and its future use

• Build an effective project governance model; in other words, define who and how will see AI transformation through

• Provide expert guidance on AI best practices, latest generative AI technologies, and innovative uses of AI for business

• Design the best-fitting AI architecture, data strategy, modeling, and operations

• Run a risk assessment, secure operations, and set up protection of business and personal data

• Ensure that the use of AI is responsible and transparent

Implementation and deployment of AI

Once the AI strategy is clear, the roadmap is built, and all prerequisites are met, it’s time to start putting it all into action. This is a crucial stage in AI transformation. It will test how comprehensive the preparations have been: the more organized and thorough the company has been with the previous steps, the smoother this execution phase can be.

There are two approaches to implementation that we offer.

Activating embedded AI in SAP solutions allows us to carry out a fast, straightforward, and efficient realization of a proof-of-concept to achieve a quick AI implementation.

Building a custom AI model is a more resource-intensive but flexible approach, which involves training a unique model on the customer’s SAP and non-SAP data. In this case, the custom AI model can then be safely used with both SAP infrastructure and third-party data—even with another LLM (for example, ChatGPT).

Here’s how SAP MaxAttention experts would make implementation even more effective:

• Create a proof of concept or pilot, using the customer’s business data

• Empower business and system administrators to deploy, maintain, and monitor AI scenarios related to their roles

• Provide training and education to stakeholders that need AI skills

• Upskill the customer’s IT teams on AI technologies: for example, through workshops, presentations, and hand-on exercises in sandboxes or trial environments

• Integrate AI into the existing process landscape

Depending on the approach chosen, additional options may be available:

Embedded AI solutions

• Validate the embedded AI model

• Assess data quality and give guidance on improving it

Custom-built AI model

• Collect, prepare, and govern data to ensure its fit for AI applications—a crucial component of this process is vectorizing tabular data in the SAP HANA Cloud Vector engine

• Build SAP BTP solution architecture to utilize the custom AI model in your landscape

• Train a customer-specific AI model

• Configure the safe use of the customer’s SAP data with a third-party LLM

Monitoring, supporting, and optimizing the use of AI

Once the new AI processes are implemented, the work continues: it’s time to analyze, support, and expand the use of AI for business goals. This way, we can see how well everything’s working and address any unexpected challenges. It’s also a good time to start thinking further: about expanding the use of AI to other areas of business or building new workflows on its capabilities.

When SAP MaxAttention customers are at this stage, we focus on goals such as:

• Demonstrate value and outcomes of the AI implementation

• Resolve any issues that come up after implementation

• Assess, optimize, and train the AI models and adjust to emerging trends

AI adoption for organizations: key takeaways

AI has a vast potential for empowering companies to perform at their best, so the impact of getting AI transformation right can be tremendous. But ultimately, using AI in companies is most impactful when it’s implemented purposefully and strategically. That’s why we recommend a comprehensive approach to introducing and running AI initiatives.

AI adoption doesn’t have to be a daunting task, even for a global enterprise with a complex architecture. SAP MaxAttention offers both tools and expertise to approach AI adoption holistically: from devising a tailored AI-ready strategy—to execution, optimization, and continued support.

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