by Christian Klein, CEO of SAP SE
When it comes to investments in artificial intelligence (AI), the numbers are staggering. “Stargate”, a U.S. initiative to build the largest AI data centers the world has ever seen, aims to invest $500 billion over the next four years. Saudi-Arabia and the United Arab Emirates just announced plans to buy hundreds of thousands of advanced AI chips. And at France’s “AI Action Summit” earlier this year, public and private actors pledged investments surpassing €300 billion to advance AI in Europe.
It is very clear that expectations about the economic benefits of this technology are sky high. Yet, a recent McKinsey survey found that more than 80% of organizations worldwide are not yet seeing any tangible impact on their profits.[1] So where does this mismatch come from?
The key to the answer is that AI is not a stand-alone technology. For its benefits to materialize, AI has to be deeply embedded in business processes. And for that, companies have to put three pillars in place: modern cloud software, modern data management, and a consistent stack of AI technologies linking with them.
Let’s start with software: All successful companies use software to organize and optimize their business operations – from order intake and procurement to production, delivery and customer service. Yet, many enterprises still rely on legacy on-premise software – that is, a wide range of programs installed on the company’s local IT servers. This “software landscape” often consists of disparate applications plugged together – heavily modified over the years and frequently not up to date with the latest innovations. These complex systems are costly to maintain, and they make it difficult for companies and their leaders to respond to challenges and opportunities with agility and speed.
AI applications, too, face major obstacles in legacy systems: They have a hard time grasping the company’s inner workings, making sense of fragmented and widely distributed datasets, and may not be able to find certain key information.
The first step towards powerful business AI, therefore, is the move from legacy on-premise software to modern cloud software – that is applications that are centrally managed and maintained in professional data centers, constantly updated with new innovations, and tightly linked so information can flow freely between the different parts of the company.
For companies today, this so-called cloud migration is faster, smoother and more transparent than ever before – thanks to the proven methods and advanced digital tools now available. And the prize is larger than ever before, too: integrated cloud applications work together out of the box and cover the company’s software needs end-to-end across departments. This integration allows a car maker, for example, to reduce time and cost – say, from receiving an order through the vehicle’s production to its final delivery. Similar benefits extend to all other industries and workflows.
A cloud migration, consequently, is more than an IT project: it is the digital foundation for a thorough modernization of the entire enterprise, for moving from “good” to “great.”
Once in the cloud, companies can add advanced data management solutions with little effort. Think of advanced data management as a magic filing cabinet: it automatically stores and organizes all documents, all information, all data automatically in the right place and in perfect order – always up to date, perfectly searchable, without duplicates and errors, smartly annotated, and everything in the right context.
In their combination, integrated cloud applications and advanced data management allow company leaders a holistic view of their enterprise. At the same time, they enable AI technologies to access, understand, and facilitate transactions across the company – assisting human users with repetitive tasks as well as with deep analyses and insights. And the next evolution is already at hand: Based on integrated cloud applications and data management, digital coworkers – also known as “AI agents” – are now able to carry out complex work assignments. For example: find overdue invoices, identify what went wrong, resolve the issue, and make sure payment targets are met.
Realizing the tremendous benefits of AI is thus about going on a journey: from on-premise software to cloud applications, then onwards to modern data management and the use of AI agents throughout the enterprise. It is this journey that unlocks the tremendous potential so many see in AI – and enables us to completely reimagine how our businesses and economies are run.
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