From the automation of tasks to the analysis of data, AI is proving itself a catalyst for business transformation. Yet, many leaders still ask: Where can AI actually deliver results? Are the benefits of AI worth the investment?

In this article, we explore practical, proven AI use cases across finance, HR, marketing, and supply chain operations that demonstrate how it is delivering measurable impact. You’ll see how AI can help employees make better decisions, streamline operations, and unlock new revenue streams.

The AI use cases below are a few examples of the AI line of business solutions that many organisations are implementing—and gaining value from—today. If you’re interested in a deeper exploration of AI use cases and the SAP technologies that make them possible, read our e-book, AI in Action: Practical use cases for real business results.

The benefits of AI in business

For executives focused on productivity, efficiency, and innovation, the benefits of AI in business are clear: It helps organisations operate more intelligently, adapt more quickly, and compete more effectively in an increasingly complex market.

Across industries, organisations are realising gains in five core areas:

• Productivity and efficiency: Automating repetitive, manual tasks (such as data entry) to free up human talent for higher-value work.
• Decision accuracy and speed: Utilising real-time data, advanced analytics, and predictive models empowers employees to act with confidence.
• Customer experience: Providing personalised, timely, relevant interactions that foster customer loyalty.
• Innovation and growth: Uncovering hidden insights that can lead to the development of new business models, products, and services.
• Resilience and agility: Enabling organisations to respond rapidly to market changes, supply chain disruptions, or shifts in customer demand.

The AI use cases that follow illustrate where these benefits are having the greatest impact.

AI in finance

Finance teams use AI to automate manual, repetitive processes and inform decision-making.

Automating payment reconciliation: A historically time-consuming task that is prone to errors, which can result in delayed closing and strained cash flow. AI can accurately reconcile invoices with the corresponding internal documents before authorising payment. It does this by analysing historical data and applying pattern recognition to remittance behaviour.

With over 7,000 clients across 120 countries, this was vital for Accenture. Before they began using SAP Cash Application software to match invoices, they were processing 250,000 entries manually. Afterwards, they were able to automate the process with greater accuracy, with 54% of invoices automatically clearing.

Predicting late payments: By using AI to analyse historical patterns and customer behaviour, finance teams can detect early warning signs of late payments, enabling them to take a more proactive approach to managing liquidity and investment timing.

Best of all, every user can access these insights with natural language prompts—and without the assistance and technical skills of analysts. With accessible answers, finance teams can act more quickly and with greater confidence.

AI in human resources

AI is streamlining how HR departments recruit, interview, and hire talent that best fit the goals of their wider organisations.

Creating job descriptions: Attract leading talent with engaging and inclusive job descriptions. One of the main benefits of AI is that it can generate high-quality writing with speed and consistency at scale, with less bias and ambiguity.

Screening candidates: AI tools can accurately highlight candidates who are best suited to the position. This saves recruiters the time-consuming burden of scanning through hundreds of CVs and prevents high-potential applicants from going undiscovered.

By adopting SAP SuccessFactors, Frit Ravich, a distributor of crisps, snacks, and nuts exporting to 27 countries, could make it easier for candidates to apply and for recruiters to match them to open positions.

Smarter performance management: For employees who are already on board, AI can suggest goals that support their personal development and their team's priorities. This alignment encourages employees to remain engaged in their roles and invested in their organisation.

American Honda uses this approach to close the skills gap: the skills they require versus the skills their workforce may possess.

AI in customer experiences

Like finance and HR functions, marketing and commerce teams are reaping the benefits of AI by using it to automate manual tasks and uncover hidden insights in their data.

Forecasting customer behaviour: AI can analyse engagement patterns, browsing behaviour, purchase history, and other intent signals to highlight leads with the highest potential to convert. This enables marketing teams to target them with timely and relevant campaigns.

Product content creation: By drawing on structured data such as specifications, features, and pricing, AI can generate accurate product descriptions. They can even ensure that content aligns with audience preferences and SEO strategies. Marketing teams can instead focus on shaping brand-building and other higher-level storytelling initiatives.

Sales order entry: When a customer finally decides to purchase, AI can automate the capture of the order data from emails and scanned documents and consolidate it all in one place. Freed from the manual, repetitive, and error-prone burden of data entry, sales teams can focus on nurturing new customer relationships.

Optimising customer service: AI agents can work in tandem with human customer service teams to deliver faster responses, better first-time resolution rates, and more consistent service quality.

For example, Bosch Power Tools uses AI agents to analyse the content and context of each of the millions of customer service tickets they receive per year and directs them to the appropriate team for assistance. Not only does this approach save thousands of hours annually—it also significantly reduces costs.

AI in supply chains

From geopolitical uncertainties to trade restrictions, supply chain leaders face more challenges than ever before. AI is helping them anticipate disruption and detect discrepancies to maintain continuity of service.

• Identifying supply chain risks early
  Every second matters when it comes to mitigating disruption. AI can monitor logistics, stock, and operations data to detect anomalies before they lead to costly delays.
  
  By embedding AI in planning, Microsoft substantially reduced finished goods stock and proactively mitigated stock risks in its global hardware business, transforming their reactive supply chain into a real-time, predictive model.
• Accurately anticipating demand
  AI-assisted forecasting uses machine learning to adapt to changing market conditions in real time, enabling decision-makers to prevent shortages or overstocking.
• Processing goods receipts more quickly
  When goods arrive at the port, processing delays can have a knock-on effect throughout the supply chain. AI tools can streamline this process by scanning and matching receipts quickly and accurately.

How to implement AI in business operations

The potential of AI in business is clear. The path to actually implementing it is much less straightforward.

Implementing AI in business requires readiness within your workforce, alignment with business needs, and the establishment of measurable goals.

These are all vital elements—and we have a guide to help you define them.

Read our e-book, The Path to AI Implementation, to learn how to bring the benefits of AI to your organisation.

From assessing initial readiness to measuring success, the steps outlined in this guide are designed to help you move forward with confidence and towards measurable results.

Get the full story

These AI use cases make one thing clear: AI isn’t just a tool—it’s a game-changer. Finance teams are using it to navigate complexity and uncertainty with agility. HR departments are using it to attract and retain talent. Marketers are using it to handle lower-level tasks so that they can focus on higher-level strategy. And supply chain leaders are becoming more proactive planners.

If you are ready to bring the benefits of AI to your organisation—or would like to learn about more AI use cases in sales and procurement, download our AI in Action: Practical Use Cases for Real Business Results e-book. It’s essential reading for business leaders seeking to unlock AI’s full potential.

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