Where to Deploy AI in Business First? Try These Real Use Cases That Deliver Positive Returns

February 23, 2024

In the dynamic world of business, artificial intelligence (AI) and machine learning (ML) have evolved from visionary concepts into key drivers of change across many sectors. Find inspiration among real use cases that demonstrate how AI can redefine business processes and strategic decision-making.

AI Optimizes Manufacturing and Logistics

Artificial intelligence significantly transforms manufacturing and logistics processes, enhancing operational efficiency and increasing customer satisfaction. Its use in planning and maximizing the use of transportation space, along with the ability to track shipments in real-time, provides organizations with precise delivery schedules, improving the customer experience and saving the environment.

The most common use cases in the manufacturing and logistics segment include:

• Reducing costs related to logistics and transfers between warehouses.
• Reducing CO2 emissions for more environmentally friendly operations.
• Minimizing the amount of packaging materials used and maximizing the use of transport vehicle space.
• Enhancing planning systems to allow for immediate, ad-hoc adjustments.

Škoda Auto Saved 160 Tons of CO2 Thanks to AI, Reducing Time and Costs

A standout innovation in this field is the OPTIKON platform, which revolutionizes the way transport containers are loaded for approximately two thousand different types of pallets. Its deployment in just one year led to a reduction in the number of train shipments by five at Škoda Auto, corresponding to a saving of approximately 160 tons of CO2 emissions. This business case highlights the benefits of AI for both the environment and the efficiency of logistical processes.

Petr Švarc, head of the AI Competence Center at Škoda Auto, praises the solution for the company: “Together with our strategic partner, Blindspot AI from the Adastra Group, we developed the OPTIKON system, which solved our challenges associated with loading pallets into containers. Thanks to the proactive and highly professional approach of the experts from Blindspot, we developed and deployed algorithms that consider all our needs and the limitations associated with loading in a very short time.”

Read the full story in the interview.

160 tons of CO2 emissions were saved annually

30 seconds to calculate the optimal loading combination

Barum Continental: Optimized Inter-warehouse Transport Reduced Transportation Costs

AI advances levels in finance, telecom, and other services

The deployment of artificial intelligence in finance, insurance, and telecommunications significantly enhances operational efficiency and decision-making. Algorithms analyze extensive financial data sets, enabling banks and other institutions to more accurately assess the risks of loans and investments. AI also simplifies repetitive interactions with clients, ensures real-time data verification, and strengthens fraud detection capabilities.

The most common use cases in the service sector include:

• Transforming customer support through automation, from initial onboarding to advanced chatbots and virtual assistants.
• Identifying and reducing the risk of fraud in complex systems.
• Optimizing shift planning with the ability to flexibly and instantly reschedule.

The AskYourData platform is an interesting example of using generative artificial intelligence in services, serving as an assistant for automated processing of queries from both customers and employees. Within a simple chat interface, it provides quick and reliable answers in natural language, based on the interpretation of provided internal data sources. It is particularly useful in customer service, where it uses an extensive knowledge base to provide comprehensive answers for the quick resolution of various problems.

Zonky automated more than half of user registrations using AI

Another proof of the power of artificial intelligence in process automation comes from Zonky, a consumer credit provider, which radically transformed its registration process. By automating over 50% of user registrations through document extraction with AI, the company reduced the registration time from days to minutes, saving the equivalent of more than 10 full-time positions.

50% increase in efficiency of document transcription

10 FTE saved

TÜV SÜD: Automation Improved Inspector Scheduling and Reduced Workload

AI Revolutionise Retail 

AI is revolutionizing the retail sector by streamlining operations, enhancing security, and improving overall customer experience. It eliminates long queues, speeds up and optimizes product delivery, and enables quick detection of suspicious activities among both customers and employees, thus bolstering security measures.

Common use cases in the retail segment include:

• Personalized customer experience, tailored offers, and gaining new insights from customer data.
• Improved workforce planning and logistics, along with swift planning adjustments.
• Utilization of chatbots and virtual assistants for automated customer support.
• Early detection of fraudulent activities, anomalies, and undesirable behaviors.

A Czech Food Giant Reduced Logistic Costs by a Third and Expanded Its Market

A compelling example in the retail sector is the case of a Czech food manufacturer and retailer who transitioned from manual to digital logistics using the optimization platform Adastra OptiSuite to enhance and expand its distribution routes. This sophisticated solution, surpassing traditional methods, helped the company optimize its logistic operations, resulting in a significant 30% reduction in transportation costs. The solution standardized delivery processes, increased efficiency, and facilitated the company’s expansion into new markets.

30% reduction in logistic costs

AI Enhances Operational Safety

Artificial intelligence also enhances workplace security by detecting unauthorized access and alerting to breaches of security protocols in real-time.

The most common use cases in operational security include:

• Automated anomaly detection, such as in network data or behavior.
• Uncovering hidden risks and unknown trends.
• Reduction of false positives.
• Improvement of operational efficiency in production lines.

AI Is Transforming Security Measures Across Sectors

AI technologies significantly enhance security protocols both in the workplace and in public safety. For instance, a major automotive player in the Czech market utilized AI for anomaly detection, reducing machine downtime by 20% and proactively addressing maintenance needs to enhance workplace safety. Similarly, innovative AI applications by Avata Intelligence optimized police patrol strategies through a criminal behavior model, resulting in more effective crime prevention and community safety. These examples underscore the pivotal role of AI in supporting safer environments and operational efficiency.

20% reduction in machine downtime

Start Transforming Your Business with AI Today

Get employee buy-in for fast, impactful AI results

Feeling the pressure to implement AI in your company and wondering where to start to see results quickly? Need to engage key employees in the change but don’t want just another round of training?

AI Days are one-day workshops tailored to individual companies to directly identify specific use cases for AI involvement in their business and guide them on the path to success and rapid results.

Positive ROI
Low risk
Visible results

We’ll engage your key stakeholders in a discussion to collectively identify the best use cases for your business and assess the benefits and risks. By the end, you’ll have 3-5 cases with high potential ready for Proof of Concept development, allowing you to quickly verify their feasibility and added value.

“We believe that understanding the potential of AI is the first step towards transformational success. AI Days is not just a series of corporate workshops; it’s a catalyst for innovation and an investment in the long-term future of your company designed to deliver tangible results from day one,” says Ondřej Vaněk, Chief AI Officer at Adastra.